The AI and Games Newsletter brings concise and informative discussion on artificial intelligence for video games each and every week. Including industry news, innovative research, emerging trends, and our own exclusive editorial and reporting.

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Greetings all and welcome to this week’s edition of . This week we’re covering some headlines, some new talks and case studies from us, and chat a little bit about the latest Xbox reset (or reset of the reset?) and what it might mean.

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Announcements

A couple of quick announcements coming your way.

New Case Study: Alien - Rogue Incursion

Live now on YouTube, and coming to the website tomorrow is our latest case study. To celebrate Alien Day - April 26th given the perfect organism is discovered on the planet LV426 - I dig into the pathfinding and encounter design systems in Servio’s Alien: Rogue Incursion - the first VR title based on the popular sci-fi franchise.

AI and Games Conference 2025 Talks

Plus your weekly dose of new talks going live on YouTube from the 2025 AI and Games Conference! Once again with thanks to our recording partners Xsolla!

From Cloud to Edge: Optimizing Small Language Models for Game Applications on AWS
Patrick Palmer & Andrei Muratov / Amazon Web Services

Patrick and Andrei showcase how developers can leverage AWS to prepare small language models that run directly on phones and desktop computers. Demonstrating practical approaches for fine-tuning open-source models for specific gaming needs, enhancing them through distillation techniques, and optimizing for edge performance.

Use Cases and Practical Methodologies for Reinforcement Learning for Learning at Agents at Scale
Huntting Buckley, Duncan Davis & Kyra Wulffert / Databricks

As games continue to build diverse and dynamic gaming experiences, there is constant pressure to be able to iterate quickly, adjust NPC behavior and create more and more dynamic content. The team from Databricks, including Huntting Buckley (Databricks Global Games Strategy Leader), Duncan Davis (Lead Solutions Architect for Games) and Kyra Wulffert (ML Specialist) dive deeper into these topics.

AI (and Games) in the News

A quick round up of some of the headlines from the past week or so. We have not one but two headlines related to AI consuming compute hardware again, so I’d recommend checking out last week’s overview on the subject if you fancy a primer!

• The Steam Controller Won’t Be Delayed Due to AI [Kotaku]

  In a move that isn’t all that unexpected, Valve are moving forward with releasing the Steam Controller next week after delaying their 2026 hardware line-up. The big reason? Well, there’s no RAM in the controllers…

  • I think that’s going to be my new reaction when I see the price of things: “What’s it made out of? RAM???”
    

• Your CPUs Aren’t Safe from the AI Goldursh [Tom’s Hardware]
  Another not entirely unexpected headline courtesy of Intel that having gouged the market of RAM, SSDs and GPUs, the AI industry is going to go after CPUs next. The reason for this is that while much of Machine Learning and Generative AI training is conducted on GPUs with high-bandwidth memory, the deployment of the trained models later on can transition towards CPUs - and notably CPUs with AI compute cores in them, that Intel now specialise in! A big reason for this is also the surge in interest (and promotion) of Agentic AI: systems where you glue multiple AI agents together to work on larger and more complex tasks.
  

• Blender Takes Money From Anthropic, Chaos Ensues [Blender]
  A story that kicked up a lot of online furore just last night, 3D modelling company Blender announced a partnership with AI company Anthropic - largely known for the Claude LLM and Claude Code tools. In the announcement Blender declared Anthropic are signing up to a be a corporate patron of the Blender Development Fund. There was little to be said in the official announcement, but people were kick to point out Anthropic no doubt want to pump money into Blender in pursuit of their tools, their audience, and their market so they have a new industry to pilfer. Given Blender has largely build a positive reputation among game developers over the past decade as a champion of free and open-source 3D creation tools, this has unsurprisingly pissed off a large proportion of their userbase.
  
  As of this morning, the press release has been updated to include the following: “This announcement is causing a lot of feedback. We are actively evaluating it. Reach out to Blender Foundation directly if you wish to share more feedback.”
  
  Since they didn’t do the write thing and point out how to contact the Blender Foundation, you can do so at foundation (at) blender (dot) org

Does Xbox’s New Vision Align with Microsoft’s AI Ambition?

The story that certainly caught the most attention last week was the new Xbox head Asha Sharma’s message sent to Xbox employees. This memo sought to establish the philosophy that Sharma and president of game content Matt Booty will bring to their tenure as leaders of Xbox. The memo, entitled “We Are Xbox” was bound to be leaked within minutes of it being published - and true enough it popped up on the Verge not long after. Though it seems the Xbox team figured they should just publish it on the Xbox Wire and aim for some easy wins.

It’s a very safe announcement that lacks in any major commitments, but with enough platitudes and immediate changes to low-hanging fruit that seem designed to garner favour with the online masses. This includes:

• Renaming Microsoft Gaming back to Xbox: A change of business stationary that ultimately means very little. After all, it’s not like people were lining up to buy the ‘Microsoft Gaming Series X’ were they? The PlayStation division seems quite happy to continue to be called Sony Interactive Entertainment.
  

• Game Pass Pricing Changes: The Microsoft Game Pass Ultimate subscription has dropped from $29.99 a month to $22.99: that’s a drop from £22.99 to £16.99 for us over here paying with the King’s pounds. Now for £2 more a month than what you were paying six months ago, you now get the pleasure of the Game Pass library without the joys of day-one access to Call of Duty. After the rather lacklustre Black Ops VII it seems an extra £2 a month to avoid it is reasonable.

The rest of the piece is very much about transforming Xbox as they seek to re-establish what the publisher is under new leadership with some strategy areas focussed on new hardware (the upcoming Project Helix), expanding into China, focussing on live-service products (ugh), and ‘fixing the fundamentals’ to restore trust with Xbox players.

We Are Xbox - Again

Now this has certainly caught my attention because you might recall that back in January I had ‘The Death of Xbox’ as #9 on my 10 predictions for the year. To quote the issue from January 14th:

By the end of 2026 there will still be Xbox consoles on the shelves - assuming stores keep selling them. But unless efforts are made to improve the public image of Xbox and the value it is bringing to players as a platform, the console space they operate in will be largely a net loss, and the brand would be best served as a games publisher on PC, PlayStation and Nintendo.

I argued that Microsoft’s aggressive push to become an AI company that sells tools nobody wants to buy has proven to be a significant detriment to the handful of things it does right. Xbox players - myself included - have little to be happy about, as studios are shutdown, games are cancelled, and prices increase as Microsoft reportedly aimed for a 30% profit margin - a rather unrealistic target for a games publisher and platform holder.

As we’ll get into momentarily I’m incredibly cynical about all of this, but credit to Sharma and the rest of the leadership in showcasing there’s an effort to do something. As I said in January, something needed to be done, and this seems like a step forward in that regard. Sure, it reads like it was written in Copilot, but it speaks to a collective understanding of a malaise that sits across Xbox as a brand that needs to be addressed.

Sharma addresses this directly in one of the opening lines of the memo, stating that “players are frustrated” at the state of Xbox and the games industry as a whole. That the old model pushed by Phil Spencer and Sarah Bond was no longer working, so they need to move in a different direction.

Stop Me If You’ve Heard This Before

All that said, it’s interesting how you can repackage the same ideas again and again under a corporate reset. Sharma is treating this like taking on a position in government. I mean, she openly says that at the time of the memo she was 62 days into the job. Expect a big PR stunt in a months time when we hit the 100 day mark.

But then half of it is stuff Phil Spencer was pushing for: engaging with 3rd party developers (notably those in Asia), strengthening the portfolio of franchises, reinforcing the slate of titles coming to the platform, cloud play, Game Pass, supporting ongoing live-service games like Sea of Thieves, Elder Scrolls Online, Fallout 76 and Minecraft (yeah, Minecraft is a live-service game).

In fact right now the things that are going well for Xbox are largely down to a lot of initiatives that Spencer and his team fought for years to put in place. The Xbox line-up has been consistently strong over the past two years:

• 2024: Senua’s Saga, Avowed, Indiana Jones and the Great Circle, Ara: History Untold, Diablo IV: Vessel of Hatred

• 2025: Outer Worlds 2, Ninja Gaiden 4, DOOM: The Dark Ages, South of Midnight, Tony Hawk’s Pro Skater 3 + 4, Gears of War: Reloaded, Elder Scrolls IV: Oblivion Remastered.

Meanwhile 2026 is shaping up well with Kiln out now, Forza Horizon 6 next month, plus Halo: Campaign Evolved, Fable, Minecraft Dungeons II and Gears of War: E-Day planned for the rest of year. Though many projects have subsequently been cancelled given Spencer’s push to purchase Activision. He’s certainly made many of his own mistakes over the years.

Killing the ‘Everything is an Xbox’ PR push will help to consolidate the brand a little. But I find this press release interesting in that while I stifle a yawn it also reads like two separate stories published in the same post.

A Reset to Business As Usual?

So one of the lines that stuck out to me was as follows:

Along the way, we will reevaluate our approach to exclusivity, windowing, and AI, and share more as we learn and decide.

Now of course, yes, AI is mentioned here. But it’s just one part of a larger meta-narrative going on, and how that fits into the broader eco-system of Microsoft as a whole. After all the real emphasis of where Xbox is going can be seen just a few paragraphs earlier - emphasis mine:

Xbox will be built to be affordable, personal, and open. We will offer flexible pricing so it’s easy to get started and keep playing. The experience will adapt to you, letting you customize how you play, helping you find what you’ll love, and connecting you with the right people. And we will be open to all creators, from individuals to the largest studios, giving anyone the tools to reach a global audience and keep their games growing over time.

Our new north star will be daily active players.

Now when you take the latter in context of the former, the math doesn’t really add up. If we’re keen on maximising and stabilising daily active players, then exclusivity makes little sense - plus they’re still trying to justify that Activision Blizzard purchase after all. Sure, windows might shift, but then having delayed releases on non-Xbox platforms may prove more harmful than otherwise. In the past year Xbox’s titles have proven quite successful on PlayStation, but then Sony are returning to exclusivity given their PC ports don’t really sell that well - admittedly how much of that is down to the fact that by the time they hit the market, they’re often 2-3 years late? If you’re interested in maximising DAU, going back to hardcore console exclusivity is simply implausible.

Besides, I sincerely doubt the next Call of Duty will be removed from or released later to PlayStation. Not just because it’s the game’s largest market, but it runs risk of exacerbating the opposition against Game Pass that the FTC argued just a couple years prior.

Then of course everything about maximising experience, given players options, and opening up to creators very much plays into the entire AI playbook that Microsoft have been playing from. At present, we’ve yet to see much of what Microsoft hopes to bring to Xbox with AI. At best there’s been the Gaming Copilot announcement? Right what little dialogue there’s been about AI impacting Xbox has largely came from elsewhere in the company as they make a lot of noise about things like Microsoft Muse - with CEO Satya Nadella highlighting how little he understands video games and the work his own researchers do by proclaiming it was the future of game development (sigh, no…). Not to mention that of course their Xbox hardware is now significantly more expensive than it was at launch because the parent company is in amongst the data centre hardcore that’s causing prices to increase.

Right now it seems like the easy wins Sharma can achieve in AI is just to keep quiet for a while. But then it’s her bosses that are the bigger problem with player’s perceptions of how AI will affect Xbox right now. Though I doubt she can send the big boss-man a Teams message asking him to pipe down…

Pushing all of my tired cynicism aside, I do hope for the best. I want Xbox to succeed and the more competition we have in the sector the better off the industry is, and I hope Booty and Sharma can execute on their vision. Just don’t be surprised if we’re sitting here at the end of the year and nothing’s really changed.

The AI and Games Newsletter brings concise and informative discussion on artificial intelligence for video games each and every week. Including industry news, innovative research, emerging trends, and our own exclusive editorial and reporting.

Subscribe now

You can subscribe to and support AI and Games, with weekly editions appearing in your inbox. If you’d like to work with us on your own games projects, please check out our consulting services. To sponsor, please visit the dedicated sponsorship page.

Hello and welcome to this week’s edition of . For this issue, I wanted to pick up on a reader-voted topic from earlier in the year, and start taking a crack at it. We’ve seen a lot of news stories of late about the impact that AI is having on gaming hardware, with everything from the PC components to games consoles and even the impending Steam Machine seeing price increases as a result.

This week it’s a high-level overview as to why this is happening, but going into it in a little more detail than most other outlets. I wanted to paint a more accurate picture of why this is happening, how it was foreseeable, and why it is not an easy fix.

Follow AI and Games on: BlueSky | YouTube | LinkedIn | TikTok

More AI and Games Conference 2025 Recordings

Before we get into the meat of the issue, we have more conference talks for you! Following the release of presentations from BitPart.ai and Havok last week, two more talks from last year’s event just dropped on our conference YouTube channel this morning.

Predicting Combat Outcomes in Total War
James Kwan and Miguel Lopez-Bachiller, Creative Assembly

One of the features of Total War games is the ability to auto-resolve combat: rather than have two players fight it out, the system can simulate the outcome. This is a useful feature both for players, as well as the in-game AI, given they can use the outcome of the simulation to decide whether to even engage in conflict. In this talk we hear about a new approach to improving the auto-resolver using machine learning. By collating a large amount of data by having armies battle it out, it helps create a more accurate prediction model based on how they actually performed across a variety of conditions.

When Research Meets Release Dates: Production-Grade Reinforcement Learning for Games
Wes Kerr, Riot Games

We hear a lot about how to use machine learning, notably reinforcement learning, as a means to enhance gameplay. But the reality is it’s quite difficult to do that during the ongoing development of a game. We hear from Wes Kerr, who leads the Tech Research team at Riot Games as he highlights the lessons learned from working at the intersection of research and live games. How safety, evaluation, and reliability are paramount when you’re working on ever-evolving and player-facing content. Plus we get some insight into lessons learned in this approach as the team opted to try a different approach for the creation of bots for Riot’s fighting game 2XKO.

The AI Ram Crisis Part I: How Did We Get Here?

In recent months we’ve seen much discussion online, be it on this newsletter or elsewhere about AI’s impact on the cost of computing, and what this is doing to the production and retail costs of consumer products. This surge in pricing, which has been nicknamed the RAMpocalypse, RAMmageddon, and much-more besides, stems by-and-large from the surge in business activity surrounding (Generative) AI.

This have seen significant impact across the gaming space. Consoles such as the Sony PlayStation and Microsoft’s Xbox Series S|X have seen prices increase first in late 2025 and again in 2026 as a combination of both component costs and previously the US tariffs. The Nintendo Switch 2 has not seen a price increase yet, but peripherals did receive a price adjustment in the United States at launch as a result of the tariffs issued at the time. Valve’s Steam Machines have been delayed given the price tag has been hard for them to nail down. Meanwhile just last week, the Meta Quest 3S and Quest 3 VR headsets saw an increase of $50USD and $100USD, with the “the global surge in the price of critical components - specifically memory chips” being the root cause.

But it’s not just the consoles that are suffering, if anything it looks much worse when you look elsewhere. The same chip shortages are resulting in price increases for memory in your computer, combined with GPUs and solid-state-drives (SSDs). Leading not just to inflated costs for upgrading your computer, but also it has a trickle-effect for other consumer products such as laptops, smartphones, and virtually every consumer-grade product that needs chips for core functions. It’s so bad that Nvidia are planning to re-release old GPUs because they’re cheaper and easier to manufacture in the current climate.

As is well-known, the surge in pricing is largely being triggered by the significant amount of investment into Generative AI. However, it might not be obvious why exactly this is happening.

So for this edition, it’s the first of a beginner’s deep-dive into the issue, we’re going to talk about:

• What are the shortages that are actually occurring?

• Why is this happening?

• How did this situation even come to pass?

Then in a follow-up issue we’ll dig deeper into what the future looks like, and how this may potentially resolve itself, and the bigger industry challenges this presents going forward.

The Problem Statement

So let’s start by getting into what the issue is, and how this manifests. It all starts with the chips used in the manufacturing of specific computing components, and then it’s the AI industry’s interest in them that has caused the supply chain issue.

What Exactly is in Short Supply?

As we explained a moment ago, the issue is appearing in a variety of consumer products, and most notably in PC and gaming hardware, but it all stems from a single resource: the manufacture of memory chips for computers.

If you’re not familiar, memory for computers comes in two forms: volatile and non-volatile. The former is memory that only maintains information when an electrical current is passed through it, while the latter will persist over time. So volatile memory covers things like Dynamic Random Access Memory (DRAM) that used in a computer or games console to allow us to store information about the game temporarily so it can then be used thereafter. Meanwhile non-volatile memory is typically NAND or ‘flash’ memory, which is used in the likes of SD cards, solid-state hard drives, and the memory on devices like smartphones.

Both DRAM and NAND memory come in all different shapes and sizes, and over the years chip designers have built a variety of permutations with different storage capacities, data transference rates, and other costs. You’ll find forms of both types of memory built to support the likes of mobile devices, consumer-grade PCs and games consoles, but also cloud computing and server infrastructures. Plus it’s worth mentioning that even the likes of CPUs and GPUs used for both core logic processing and graphics rendering on these devices use smaller numbers of these memory types to handle specific aspects of their execution such as Cache Memory, which is very short-term memory that is very fast and connected right to the CPU for when it is doing any type of calculation.

However for the most part, the average person will have noticed the discussion around memory is usually focussed on consumer-grade PC specifications and games consoles. Over the past 15+ years the big ongoing development in consumer memory is what is known as Double Data Rate or DDR RAM. Throughout much of the past decade DDR4 was the dominant memory on PCs throughout the mid-2010s, with the Xbox Series S|X using GDDR6 (a variation used to support GPU processes) and the PlayStation 5 uses a mixture of DDR4 and GDDR6 - with the PS5 Pro also having a smidge of DDR5 in there. At the time of writing it is still rather common for computers to use DDR4 or 5 for ‘traditional’ compute processes , while GDDR7 is the hot commodity, and is commonly used for graphics rendering and, oh yeah… AI.

What Does AI Have to Do With It?

So yes first and foremost GDDR7 is something of use to AI, given it’s designed to allow for fast data processing. But the real issue isn’t in GDDR7 but what we call High-Bandwidth Memory (HBM), which is designed for use in data centres, or in things like Nvidia’s dedicated AI compute devices such as the H100 where it’s integrated into the chip alongside a GPU.

Now the thing is, HBM essentially re-uses traditional DRAM technology, but it’s just built differently. It sticks DRAM into a vertical stacking setup that allows for - as the name implies - incredibly high bandwidth of data processing. A traditional HBM3, which has around 8-12 stacks of DRAM in it might have a smaller raw capacity than DDR5, but it will 10x-15x the throughput, and this allows for it to be used in processing for Generative AI models, which pump through hundreds of GB of data very quickly during both training and real-time execution (aka inferencing).

Right now everyone from OpenAI to Nvidia, Microsoft, Oracle and more are pushing for the investment in AI data centres that help with their rolling out of their tools and services. There are even concerns from these companies that data centres are not being built fast enough. Though what market actually exists for these data centres has yet to be properly defined, and is rather unclear.

I’ll refrain from editorialising at this stage as to the worth or need for these data centres, and the shady financing going on to get these projects off the group. But for now let’s just deal with the reality that this is happening, whether we like it, or want it.

The WHAT: TLDR

So what is happening really boils down to the following:

• As the hype for Generative AI continues, so too is the demand for large-scale AI datacentres.

• As more and more datacentres are built to host large-scale AI models, it needs a lot of HBM to function at the scale suggested by Generative AI such as GPT

• The increased need for HBM memory consumes the available DDR memory in the market.

In the past year we’ve seen the cost of traditional hard drives, SSDs, GPUs, and DDR RAM increase significantly as a result of this bottleneck that is emerging, with DDR5 RAM in particular shooting up by more than 400%.

Why Is This Happening?

Having covered the what, let’s get into the why. Why is HBM consuming the supply chain market? Well in order to do that, we need to spend a little bit of time discussing the how. How semiconductors, the micro-level components used in the likes of DRAM and HBM, are actually built.

Semiconductors are built courtesy of what are known as fabrication plants or ‘fabs’. These plants are incredibly complex and expensive facilities designed to etch electronic circuits onto semiconductor wafers - typically made from silicon - at an unbelievably small scale. For context most wafers are millimetres in size, with circuiting etched into them at microscopic levels. Since the boom of semiconductor manufacturing began in earnest in the 1960s, we have seen the size of individual transistors used as part of circuitry reduce from the micrometres (i.e. thousandths of a millimetre), to nanometres (i.e. thousandths of micrometres), with contemporary transistors manufactured at around 7 nanometres and smaller. By comparison, nucleotides that compose DNA in organic life are around 1.5 nanometres. That’s how small we’re dealing with here.

Now I bring this up because as you can imagine, this is a highly complex and expensive proposition. Etching silicon - the part of using lasers at precise microscopic sizes to create the circuits - is but one of many steps taken to ensure the final chips are going to work and are of suitable quality. On average it takes 10-15 weeks for a chip to be made depending on the size of the etching as necessary cleaning and preparation of the silicon is required. Plus there is extensive testing of individual transistors before stitching them into more complex chips. The subsequent creation of the complete product, which often is sticking dozens of fully manufactured chips together, can take months if not longer. All of this requires a huge amount of resources, both in terms of human expertise, but the amount of hardware required to manufacture at this level of precision. The number of companies that manufacture specific components needed for a particular process, notably in areas of photolithography (the lasers that draw circuits onto the silicon), are often in the single-digits - and cost tens if not hundreds of millions of dollars.

As a result, the number of places that can actually manufacture chips at different wafer sizes is incredibly small. From data produced back in 2023, there are just over 1000 chip fabs worldwide, though they are often specialised against specific wafer size and composition. As we can see in the table above, there are less than 100 fabs in the world that can manufacture chips on wafers that are 2 inches in size. So if you’re seeking to manufacture these chips, your options are even more limited than operating on larger sizes. Though it’s worth stressing the most common wafer sizes for contemporary PC chips for the likes of CPUs and GPUs are in the 8inch/200mm - 12inch/300mm region.

In addition, the vast majority of these fabs - regardless of wafer production size - are based in Asia. While the concept of the semiconductor and much of its initial development and manufacturing started in Silicon Valley in the United States - which is how it got its name - much of fabrication was offloaded to Asian markets in the 1970s. This has led to Taiwan becoming a global powerhouse in semiconductor manufacturing. The Taiwan Semiconductor Manufacturing Company (TSMC) is not just the largest non-US company in the world (worth ~25% of Taiwan’s GDP), but it controls around 70% of the global market share for semiconductor chips.

Fabrication is the Bottleneck

TSMC has developed a leading edge in the space given it doesn’t design chips, it’s sole focus is in fabricating them. This helps cement TSMC’s position as the world’s leading chip fabricator, because they’re not in competition with chip designers, they’re simply helping them achieve their ambitions.

As I mentioned, most US-based companies offloaded their fabs between the 1970s and 1990s as a means to cut costs, given they knew it was more cost effective to outsource to factories in Asia rather than maintain them in the United States. The prospect of a significantly cheaper yet equally skilled labour force was all too alluring. Hence in the modern day, many have focussed solely on becoming chip designers - referred to as ‘fabless manufacturers’. This means that the vast majority of major chip companies you associate with computing don’t actually make their own chips. This includes the likes of:

• Nvidia: Famous for their gaming GPUs and more recently their AI NPUs like the H100.

• AMD: Nvidia’s competitor who are increasingly involved in designing chips for games consoles such as as the PlayStation and Xbox.

• Apple: The chips made for the Macbook, iPhone and iPad are designed by the tech giant, but manufactured by TSMC.

• Arm: Creators of CPUs for mobile devices that are used in Raspberry Pi’s, Samsung Galaxy smartphones, and even the Nintendo Switch 2.

• Qualcomm: The designers of the Snapdragon chipset, used in the likes of the Meta Quest 3 VR headset.

At the time of writing, Intel is the only major computer/gaming chip manufacturer that actually owns chip fabs, and runs around 15 different sites around the world. Decades ago this was frowned upon as a huge cost for them, and has since proven to be less of a liability and more of a strength.

The same can’t be said for memory. While there are only a handful of companies in the world that produce commercial-grade NAND memory, the big difference is that almost all of them operate their own fabs:

• Samsung: While many will know them for their consumer grade products, Samsung is one of the largest and most successful (Arm-based) CPU and NAND fabricators in South Korea (with sites in United States too).

• Kioxia: A spin-off from Toshiba (where it was originally called Toshiba Memory), it was the company that created NAND memory in the 1980s, and is one of if the largest producers of RAM and solid-state drives in Japan.

• Western Digital: While they have a handful of sites in the US, the bulk of their manufacturing occurs in Asia, but they don’t run their own fabs. They collaborate with Kioxia in Japan instead.

• Micron Technology: Hosts a variety of fab sites across the US, Taiwan, Japan, Singapore and China.

• SK Hynix: Another major South Korean NAND manufacturer with fab sites in their home country, plus in China and the US.

Now to give you an idea of the scale of manufacturing, as far back as 2021 it was suggested semiconductor sales reached 1.15 trillion units, with over $570 billion in sales. Yet the whole thing is largely driven by a comparatively small number of businesses.

One critical aspect to raise here, is that the distribution of fabs predominantly in Asia has become a huge sticking point both in terms of international logistics, but in political motivations and action. Many western governments, notably the US, are concerned that their tech industries - and especially their military - are heavily reliant on foreign agencies in constructing these vital resources. This has had an impact notably in the United States fiscal policies and military strategy. While there has been much bluster from the Trump administration about the need to bring manufacturing jobs back to the US, it was the Biden administration that signed the ‘Chips and Science Act’ in 2022 to make it happen. This bill introduced $280 billion of investment that helped to, among other things, build fabs in the United States. TSMC then jumped on this bandwagon, having initially declared a desire to build a fab site in Arizona in 2020, and then broken ground in 2022 having received financial support from the bill. This new fab kicked into production in 2025, and before the first production line was even assembled, Apple had signed up to become its largest customer. Meanwhile, the US Navy continues to have the Seventh Fleet primed and ready from its operating base in Japan in the event that China could attempt to take the Taiwan Strait. It is recognised by the US government and military that Taiwan is a critical US asset, and there are very real fears that China could starve the western world of chip manufacturing capabilities should they invade and assimilate the country. This is still to this day an issue that influences their actions within the Pacific theatre.

The WHY: TLDR

The important thing to takeaway from this segment is that:

• Fabrication of the components needed for DDRAM and HBM is incredibly expensive and time-consuming.

• The lead times on this are staggering, with weeks taken to manufacture the silicon, complete chips can take months at a time.

• The number of available fabs in the world is frighteningly small for the amount of chips being manufactured.

How Did This Happen?

So bringing it all together, what do we have?

• A consumer market that requires specific types of memory for electronic products, especially in PC and gaming.

• An AI industry whose memory requirements consumes consumer-grade memory resources during manufacturing.

• Large-scale industry investment in AI datacentres, thus increasing demand for HBM memory.

• A fabrication market that has significant supply chain bottlenecks given how few companies can actually built the memory needed.

And all of this then brings us to the all important fact: AI companies pay a premium for the HBM memory.

This creates a dynamic where it is more financially lucrative for the fabrication companies to divert their resources towards manufacturing HBM rather than DRAM. Thus creating a situation where consumer grade memory reduces in supply, and therefore manufacturers either charge their existing supply at higher prices for pure profit, or have to absorb costs of competing for limited fab space, which also increases the price.

This has led to a number of DRAM manufacturers, notably Micron, to declare that they’re divesting from the consumer market. They can make significantly more money by building HBM for AI companies than bother with the little people. All in pursuit of profits based around manufacturing of datacentres we still don’t really know if we’ll even need.

Meanwhile there are additional factors that could further increase cost. For one there is the cost of resources, be it precious materials used in chip manufacturing, but also in fuel. There has already been issues with precious metal acquisition that combined with COVID lockdowns heavily affected chip production in the early 2020’s. Meanwhile in the present day the ongoing conflict across the Middle-East is a significant cause for concern in the chip industry. The ongoing air and missile strikes by the United States and Israel on Iran and neighbouring countries leading to the closing of Strait of Hormuz, and the transit of fuel, is only adding to these complexities. While most countries driven heavily by fab-based industries, especially Taiwan, retain stockpiles of key materials, they typically have limited fuel reserves. TSMC accounts for up to 10% of all of Taiwan’s energy consumption, and as an island nation it relies heavily on imported fuel, typically with only a week or twos supply at best. Hence should the Strait of Hormuz continue to remain shut through the summer, things could get even worse as fuel prices raise and scarcity impacts their production lines.

A Manufactured Failure

With the facts laid out as they are, the one thing to really take away from this is how this was entirely foreseeable by the people that caused it. As we mentioned already chip fabrication has a long lead time, and companies engage with the fabs early to ensure supply chain will not be disrupted as they seek to execute on new projects. Hence many of the companies involved knew that their heavy investment in HBM would starve the consumer market as far back as late 2024.

Meanwhile companies are only going to starve the remaining market until the HBM boom dies down. Most recently news came of Apple seeking to swallow up as much of the mobile DRAM market - even potentially at a loss - so as to avoid letting competitors impact their market share. By comparison, the likes of Qualcomm are slashing production budgets for specific chips, while Samsung are increasing prices for devices (even in South Korea).

In Part 2…

So with part one in the bag where we explain how we get here, we’ll dig a little more into the future of the situation in a later issue. In part 2 we will discuss:

• What efforts are being made to mitigate this, if any?

• How soon could this turnaround, if at all?

• The status of the AI data centre rollouts.

• What about the building of new fabs in the US?

• New research in AI developments that could upend the situation.

Wrapping Up

Wooft, well… that was upbeat! But hopefully you have slightly clearer idea of a lot of the realities behind why this is all happening. We’ll get back to a slightly more fun and cheery topic next week, I hope, before returning to part 2.

Thanks for reading and catch you all soon.

The AI and Games Newsletter brings concise and informative discussion on artificial intelligence for video games each and every week. Including industry news, innovative research, emerging trends, and our own exclusive editorial and reporting.

Subscribe now

You can subscribe to and support AI and Games, with weekly editions appearing in your inbox. If you’d like to work with us on your own games projects, please check out our consulting services. To sponsor, please visit the dedicated sponsorship page.

Hello one and all, and welcome back to this week’s edition of . For this week’s edition I’m picking up a thread from a recent interview over on ’s on the need for AI governance and strategy. This is something I spend a lot of time discussing with studios in our consulting work, and figured I should share some of that here in the newsletter.

But first, some headlines, and the first talks from AI and Games Conference 2025 hitting YouTube!

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AI and Games Conference 2025 on YouTube

After many hours of editing, colour correction and approvals, I’m pleased to announce that for the next couple of months we will be slowly releasing the the recordings from last years AI and Games Conference.

As always we’re committed to making information as accessible as possible for those interested in the Game AI space. Hence we’re releasing these videos for free on the conference YouTube channel. With special thanks to Xsolla who join us as our presenting partner for the video releases!

To kick things off we have two talks that delivered on some really interesting subject matter.

Debugging Across Time and Platforms: The Power of Determinism
Richard Kogelnig / Havok

First up we welcome Richard Kogelnig from our 2025 sponsor Havok who digs into the complexities of debugging AI behaviours across different gaming platforms. The challenges faced in dealing with an issue that isn’t guaranteed to be reproduced the same way on Xbox as it is PlayStation. And how Havok have developed a fool-proof philosophy to meet these challenges in cross-platform determinism.

One Trillion Parameters and No Plans
Jeff Orkin / Bitpart AI

Our second release for this week is one that feels very relevant to the current climate. In an age of Large Language Models being proposed as the solution to many a Game AI problem, is there still a need for traditional planning systems? Jeff Orkin, the creator of the GOAP planner using in 2005’s F.E.A.R., argues not just yes, but maybe more now than ever. This talk digs into the work that Orkin’s team at Bitpart.ai are doing that explores how LLMs can add real value in traditional planning domains, and the that can opportunities from hybrid solutions. Turn up for the insights, and then stick around for the great real-time demo which turns into a meta-joke about all things AI and Games. It was a pretty surreal moment to be there when it happened.

AI (and Games) in the News

Let’s take a quick run through of the headlines before we dig into our story of the week.

• Paper’s Please Creator Wary of AI Plagiarism (VGC):
  Beloved indie developer, creator of Papers Please and Return of the Obra Dinn mentioned in an interview on Mike Rose and Rami Ismail’s ‘Mike & Rami Are Still Here’ podcast that he’s reticent about discussing his future projects because of AI. While he loves talking about the stuff he’s doing, he has a - rather justified - concern that if we posts about it online, then some grifter will attempt to clone it with Generative AI tools.
  
  I mean, not only did I raise this as an issue specifically with the UK’s (now cancelled) copyright plans, but also we talked about how this exact thing happened just two weeks ago. I get it. It sucks.
  

• Lenovo’s New Gaming Headheld DoA Thanks to RAM Prices (Kotaku):
  The Legion Go 2 released in 2025 with a hefty price tag of up to $1300. Now thanks to, you guessed it, Generative AI hype, the base model is now $1500, and the top-end device (which as double the RAM) has increased $700 to a whopping $2000. Just in case you needed a reminder that video games are becoming a luxury hobby.
  

• Black & White - 25 Years Later (Eurogamer): Lewis Gordon published a piece on Eurogamer last week celebrating 25 years of Lionhead’s beloved god sim Black & White. It’s a decent overview, with comments from various members of the development team. Plus it has some insight into how the AI works in the game, but having researched it myself I feel it works too hard to draw parallels between what the game did, and the AI of today. Yes DeepMind co-founder Demis Hassabis worked on the game, and yes DeepMind made StarCraft bots using the same methodologies, but there’s a big difference between the two.
  
  And yes, I have finished researching Black & White. I hope to have a case study on it sometime this summer. Stay tuned!
  

• How Upcoming RPG Bellwright Simulates NPCs at Scale (80.lvl):

  Sticking with the Game AI theme - oh how nice it is to briefly write about something other than Generative AI hype - developers Donkey Crew were interviewed by 80LV to discuss how they have thousands of NPCs active in the game. A fun chat and worth checking out. It has a lot of parallels with games like Kingdom Come Deliverance 2, which I’m also working on for a case study later this year!
  

• Phantom Blade Zero Devs Reject DLSS5 (Kotaku):
  Short and sweet, but after S-Game Studio’s upcoming title Phantom Blade Zero was listed as one of the upcoming games that support DLSS5 - which as you’ll recall had a reveal that went down like a lead balloon - wrote a lengthy post over on Twitter/X/Whatever to communicate how they’re not using “AI visual tech that could alter our artists’ original creative intent”.
  
  When studios are having to defend their projects because they were planning to use the arguably useful features of DLSS, it only further highlights how badly Nvidia has messed up.
  

• Sony Doubles-Down on AI Rendering with Cinemersive (80.lvl):
  A small story beat that most didn’t pick up on. Sony Interactive Entertainment acquired UK AI company Cinemersive Labs: a company that specialises in volumetric 3D imaging. Meaning it takes 2D images and turns them into 3D volumes. Sort of a mishmash of existing efforts in photogrammetry but applying it to creating interactive real-time renders using machine learning. While Cinemersive’s work has been predominantly in VR, it does align with Sony’s increasing interests in using AI for rendering, as seen with the PSSR technology on PS5 Pro.
  

While Most AI Tools are Hot Garbage, Studios Need Solid Governance and Strategy

Last week I saw some headlines off the back of ’s interview with Jon Gibson, the head of transformation at Keywords Studios. When the conversation surrounding AI tools came up, Gibson had this to say:

“AI feels like it’s in the chaos phase right now. And we need to move to the usable phase. How do we use AI in live production environments? How do we use AI in a way where it complements teams rather than potentially threatens teams? And also how do we use it in a context where it’s governed, it’s controlled, it’s IP safe, it’s legally safe, it’s ethically and morally safe? The gulf between cool AI demos where you put in a prompt and you get something amazing, to actually AI in production where you get consistent, high-quality results steered and directed by humans, is quite a big leap.”

You can hear the full comment over on the The Game Business, but for me it was refreshing - and not too unsurprising - to hear this coming from Keywords. After all they’ve done a lot of work in exploring the efficacy of AI tools. I have previously written up on the work they have done on the likes of Project AVA in 2024, an effort to build an entire visual novel game using AI tools. Plus in Project Kara in 2025 which took the same idea but instead sought to remaster an existing 3D game they had already built.

As reported in Gibson’s interview, the company has “tested about 500 different AI tools”, with only about half a dozen ready to be used in production right now. This came up during the original Project AVA report by Stephen Peacock and Lionel Wood in that many of the tools they found were poorly built, lacked enterprise costing structures and licenses, had operational security concerns, or had “laughable” legal terms associated with them. Never mind the actual efficacy of the tools in practice, which as was discussed in both projects were mixed at best.

While this was the main headline for a few news outlets, it wasn’t the main takeaway for me. I have been paying close attention to what Keywords have been up to for a while now, and it makes sense that as a co-development studio they want to show they’re aware of the current state of these technologies - be they positive or negative. However, I wanted to talk about what was for me a more crucial point. When Dring brought up on the current sentiment surrounding AI adoption as has been reported in the likes of the GDC State of the Industry reports, Gibson said, emphasis mine:

“I think not having controls and governance around AI is part of that issue… A lot of companies are not really explaining to their people why they’re using AI, and why it’s a good thing, and what the strategy is. They’re going into using AI models without that clarity. And it concerns developers.”

Governance is Crucial for Studios on AI Use

This was interesting because I don’t hear a lot of people talking meaningfully about building AI governance publicly. On how to ensure there is clear guidance within an organisation on what is considered use of AI tools and technologies, what impact it can have on the development pipelines, and also understanding from stakeholders across an organisation as to what value - if any - it presents.

It’s referred to as an “uncomfortable truth” in the title of the article, in that there’s too much focus on the power and capabilities of what AI can do, rather than meaningful discussion of how and if it should be adopted. And I would agree with that, it’s a topic raised frequently in talks I present at games industry conferences: studios need to take this seriously, and not simply ignore it. This means we need to consider:

1. What tools are considered acceptable in a games studio?

2. Who is allowed to utilise these tools and in what business capacities?

3. How does this extend to vendors, contractors, and other third parties?

4. Ensuring policy reflects the values of the organisation.

5. Recognising the sentiment among stakeholders across the organisation - from management right down to juniors - on how AI is impacting the business and what lessons are to be taken away from that.

6. Appropriate communication within the studio and beyond on what the policy is and how it influences decision making.

Now this isn’t an easy process, and I can speak to it given it is something that we help studios address. We run training and consult with studios on putting this governance in place - more on that later. But there’s a real net benefit in having this in place. It helps developers understand what the studio’s stance is on AI, on what is acceptable usage, and helps give clarity to both the use of these tools, but also to whether a developer’s work and livelihood runs risk of being affected by it. In an age where image generators are being sold left and right, it’s important that art teams feel like they can continue to do their best work without risk of their role being automated.

As Gibson states in the article, the culture that emerges off the back of good governance is one that encourages learning. While there’s no guarantee that someone is going to use AI, it’s useful for them to feel they’re in a space where they can ask questions.

In fact one of my regular activities I do when running a consultancy - where I’m in the studio for a couple of days - is I bake in a couple of hours where I’m at a desk (be it in the office or online), working on my thing, but anyone from across the company is welcome to DM me, jump on a call, or sit with me to ask questions. We get into every topic you imagine, because regardless of people’s enthusiasm for AI they’re curious about it - how it works, its efficacy, whether a tool exists for a specific problem, or even could we theorise how to use AI in specific scenarios. Ultimately people are curious whether AI can be used in responsible ways to deliver value.

These conversations are kept in confidence, but I do summarise the themes of what I hear to leadership. This works on two levels: it helps me educate and empower the individual, while also gathering an idea of the sentiment that is potentially affecting morale such that more effective governance and policy can be constructed.

Even If You Don’t Use AI, Leadership Must Take Charge

Now it’s worth stressing that even if you studio has no intention to use AI at all, policy and governance should still be in place. It’s important that teams feel that the leadership understand the state of this technology, what it does, and also how its evolving.

I often ask the audience in my industry talks as to whether their studio as even a basic policy in place for AI usage, and many still fail to put up their hand. Regardless of the intent, every game studio needs to have AI policies in place. Leadership needs to be able to show they have a grasp of the situation, of how their position reflects the current status quo, and but more importantly, and give clarity to their teams as to what that stance is.

But more critically, a non-AI policy once it is put in place is enforceable. If it’s in writing and clearly communicated, then this becomes a foundational component of what is considered good practice. You don’t wind up with a situation arising because someone has secretly been using AI tools as part of their role, and then it causes a headache because there’s no clear indication of whether this was acceptable, and how it will be acted upon when discovered.

Unsurprisingly, to me at least, a lot of the work on governance we do comes from indie studios who have zero interest in using tools.

Shameless Plug: Work With Us on AI Governance

So yeah, as I’ve expressed more than once, this is something we cover in our client work with games studios. I hadn’t planned on turning the end of this issue into a commercial for our work with games studios, but it’s clearly a talking point right now and worth raising more publicly.

We host a variety of training sessions on these issues. Not just on a technical level, but also the likes of ethical issues, legal considerations, and broader challenges studios faced in constructing and reinforcing AI policy. We also run dedicated consultancy on AI policy adoption, working with all corners of the industry to ensure guidance is in place.

If you’re interested, simply click the image above or the button below, fill in the form and we’ll get back to you!

AI and Games Training Modules

Wrapping Up

That’s it for this week, thank you for sticking with us to the end. Next week we’ll begin the reader-voted piece on the RAM crisis and a deeper dive into how this all came together. Plus we’ll have more conference talks, and all the other jazz you’ve come to love from this here publication.

In the meantime, my one more thing for this week is our quicklook livestream from last week for indie game Aether & Iron by Seismic Squirrel. A ‘decopunk narrative RPG’ that also has a turn-based car combat system. It’s came out to very positive reviews on Steam and is sort of the antithesis of a lot of the Generative AI hype, with fully hand-drawn art and over 200 human-voiced characters. I had accepted the press key for the game given I was interested in the car combat aspect, but If you’re a fan of games like Disco Elysium and Dispatch this is definitely going to be up your alley.

• When a story breaks and every games outlet misreports on it.

• Tommy has a right good rant about poor AI reporting, again.

• An update on the conference, Goal State, and upcoming case studies.

• Plus a brand new project coming your way later this year.

The AI and Games Newsletter brings concise and informative discussion on artificial intelligence for video games each and every week. Including industry news, innovative research, emerging trends, and our own exclusive editorial and reporting.

Subscribe now

You can subscribe to and support AI and Games, with weekly editions appearing in your inbox. If you’d like to work with us on your own games projects, please check out our consulting services. To sponsor, please visit the dedicated sponsorship page.

Hello one and all and welcome to this week’s edition of . Hope you had a (un)healthy amount of easter eggs for those of you who celebrate the chocolate bunny gods. This week we have big behind-the-scenes update for premium subscribers. But before that, I have a bone to pick with a news headline.

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Announcements

Final Reminder: CoG Industry Day Submissions Close April 10th

Last chance for submissions for talks and demos to the industry track of the IEEE Conference on Games 2026 in Madrid with deadline this Friday on April 10th.

Visit the website for more info.

The One News Story That Annoyed Me This Week

Sadly news come down last week that a central AI team at Take-Two Interactive was being let go. An undisclosed number of individuals who worked under the head of AI Luke Dicken are out of a job as he reported on LinkedIn. Dicken had been in a leadership position on the subject for seven years, first at Zynga and then Take-Two.

This is a sad outcome for sure, and I wish the team the very best in finding new positions. Now full disclosure I’ve known Dicken for close to 20 years (good grief, has it been that long?) and have met staff that reported to him in recent years at GDC. I am not pointing this out to make more of a story of how this group of people lost their job versus everybody else, or to go to bat for these people disproportionately.

Rather, I raise it because I’m annoyed at how badly this story has been reported on.

Everyone from Kotaku, to Eurogamer, GamesIndustry.biz, Engadget, TweakTown, PCGamer, Rock Paper Shotgun, and TheGamer all reported on this story, and all built a narrative around it that doesn’t reflect reality.

It doesn’t help that most of this stems outlets simply reporting off the back of the articles by Kotaku (see Eurogamer, GI.biz and Engadget) and PCGamer (I mean the RPS and TheGamer articles are just copies of it), but also that it is then presented with zero context. Given this is not a particularly big event on its own in context of the industry (sad as it may be), every publication then pivots to making unrelated points on AI in the games industry to make it sound like it’s part of a bigger developing narrative. More often than not falling back onto former comments on AI by Take Two. Such as President Karl Slatoff’s recent musings on Google’s Genie 3 to CEO Strauss Zelnick’s opinions on Generative AI that range from intrigued to ambivalent.

All of this helps add substance to an argument in these stories that suggests the turning of the tide against an aggressive pursuit of Generative AI at Take Two, or the industry as a whole. That two months ago Zelnick suddenly changed his mind about AI and so a team that had been sprung up to do Generative AI ‘stuff’ is now fired. When in truth the reality is probably much more benign: budgets being cut as the need for a central AI team is no longer needed? The team was no longer necessary in an age where generative AI fills the gaps? They didn’t fit the generative skillset needed for a broader push by the publisher?

Now I’m not saying any of this is the actual story. I just suspect the truth is far less sensational than has been reported. Plus I don’t have any inside baseball as to what happened here. I did reach out to Luke to express my sympathies but I didn’t do so in pursuit of an inside scoop for the newsletter (also I had no plan to write this story). For me that’s both unprofessional and frankly icky. I have no interest in exploiting my personal and professional network in pursuit of clicks. Besides I doubt Luke can even comment on at this time given whatever severance package will no doubt have some non-disclosures involved.

All that said, I got annoyed at this for two reasons:

1. Any effort to do a surface-level analysis of the situation can tell the headlines don’t match up.

2. This feeds into uninformed anti-AI sentiment that causes people who actually work in the AI corner of games more harm than good.

First up, this team isn’t some Generative AI start-up, they were a central AI team previously at Zynga and then folded into Take-Two when they were acquired. The bulk of their work is not Generative AI based. They’re a team that’s been focussed on procedural content generation tooling and machine learning. Supporting deployment of ML in broader DevOps in aspects of automation and tooling for developers. What they’ve been doing in Generative AI is relatively minimal and also more recent, given they’ve been a team that’s been focussed on supporting game projects.

All of this is pointed out in Dicken’s LinkedIn post, but most news outlets conveniently forgot to mention it, given it contradicts their narratives.

Now the reason this annoys me is that it feeds back into a lack of nuanced conversation about what’s happening on AI in the sector. Misreporting like this, or at least tying it into narratives that are unsubstantiated is an evergreen issue of the games industry. It’s how you get narratives ranging from the benign to the damaging to manifest.

On one hand it’s all fun and games that people still seem to think that Nintendo are going to drop a fully-fledged 3D Mario game this year - despite zero evidence to support the theory other than a new movie is out. But then you have this same approach used for targeted hate campaigns that masquerade as advocates of the industry under dog-whistle politics around issues of ‘ethics in game journalism’ and ‘DEI in games’. I can’t help but fear being an ‘AI programmer’ at a games studio is going to be the next angle for gamers ire.

I mean just look at the comments section of most of those news stories, or even this random Reddit thread, where but a handful of people are actually speaking sense. Everyone is feeding off of the anti-Generative AI sentiment. And while I understand it, and to an extent am all for it, this team is being roasted for no other reason than they work in a sector that has been demonised by the very nonsense they didn’t embrace.

Heck, the one bit of inside baseball I’d suggest is if you’ve ever followed Luke on social media, you’d know full well how dismissive he is of much of the Generative AI hype. The man does not mince his words…

I’m sorry I have a lot of respect for the publications involved and many of the writers, but it would help if you actually reported on the story as it stands rather than misreport on these events to make them more than they are - a point I raised just recently in the final part of the Game AI Existential Crisis essay. I’ve complained about this before be it with the Microsoft Muse project, with Google Genie, the Google Cloud AI survey, and many more besides. The willingness to be anti-AI on everything is frankly a little too easy, and efforts should be made to better understand where all of these things actually sit within the sector.

My apologies to Luke and his team for making this the focus of the issue. I wish the team all the best and hope you find new positions soon. Be sure to check out Dicken’s LinkedIn for info on the folks who lost their roles if you’re in a position to help.

Behind-the-Scenes Updates

Okay here we go. There’s a lot of stuff happening for us right now in the background, be it the 2026 conference, new case studies, Goal State, newsletter issues and more. So let’s dig into where we are with all of these and what to expect as a regular reader and fan of our work. It’s important to me that our audience can get a bit of an insight into what we’re doing, plus how we’re investing the funds we raise from our premium subscriptions. For this edition we’ll cover:

• The case studies we’ll be presenting over the next 2-3 months.

• What we have planned for newsletter topics.

• A new AI and Games project coming your way in the next few months.

Read more

• Game AI’s Existential Crisis is Now on YouTube

• Japanese Indie Dev Gets Ripped Off Thanks to Gen AI

• Warhorse Studios Replace Translators with AI Tools?

• Tommy’s Take on the DLSS5 Debacle

The AI and Games Newsletter brings concise and informative discussion on artificial intelligence for video games each and every week. Including industry news, innovative research, emerging trends, and our own exclusive editorial and reporting.

Subscribe now

You can subscribe to and support AI and Games, with weekly editions appearing in your inbox. If you'd like to work with us on your own games projects, please check out our consulting services. To sponsor, please visit the dedicated sponsorship page.

Hello everyone, welcome to this week’s edition of AI and Games. I’ve been busy these past two weeks reporting on the AI situation from GDC, as well as completing the Game AI Existential Crisis essay, so I figured let’s do a shorter edition this week catching up on the news, and then spend a few minutes giving my own take on the long-lasting damage that will stem from that god-awful DLSS5 reveal.

Don’t worry, no April’s fools around here. We’re all about consistency around here.

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Announcements

Couple of quick things to get in you

Reminder: CoG Industry Day Submissions Close April 10th

As mentioned last week, the submissions for talks and demos to the industry track of the IEEE Conference on Games 2026 in Madrid close April 10th.

Visit the website for more info.

New on YouTube

Having just finished writing the series in the newsletter, I figured it was time I started translating it across to our video channels. Part 1 of Game AI’s Existential Crisis is now live on YouTube as video essay. It’s a shorter and slightly re-written version of the original shared in the newsletter, but still comes in at a whopping 50 minutes in length.

AI (and Games) in the News

A quick round-up of a bunch of news stories that have cropped up in the past two weeks.

Remember When We Trained AI to Play Games? Well LLM’s Suck At It [IEEE Spectrum]

I wanted to give a shout-out to my academic friends as Georgios Yannakakis and Julian Togelius whose recently published paper on LLMs trying - and failing - to play video games successfully is an interesting regression in AI research versus some of the work happening in games-based artificial general intelligence (AGI) around 10 years ago. Perhaps an issue of the researchers digest on this paper? Let me know if you fancy it.

Sony AI Develops AI Models That Protect Copyright? [Automaton]

The long and short here is Sony AI have tried to develop a generative model that can create AI-generated outputs that respects copyrighted material. Protective AI (PA) as they call it is essentially an AI model that is still trained on the copyrighted material, but it has it baked into the training process that it needs to avoid generating outputs that look like it. While still in development, it suggests the solution to having stopping AI creators sticking artists work into their model so it can reproduce it, is to stick the artists work into the model so it does not reproduce it.

This reads like a sensible idea from a research perspective, but I doubt it will have much traction in the real world.

Unity Shuts Down IronSource To Pursue AI-Powered User Acquisition [GamesIndustry.biz]

Remember back in 2023 when Unity merged with the ad network IronSource? No? Well nobody liked it. Everyone was unhappy about it at the time given it lumped the Unity game engine with a the rather annoying and predatory practices of a mobile-ads company. So good news, they’re shutting the whole thing down later this month.

Why? Well as Jon Hicks reports over on GI.biz, the real real revenue growth is coming not from ads but AI-driven user acquisition. This is achieved courtesy of the ‘Vector’ platform that Unity launched back in 2025.

Japanese Indie Dev Has Work Ripped Off Thanks to Generative AI [Automata]

So here’s something I’ve been warning about for years: if developers are continually sharing their work online as they develop their projects, what’s to stop some shitty individual from taking your work and cloning it using generative AI?

Well this was proven right for me last month after Japanese indie developer and YouTuber Kamaboko had been caught out after their work on their game ‘Typing Magician’ was cloned and reproduced by another user. Having shared their work on the Unityroom site, another user then posted their own version of the same game achieved using AI tooling.

I mean the person who did even shared how they did on YouTube. One for all of you out there that have some experience in Japanese!

Kingdom Come Deliverance 2 Language Editor Replaced by AI? [PCGamer]

Warhorse Studios Kingdom Come Deliverance 2 is a beast of an RPG, and it requires a lot of effort to get all of the dialogue written up and translated into various languages. So it’s rather disheartening to see this post emerge on r/kingdomcome on reddit in which Max Hejtmánek, who was previously hired to as a Czech to English translator for the game was fired last week since the studio felt using AI for translation would “make the company more effective”.

Sadly translation is one of the areas most heavily hit by AI in many business and creative sectors, even though it’s nowhere near as good in practice as a human expert. You would think a games studio that focusses heavily on delivering a high quality RPG experience would know that?

Crimson Desert Team Convinces Nobody in Saying AI Art Was Placeholder [IGN]

That TikTok game you’ve never heard of until two weeks ago Crimson Desert has came under fire for being full of AI-generated art assets despite having no AI disclosure on Steam at the time of launch. Since then developers Pearl Abyss came out with a waffling and unconvincing statement that suggested these were placeholders from early AI experimentation, convincing absolutely nobody. Oh and the Steam disclosure was adapted, thanks guys!

Brief Op/Ed: Nvidia Completely Misses the Mark with DLSS5

It’s been over two weeks now since the unveiling of DLSS5 at Nvidia’s GTC event, and naturally I’ve been busy writing other things, but also I had refrained from getting involved into I’d heard and seen more of what’s going on here.

If you’ve somehow missed all this furore since it was announced - first of all lucky you - Nvidia announced the latest version of their AI-upscaling technology DLSS was showcased at their GTC event in San Jose and it has been widely condemned - and rightfully so - for fundamentally failing to grasp what value this technology has within the games industry. The new version has introduced a new lighting rendering pass, plus the controversial neural face renderer - that we reported on when it was announced in January of 2025 - that received a lot of criticism when it was first announced given it was prone to beautifying faces akin to an Instagram filter (i.e. yassified), as well lightening darker skin tones.

As you can see from the video above, the attempts to use both aspects of this updated tech look awful in that video. The faces aren’t consistent, the lighting is washed out, the faces look waxy and overly lit, and of course it also fundamentally changes how the game looks versus how it was intended. It has rightfully been trolled on social media, with the video above sitting at over 2.3 million views, with only ~16% likes compared to more than 100k dislikes. Not to mention the comment section eviscerating this idea. But hey, Nvidia’s stock only dropped a mere 0.3% on announcement, so that must mean it’s good right?

I have a sneaking suspicion someone’s been drinking their own Kool-Aid.

The Unspoken Agreement on DLSS

DLSS has since its inception been focussed on increasing the overall rendering quality of a game, and this is where DLSS5 not only drops the ball but highlights Nvidia’s arrogance over the issue. DLSS 1 and 2 were focussed on trying to increase resolution of rendered games by taking in lower-quality versions of the rendered frame and then outputting a higher quality version. So in essence, you feed in a 720p image to get a 1080p one, or a 1080p frame for a 2160p render. Ultimately you get the graphics card to do the rendering work, then the AI upscaler works to increase the size and pixel density of the image. This was then enhanced in DLSS3 with frame generation, meaning it would also attempt to figure out intermediate frames akin to how video rendering works. I actually made a video about this in collaboration with Nvidia when it was announced back in 2022.

Since then DLSS has worked to continue to optimise the overall quality of the underlying technology. In fact in the past year or so we’ve seen two iterations of DLSS4 hit the market which includes optimisations to overall image quality, reducing the requirements of the underlying in-engine render, plus an increase to the number of intermediate frames that the Frame Generation technology can provide.

Now all of this stems from a fundamental alignment between the industry and the provider. The games industry continues to push increased graphical fidelity as means to showcase the biggest and best games, but to render at higher resolutions with equally high framerates is computationally expensive, and often beyond the capacity of many end-users GPUs. Hence DLSS was a workaround: allow players to experience the game by instead using an AI supported upscaling process rather than through native rendering. This is particularly useful when running the likes of raytracing for dynamic lighting which significantly increases the workload of the renderer.

And for the most part, the games industry has signed into this unspoken agreement, that AI upscaling was an acceptable workaround for ever increasing hardware costs necessary for big-budget high-fidelity games.

Now while I have problems with the games industry’s obsession with graphics rendering, even I see some of the benefits of using the likes of DLSS in games. It helps enable players with lower power devices to engage with the latest games. It helps titles get ported to the Switch 2 which has an Nvidia GPU. In fact I wrote about this at the time of the Switch 2 launch heralding how important it was both for the future of AI tech used in rendering, but also that it was of sufficient quality that it would be used now as the sole primary means for certain games to be deployed on Nintendo hardware.

But I also have issue with how the industry is beginning to rely on it even more now as means to achieve base performance. The debacle surrounding Borderlands 4’s launch last year - where virtually every base setting required DLSS to be enabled, speaks to an over-reliance on the technology as means to work around the necessary optimisations for a game at launch. Sure, a balance must be struck here, and yes some players hate DLSS - referring to it as ‘fake frames’ - but games like Borderlands 4 are a shining example of going too far in the wrong direction.

Fundamental Misalignment Between Product and Consumer

DLSS5 has broken that unspoken agreement, and it has put Nvidia in an awkward position as they attempt to sell a technology that nobody wants. Never mind that Jensen Huang says players “are completely wrong” about the technology (they’re not). Never mind that they won’t admit to what the tech does (it’s a post-render AI pass). Never mind that it’s currently not even feasible to run it on a single GPU. The most important thing here is that Nvidia has overstepped. Nvidia assumed that they knew better than developers what AI rendering should be doing to support the experience, and they have been burned by it.

It’s a considerable shot in the foot what with DLSS4.5 coming and going without much grief. An overstep as Nvidia now showcases technology that seeks to replace the original artistic intent of a game, running under the assumption that those games simply couldn’t achieve their original vision without Nvidia’s help. Now I know a few people who tried out the demos behind closed doors at GTC, and while some of them felt that the lighting features in DLSS5 could be useful if actually controlled by environment artists, they were universal in saying the faces were awful. Yassification aside, there are significant problems with the eyes being prone to not lining up, or even looking in the same direction. Plus an awkward jitter in the facial movements, and the lighting on the faces often making them look waxy and dirty, or to a point they sometimes have different lighting versus the rest of the scene.

But again we’re still in a space where the big issue is the game is being re-rendered to something that arguably does not fit the original artistic vision. The Grace Ashcroft example in Resident Evil: Requiem is an ever bigger problem when you realise that she’s based on a real person. Grace’s face is based on that of Polish/American model Julia Pratt. While there is naturally going to be some artistic license applied, the face will still be expected to behave in a manner much like Pratt’s given they will use her for expression capture. The whole point of this process is to have a consistent baseline of physical appearance you can build Grace from. It’s not going to help if you then have an AI render sit atop it that won’t guarantee that consistency lest you can actually train the face renderer. But even then, in the game she’s not meant to look like Pratt, but Grace. So even in the best case example it’s a lot of effort that still results in the same problem of a lack of consistency.

Consistency is paramount for these sorts of things. Not just in the game itself, but all of the marketing building off of that. Both Leon and Grace need to be clearly identifiable and consistent so you can run billboards and all sorts of digital advertising such that people begin to recognise them. Marketing 101 here.

Plus, there’s an interesting line here in whether the likeness rights in the contract between Pratt’s agency and Capcom would extend as far as Nvidia fucking around with the face after the fact without either party’s permission?

To add insult to injury, Capcom stepped up to be one of the studios who acknowledged they didn’t know about the DLSS reveal until it happened. Now I do want to slap some cold water on this, given I highly doubt big companies are completely in the dark about Nvidia using their games without permission. Though I suspect they didn’t expect all of this to happen with their games front and centre. They figured Requiem was going to be used to showcase a DLSS demo, not that they would wind up in the centre of a war between AI bros and gamers.

Players Suddenly Realise DLSS is Generative AI (and are not happy)

So I mused about this in part 3 of the Existential Crisis, but it amuses me how Nvidia have dodged many a bullet in recent years surrounding the ‘AI slop’ problem in that DLSS came to be before the term 'Generative AI’ was normalised. The acronym - Deep Learning Super Sampling - highlighted the use of super-resolution convolutional neural networks for interpretation and reconstruction of images. It is essentially using the precursor to modern Generative AI techniques.

Now considering DLSS has, since version 4, used transformer networks - which are the standard for Generative AI - it is without a doubt a Generative AI technology, and has been since inception. But it felt like it snuck under the radar of consumer ire for the most part until this DLSS5 debacle, because it highlights all the problems and issues consumers have with AI slop.

And boy did they pick the wrong franchise to throw under the bus in the process. Resident Evil at this point is an institution. It has gone through highs and lows for sure, but one could argue it’s never been more popular than now, and this 30 year old franchise has unwittingly victim that ‘the gamers’ will rally behind.

I mean sure, none of this is going to impact Nvidia’s bottom line right now, but to me this is a pretty fundamental misstep that the gaming audiences will remember. The point where Nvidia truly showed their colours as an AI company that will flog their slop-building tech to the detriment of the artistry of games. I mean, this has been true for at least a year or so now, but at this point people might be thinking more about how AMD’s GPUs are a more viable alternative in their next PC build - especially given those are the GPUs being used in current and next generation consoles by Xbox and PlayStation.

And on that note, my open thought is what impact this will have on everyone else? Be it AMD’s FSR4, to PlayStation’s PSSR - both of which are often described as ‘Machine Learning-based upscaling’. Isn’t it interesting that they avoid referring to it as Generative AI? Even though that’s exactly what both of them are, for fear of consumer backlash?

Either way, this is not going to help in the long run with growing apathy and downturn in gaming spend at this time. If it’s becoming all the more obvious that the hobby they have enjoyed as it stands is going to be messed with as means to promote slop engines.

This will all blow over in the coming weeks, but it won’t be forgotten. I genuinely think this is will prove to be an inflection point that we will return to in the coming years.

Wrapping Up

Short and sweet this week - I mean it’s about 1/4 of last week’s edition so yeah, I figured we should keep this one tight.

Next week, we should start having 2025’s conference talks online, plus a few other details for our premium subscribers! So I’ll see you then.

The AI and Games Newsletter brings concise and informative discussion on artificial intelligence for video games each and every week. Plus summarising all of our content released across various channels, like our YouTube videos and in-person events like the AI and Games Conference.

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Hello one and all and welcome to this (slightly delayed) edition of . I wanted to spend this week wrapping up the Game AI Existential Crisis series I started writing last year. Admittedly this was tough to commit to given so much has happened in the past week news-wise, but we’ll come back and summarise all of that next week.

Announcement: Participate in the Industry Day at IEEE CoG 2026

A quick announcement before we get into the meat of things. The IEEE Conference on Games - the largest academic conference dedicated to research in games - is hosting a dedicated industry day as part of a four-day event running from September 1st to 4th at Universidad Complutense de Madrid in Spain. You may recall I wrote about attending in 2025 as a keynote speaker. This year I have joined the organisational committee as industry chair.

Naturally for my academic friends this will be something they’re already aware of, given it is a highlight of the event calendar. But I wanted to raise this for our folks out in the games industry who fancy taking part. As we’ll have a day full of keynotes, presentations, plus a demo exhibition.

We currently have an open call for talks, demos, and sponsorship for the event. Full details can be found at the site. Participants do not need to submit a research paper like their academic colleagues. Just a short abstract and takeaways is all that is required. Whether you’re indie or AAA, if you have some interesting work you’d like to present to a captive audience, this is a great opportunity.

Also, let me stress, this is not a solely AI-focussed event. So you don’t need to be working on AI for games to submit.

Deadline is on April 10th. Feel free to get in touch if you have any questions!

Follow AI and Games on: BlueSky | YouTube | LinkedIn | TikTok

Game AI’s Existential Crisis Part III: On Building Community

At the end of October last year I wrote the first part of my essay on Game AI’s existential crisis. A longform breakdown of the challenges facing in Game AI: the discipline of artificial intelligence used for gameplay in the current video game industry.

Please note: this series is focussed exclusively on Game AI, and I am not discussing broader AI applications in production be it machine learning or generative AI.

I believe that Game AI as a field has three distinct challenges it needs to address as a community in the coming years.

In part one I gave a broader introduction to the subject matter for those new to game AI, and discussed the first challenge in that Game AI is struggling on a technical and design level in the current climate. In particular discussing the ever-increasing demands of contemporary game design and development, and how generative AI is often incorrectly hailed as the solution to our problems.

Then in part two just before the winter break, I expanded on this thesis to discuss the challenges faced in education and access to knowledge. How so many of our institutions have been lost over the years, how our knowledge is fractured, and the realisation that my work AI and Games is now the longest-running venue for information on AI in the games industry, and Game AI in practice. While this is something I am very proud of, I am equally horrified that this has come to pass.

For this third part I want to talk about community. There is a community of developers who have been in and around the space of Game AI for some time now. Some of you might be just joining us by finding my work online (welcome), while others have been in this space for decades. It is important that we continue to find ways to connect with one another, and foster that community as priorities shift in various aspects within the industry.

So for this edition, I want to focus on the following:

• The importance of building, retaining, and supporting our community.

• Recognising the generational shift that is happening in the games industry today.

• Understanding how an increasingly toxic environment makes our work harder.

• How we need to navigate and work around changes in industry priority and geopolitical lines.

In addition, I will be ending this piece with a discussion of where we go next. How do we address these challenges. Now I have already been making suggestions throughout these articles, but I want to make sure they’re consolidated and summarised such that we can foster further discussion and turn that into action.

The ‘AI and Games’ Community

One of the biggest challenges I have faced in the decade-plus I have spent creating content under the banner, was not just understanding who is the audience I have cultivated, but what is the community that I seek to serve?

As I discussed back in part two, this whole thing started with me making YouTube videos as a hobby. I was trying to find a way to connect the material I covered in class as a university lecturer with the realities of how games actually ship. I figured why not build an archive of resources I can point to as extra-curricular viewing/reading that could help, and from the beginning I made them public because why not? Let anyone else who is interested check them out and get some value from them.

Over time it’s then lead to pretty much what is now my day job:

• I write this here weekly newsletter to try and help give guidance and perspective on the current AI conversations.

• I work to produce case studies - essentially an excuse to keep making YouTube videos - while also building up my own online courses with Goal State.

• I provide professional training and consultancy to everyone from indie, AA, and AAA studios, to big tech companies, trade representatives, government agencies, universities, and much more besides. Whether that’s in consulting on active games to bringing people up to speed in current and emerging trends in AI for games that they should be aware of.

• I manage the non-profit that runs the AI and Games Conference.

While I started out on the outside looking in, I’m now very much in the middle of much of what happens in AI for game development. I don’t just work with games companies and can influence product, but I have built a platform that I try to use to bring value - and dare I say it we are actually making an impact in the sector slowly, but steadily. But it has also built a community. We have thousands of people in our Discord server (though it’s the same 50 people chatting most of the time - hey guys!), hundreds of developers attend our conference, thousands of people watching our videos, and I’m grateful that when most game devs and researchers come over to say hi at an event that we have a positive interaction.

AI and Games as a brand (ugh) has become one of the means through which we bring the Game AI community together. But this only really occurred because I’ve spent a long time thinking about the message that AI and Games is trying to say - or rather what I am trying to say - and then try to communicate that in a way that people align with it.

In many respects the message hasn’t changed, but in others, it’s had to deliver a lot more nuance. If you were to ask me when I started AI and Games on YouTube back in 2014 what values or themes represent it, it would probably be something like this:

• Game AI is a vital, specialised, and often misunderstood field of game development.

• AI research highlights the potential to change how we make games, as well as how games influence the state of the art AI.

• Both of these are poorly misunderstood fields, and AI and Games will work to communicate them more broadly.

For a time this was more than sufficient - especially given I was just making YouTube videos to an audience of maybe a couple of hundred people. Plus at that time AI in game development was very much a niche, and had not yet come to consume most of the discourse surrounding the games industry. Not to mention that we already had established communities. However the situation in 2026 is a very different one, AI is everywhere, many of those older communities dissolved, and as such I’ve had to really think about what are the values that drive my work:

• Education First: Everything we do should have a net benefit to people currently working, or aspiring to enter the space of AI for video games, be it from a scholarly/academic perspective, or to work in the industry itself. We share knowledge on good practice, we report on emerging trends, and give context to current events, and work to get the messages out to the people that want (or need) to hear them.

• Maintaining Integrity: AI should not be adopted in the games industry for the sake of it, and we must be critical of whether new developments are truly innovative, and address whether they may prove to be unethical and/or exploitative in practice. Our criticisms are constructive, and driven from evidence rather than emotion. This is how we foster and maintain trust.

• Accessibility and Inclusion: Every article/video/talk/event presented by is someone’s first. We must ensure people feel welcome, that information is accessible, and that we provide means to drive their own curiosities. We welcome new members of our community regardless of their background and experience in the field and work to promote new voices where we can.

• Protect and Archive Knowledge: As the mists of time form, we run risk of organisations collapsing, which in turn results in knowledge being lost. AI and Games will work to support archiving the history of AI for games.

Now this all reads with a little bit of corporate ‘bleh’ to it, and I personally find it a little groan inducing, but it’s important to have this in place because we’re a business. Dare I say it, this is a little bit more grown-up than when it first started! These values drive the decisions being made at my company and whether a business decision makes us feel comfortable with it. But it also highlights how community is the lynchpin of it all. Everything should service the community, and I have to figure out how to balance between doing what I think everyone will benefit from, and at the end of the day I need to make sure me and my team are being paid and able to enjoy life. Because sadly as much as we love doing this, good vibes does not put food on the table or a roof over our heads. So yeah, it has to remain sustainable for us.

So hey, as a reminder: your support is a huge boost in helping us to continue to do what we do! And we’re close to executing our next stage of plans for what we want to do in the future.

These values also address a more subtle issue. As I discussed in Part 2, a lot of the audience we now have are students and AI professionals working in games-related fields. When the YouTube was launched we had no real community, and our audience was effectively anyone interested in the subject. In more recent years I’d argue my focus has been on cultivating a community of people invested or interested in AI for games, while still seeking to provide material accessible to anyone.

Now you may think I overinflate our importance here - and contrary to what you may think I am not one for blowing my own trumpet - but I see first-hand the impact we’ve had. I’ve met developers who watch our videos, or read our newsletter, and thank us for it. Heck I’ve met developers whose work we have turned into videos and they tell me of the excitement among their teams as they sat and watched the video together. I’ve met developers who tell me they use some of our YouTube episodes as a onboarding material for new AI programmers. I meet developers who tell me they started watching as a student and it drove them to work in Game AI - be it in the industry, or as a researcher. Hell we’ve had not just attendees, but speakers, at our conference tell me how excited they are to be there because of what the brand represents to them.

That means the fucking world to me, but it also acts as a constant reminder of the need to uphold ourselves to these standards as we continue to try and figure out how pay for all of this, and navigate a world of AI in game development that has become significantly more complex.

Plus of course we are but one community that exists. Off the top of my head I can think of:

• The AI Summit crowd at GDC that Steve Rabin, Rez Graham and others have done a great job of keeping together this year what with the pivot towards the ‘Festival of Gaming’.

• The Game AI Uncovered crew that Paul Roberts has cultivated thanks to his book series.

• The Artificial Intelligence and Games Summer School by Julian Togelius and Georgios Yannakakis, plus David Melhart and Antonios Liapis.

• Plus the academic spaces like the AIIDE, FDG, and IEEE CoG conferences.

I’d be the first to admit all of the above are more expert spaces for professionals to congregate. However by comparison, is the largest, and loudest, of all of them. So for me, it’s all about how do we use our voice to and momentum to build bridges between these spaces, and drive more people to them when appropriate.

All of this is to say that I spend a lot of time thinking about the issues of not just fostering community that I want, but also how do we reinforce and support the Game AI community more broadly as issues come our way.

Weathering the Storms

Now more than ever it’s important that we bring this community together, ensure that we don’t just have an opportunity to exchange knowledge and ideas, but can build our own momentum and message to weather the many storms that we face as a sub-discipline in a highly volatile sector.

I’ve stated before that games, and the broader creative sector is currently being besieged by the AI industry. While there are a lot of new ideas, teams, and tech emerging that are interesting, and exploring how to use generative AI responsibly, I’ll be frank in saying the bulk of what I see is ill-conceived, stupidly expensive, and poorly-built junk. The signal-to-noise ratio when it comes to talking about artificial intelligence in the games industry is really messed up right now.

This has made the reality of being someone in the Game AI space that much harder, given as we discussed in part 1, most AI programmers in the games industry often work very little in machine learning, much less generative AI.

As I posited, there are several storms we are weathering at once right now, and we need to be mindful how we approach them both individually and collectively:

• The generational shift that’s happening in the games industry as old talent phases out, and new talent struggles to get in.

• An already toxic audience base whose lack of knowledge of game development is already a tremendous burden, is now amplified by the state of AI discourse.

• The changes in priority as publications and venues focus on their own interests.

• How political and linguistic lines draw divides between us, and the efforts we need to take to mitigate that.

A Generational Shift

One of the most critical and impactful issues the games industry as a whole is both creating, and trying to address right now is several generational shifts in talent. This is evident in a number of ways:

• People who have been in the industry a long time are retiring.

• People are being forced out the sector by layoffs and deciding not to come back.

  • Let’s not forget that between 2022 and 2025, just shy of 50,000 lost their jobs in the sector.

• People coming into the industry as juniors are struggling to find jobs.

  • This is due to a mixture of a larger market of available talent due to layoffs, AI tools absorbing traditional junior tasks, university graduates lacking the sufficient skills for entry roles, and fewer available positions in the sector.

• On average, people are staying in the industry for longer than before.

  • The average age of game developers has increased towards 40 years old over the past 10 years. While this is great given it addresses a known issue of talent burning out and leaving in their 30’s and 40’s, it’s compounding the existing problems for juniors.

So there’s a lot of different threads here to pick at, but the narrative I want to gleam from all of this is about the transference of knowledge and experience. Starting at the top end, the people phasing out of the industry in their 50’s worked in this sector during the real boom of the video games industry. A 21 year old junior working on a SNES or Mega Drive game in 1992 is 54 years old today. I’ve met and worked with developers who joined the sector in their late teens/early twenties sometime in the early 90s and there’s a generation of knowledge there that’s important to retain.

Now yes you run risk of chatting with them only to have old men yell at clouds, that’s an occupational hazard - plus I shouldn’t throw stones, I’m in my early 40s. But there’s a lot of expertise and experience that has been cultivated that should naturally filter down. Sure, we don’t make games like we did 30 years ago, but those little bits of genius in there that helped ship a feature are still useful to us in 2026. I speak with indie devs who tell me about the case studies/videos I’ve made on games from 20 years ago are very informative and practical for them, given they use them as means to build their own systems. Their skills and the resources available to them are often equivalent to a AA or AAA studio of 20 years ago. Take last year’s example of chatting with the team behind Trepang2 who created their very own homage to F.E.A.R. with a team of only four people.

There is always a desire even from other experts to hear about how they did it back in the day. The amount of enthusiasm and hype we had at the 2025 conference for Ian Shaw’s Dungeon Keeper post-mortem was so heart-warming. Developers who shipped games in the 2000’s cramming into the auditorium because that’s the game they were playing in college, or even at lunch breaks!

I was in high school, and Dungeon Keeper 2 was very much my jam.

Won’t Somebody Think of the Children?!?!

Now on the flip side, we also have new talent coming into the sector. We need new talent to continue to come in with new perspectives, new skills, and new ideas. We don’t just need to ensure these new developers can find likeminded individuals, but they get the mentorship and support of those that have been in this space for most of their career. As clinical as it may sound, we have to look at this whole process more abstractly as a conveyor belt on a production line. As talent leaves production, we need to be bringing in new faces to replace them, and all that experience needs to trickle back down the line. Plus we need to be looking at it not just within individual studios, but more broadly at regional, national, and international levels.

This of course sits alongside issues where juniors are struggling for entry level roles, and in an age where studios are either repeatedly in hiring freezes, replacing juniors with AI tooling, or forcing the juniors to work predominantly with AI tooling to get more out of them faster. Naturally the issues with the first two cases are highly evident: we’re not bringing new talent into the sector, and as the average age of developers continues to increase, we will create a talent crisis that will manifest in the next 10 years. But the latter issue is also a huge problem.

As any experienced developer knows, you gain so much experience from shadowing your leads. Be it working on features, having them review your code, or just sitting and chatting with them for weeks on end. The first 5-10 years of my career I spent surrounded by very smart engineers and college professors who knew their subject areas well, and the best of them know to take those juniors under their wing and mould them into future leads. I was incredibly fortunate to work with some fantastic people through grad school and then in my early career that shaped so many of the decisions and skills that drive my work today, and we need to work to enable that.

This is already a challenge for a number of reasons, but office dynamics and remote working aside, the games industry needs to consider the implications of AI-tooling entering our spaces. Given these are subsuming the roles of traditional juniors, it not only runs risk of increasing the talent gap as we don’t have new developers coming in to replace seniors as they progress, but it also means those juniors are not getting the appropriate mentorship they need and effectively exist in a lower class of professional as their expertise and career development are considered secondary to the broader need to ‘get shit done’. This is a process that media and cultural studies professors have been observing in games for some time now as we rely on an increasing range of automation courtesy of everything from procedural generation tools, to photogrammetry and ‘metahuman’ workflows. There is a risk not just that we don’t hire new talent, but that they are not giving the care and attention the deserve to thrive in the future.

I have even heard from some corners of the industry that they “don’t hire juniors”. It takes too much time and energy to do it. So it’s somebody else’s problem. They can hire them once they get a few years under their belt. But if everyone is going in the same direction, there won’t be any juniors to hire after they’ve got that initial experience. Classic short-termism.

Every time we look to promote people into senior and leadership positions, we should equally be looking at how we’re going to ensure they can eventually be replaced. As I say I feel this is an issue that is universal to all disciplines within the games industry, but given my previous points on education in Game AI back in part 2, this it feels like this is an ever bigger concern for our necks of the woods.

An Angry and Often Toxic Audience

It’s safe to say in 2026 that the term ‘Artificial Intelligence’ carries a very negative weight to it. What was once rather vague and potentially mysterious, that existed in most minds in the realm of science fiction, has since become something people are increasingly consciously aware of, and - in many instances - outright despise.

After all in 2025 the term ‘Slop’ was word of the year for both the Merriam-Webster (American English) and Macquarie (Australian English) dictionaries. Meanwhile both the Cambridge Dictionary updated to acknowledge the use of the term to refer to:

Content on the internet that is of very low quality, especially when it is created by artificial intelligence.

Meanwhile the Wikipedia article on AI slop has exploded since the first version of it was published in October of 2024 as the use of generative AI for creative outputs such as writing, images, and video has infected everything from social media to advertising, film and television production, music, books, and of course video games.

Now of course Game AI has nothing to do with this - for the most part. We’re making NPCs, combat management systems and all that jazz. 99% of Game AI uses zero machine learning whatsoever, never mind Generative AI. But it’s not like Game AI was a well understood subject matter to begin with, and now that Generative AI has become conflated to mean all of AI, it’s making what was already a difficult conversation with players all that much worse.

“Fuck AI”

Now there’s a phrase I see a lot in my day-to-day.

Running a company with numerous social media strands called in 2026 means a lot of curation of our replies. While I’m not on social media all that often - given I generally loathe it - I feel it’s important as a ‘voice’ to get out there and try to challenge narratives out there, and depending on where you post, and what you’re posting about, you get a lot of ire. On average I either hide, delete, or report 10-20 comments a week on our YouTube videos from people who write very nasty messages that more often than not have very little to do with the subject matter - even more when we release any video that isn’t about classic Game AI.

I mean fortunately I’ve been publishing content on YouTube for a decade; I’ve built very thick skin. Not to mention I’m from Glasgow; some random keyboard warrior thinking they’re a wee hardman in my comment section doesn’t bother me. But it speaks to a shift that’s occurred in any and all discourse related to AI in game development. And let’s face it, the games-playing masses know very little about how games are made. It’s been an issue that the industry has created for itself only to bite them in the ass - a point I wrote up as a video a long time ago. So I do clean up our comment section in the videos a lot because I want it to show some actual meaningful discourse. Constructive criticisms are totally fine, but when we it’s just “fuck AI” or attacks on me or our guests than I draw the line.

Heck the new trend on the YouTube channel is having people tell me I should change the name of the channel so as to get more views, because ‘calling NPC stuff AI isn’t going to help your reach’, and while they might have a point, it’s not something I’m going to act upon, because making concessions like this is detrimental as a whole.

Now yes, all of this is having an impact on the YouTube side of things. Our viewing numbers have plateaued the past 2 years, and subscriber growth has reduced drastically (percentage growth year-on-year is higher in the newsletter than the YouTube channel). But I don’t believe in making drastic change to suit these trends. I’d rather stand by my own principles and continue to do what we do because I know in the broader industry we’re respected for this output.

So while I’m not terribly worried about the YouTube side of things - I mean it’s never been a sustainable channel to run as a full-time job even when it was popular - I do worry about the broader implications the things we’re seeing are having elsewhere. After all, people are quick to conflate that any discussion about AI in game development is now Generative AI. Or that features implemented in games that exhibit traits of intelligence and procedural construction are now Generative AI.

It’s bad enough that - per my comments in part I - that quite often we’re now being told to re-invent Game AI wheels using Generative AI when we really don’t need to, but now you have a player base primed to assume any meaningful development in Game AI is now tarred with the slop brush. What if a new AAA game comes along and starts crafting really cool and intelligent NPCs? Are we going to have people breathing down our neck assuming we used GPT to do it? Hang on, the goalkeepers in EA Sports FC 26 use machine learning? Does that mean gamedevs are being lazy now?

Plus, as I stated in a previous entry I still think there is value in trying to figure out how to use small-scale, finely-tuned ML models to help address very specific Game AI problems, and some of those ML models could very well be generative in nature. But heaven forbid we ever disclose that publicly if you don’t want people jumping into your social media feeds or Steam reviews. Episodes we’ve made this past year such as MLMove and Snowcap, where I’m looking at what I think are interesting attempts to utilise ML and Generative AI in game development, have had all sorts of bile in the comments that I had to clean them up quite a bit - plus we got shit for it in our social media posts. Now clearly the people shouting below the line are not actually watching or reading the work, given if they did, they’d know none of the issues people have with Generative AI as a whole are evident in these projects - and credit to the folks in our audience who actually responded to some of these comments and called them out on this, thank you all.

But it doesn’t matter. The kneejerk reaction is just to shout online.

If anything it reinforces to me that as a sector we need to continue to be vocal. To push back against the narrative set by the Generative AI Industry that has set about commercialising the very technology people broadly despise. I wrote a op/ed piece on this for GamesIndustry.biz which was released the very same week that DLSS5 blew up in Nvidia’s face, only helping to prove my point. The signal-to-noise ratio in discussing AI in game development is overwhelming skewed towards the noise. We made to have more signal out there to combat it.

It seems like the language needed to engage with players is going to be a major concern if we’re going to try and keep communicating the efforts taken here. I’ve noticed somewhat anecdotally that ‘Machine Learning’ is now often being used to describe any ML-based approach, including Generative AI, that isn’t considered icky. This cropped up a lot in recent weeks what with the DLSS5 debacle, where I see people talking about how old DLSS is just an example of Machine Learning being useful for different parts of games, including upscaling. Meanwhile DLSS5 is now just Generative AI slop - despite the fact that any and all forms of DLSS - and AI upscaling as a whole - are Generative AI by virtue of their function.

I have wondered in the past year how much Nvidia dodged a bullet in their branding and messaging in that they commercialised DLSS long before Generative AI became mainstream. It seems like only now are people catching on to what that tech really does.

But of course this is just the conversation between the developer and the player, which has never been all that fun anyway, and in many larger studios isn’t an issue for us day-today. But this same thing is happening right across the games industry.

“I Work in AI, But Not Like That”

How many of you who work in game AI and adjacent fields have had to defend your job title in recent years? Now that’s not even an issue of engaging with the general public or our players, this is an issue happening within the industry itself. The term ‘AI’ has become so loaded within the industry as the ongoing anxiety surrounding Generative AI’s push into the industry means we’re having to re-affirm to our colleagues in the sector what it is we actually do.

All of this reinforces the need for us to fight our corner, and continue to educate people on what this stuff really does. Sure, we won’t change everyone’s minds - especially those in trapped in social media bubbles - but much like our efforts in education it’s important to hold our ground and continue to talk about the work that’s happening in this corner of the sector so that those wanting to learn more find that material out there to consume.

Changes in Priority

So thus far in this edition we’ve got the challenges of bringing in and retaining our talent, and then trying to defend against the anxiety within the industry as to our work as well as the general noise coming from social media. But we still have our own little corners within the sector within which to engage and collaborate? Sure, we have meetups, Discord servers, mailing lists (that’s still a thing right?), plus of course book publications, and events. But these last two are for me a larger concern, given we’re seeing the trends surrounding AI that are also affecting the likes of education potentially impact these avenues for dissemination and networking.

As I discussed in part two, the shifting trends in what is considered in vogue in the world of AI means we have to keep fighting to justify what Game AI is and why it deserves its own space. It’s a challenge we face in our editorial for the AI and Games Conference because while we recognise that machine learning is a useful tool in production, and there are 101 people wanting to get on stage to talk about Generative AI, we still need and want to curate a space for the Game AI community that most of our founding team built their careers in.

Now we’re something of an outlier: we’re a small organisation built by people who work in this space, who know this space, and want to serve the community. The rest of the sector doesn’t really think about Game AI in the same way we do, because most of them have never worked in it!

So what happens when they decide to follow the AI hype? What impact does this have on those community spaces? I mean they are few and far between as it is, and all of this is very much a veiled description of GDC’s 2026 “Festival of Gaming”. An event that emerged courtesy of a panic in declining numbers and marketing spend across 2024 and 2025, combined with the impending termination of the (highly beneficial) deal that Informa has with running the event at the Moscone centre in San Francisco.

While my point extends far beyond GDC, this past year is a shining example of what happens when the bigger players who manage community spaces have a change of heart…

How the ‘Festival of Gaming’ Came to Be

Contrary to the narrative bouncing around the internet that states GDC dropped 10,000 attendees in a year, it actually dropped around 5,000 each of the last two consecutive years. You may note that in 2025 they stated they had “nearly 30,000 registered attendees” versus the 30,000 attendees the year before. The subtle messaging in 2025 was to obscure the fact that a lot of speakers, exhibitors, and regular attendees cancelled in the closing months courtesy of the changes happening at border control at the US. When I enquired about this particular choice of words at the GDC AI Summit post-mortem in the summer of 2025, it was explained to me the number was much closer to 25,000.

Now I raise this not to try and soften the blow GDC has had this year in the attendance data - frankly they should have been more honest about it because there was no way it was going to go up this year. Rather, I highlight it because it gives context as to why the whole “Festival of Gaming” pivot even happened. They brought in consultants in early 2025 to examine the data they had from the event, ranging from ticket purchases to consumer spend and overall footfall, and the thing that was made clear was that people value the GDC Summits; the first two days of the week where people converged on topics focussed on specific disciplines.

The data highlighted that a not-so-insignificant proportion of attendees bought the ‘Summit pass’, which entitled you to access the two days of summit talks, the expo floor and some of the other talks and roundtables that happen throughout the ‘core’ conference from Wednesday to Friday. The summit pass was also significantly cheaper than the ‘Core’ pass - around $1,950 for Core versus £1300 for Summits - and this meant three key pieces of data:

• Attendees were paying for the ‘cheaper’ pass that delivers value.

• A larger proportion of attendees attended the Summit talks versus Core conference talks.

• Attendance would trail off towards the end of the week because a lot of people only really attended for the Summits and would leave before the end of the event.

So what this tells me, is that the Summits were delivering value for the audience in a way that Core does not - and I’ll be honest outside of the AI roundtables and some of the main stage talks I seldom attended the main conference given there were too many sponsored sessions and stuff that just didn’t interest me. It also highlights to me what the value of the Summits are to attendees:

• Programmes curated by subject experts for subject experts.

• A place for likeminded individuals to attend, connect, and network.

So it’s clear the Summits are of value to attendees, and to GDC given people are spending money on the passes to attend. So perhaps there’s a way to utilise this in a way that works for Informa? Get people to attend for the summits, but keep them around throughout the week? Maybe even reschedule the event so that the summits are a week-long affair with different ones running on different days? Run the summits in the back half of the week rather than the start?

What was the conclusion they reached? Remove the Summits.

The Death of GDC’s Community Spaces is a Warning

While this segment is about the broader impact of AI trends influencing our decisions making, I refer to the GDC situation over the past two years given it is emblematic of this very problem. As AI hype continues to trend, GDC has sought to capitalise on it. Often with a larger number of sponsored talks on the subject that - based on my time attending a handful across 2023 and 2024 - are certainly not the value for money Informa thinks they are.

Meanwhile back when the Summits still suited them, they tried to force more and more Generative AI into the AI Summit in 2023 and 2024, including a Roblox talk in 2023 that at the time none of us really wanted but the organisers pushed to be added. Plus in 2024 there was a Google talk advertised as an AI Summit talk when it wasn’t part of our programme - in fact it was double booked with another AI Summit talk, and in a different room from where our community got together.

Plus, there was GDC’s mini ‘AI Summit’ as part of ‘The AI Summit New York’ (an event ran by GDC’s owners Informa) in 2024, where they were reaching out to previous speakers to present, only for me to get emails from said speakers asking if this was legit? Or if we had any information because it was poorly communicated. I then had to ask GDC what was going on, because the messaging was confusing. Admittedly, they’re free to do that if they want, but for the community surrounding the summit when they see ‘the AI Summit’, they think the advisory board will be involved. So being left in the dark, even if there was no intention to have us involved, struck me as rather disrespectful.

On top of all this, in 2024 I spent two weeks in a daily email correspondence with some of the GDC organisers who simply assumed the AI Summit was a perfect place for all of the Generative AI content to go. After all, if this summit was about AI, then surely it made sense to start pushing for Generative AI content to just go in there? This lead to a lengthy correspondence in which I had to explain to GDC what the AI Summit is actually about, to try and prevent them burning it all down.

Admittedly the name of the summit was out of date, given when it was founded some 15 years ago, ‘AI’ for games simply meant Game AI - NPCs, gameplay systems, and virtually none of it used Machine Learning. Now of course we had a Machine Learning summit that muddied those waters a little, in that while both the AI and ML summits had clear agendas and goals, the purpose to anyone outside of the field might prove confusing based solely on their names.

So yeah, if you wondered why in 2024 GDC suddenly renamed it to the ‘Game AI Summit’, that was my doing. I convinced them to do that to reinforce the need to our community we still had a dedicated space at this event despite the ever-increasing hype surrounding AI in the industry.

In fact I even offered to help them kickstart a Generative AI Summit in 2025 if need be, just to ensure we preserve the Game AI Summit for what it was. Only for them to remove the summits from the format a year later.

I have since spoken to a bunch of people who attended GDC 2026 and while disappointed about the Summits not existing, they could still get by given they knew other community members were in attendance. But me, I’m still angry about it.

These Summits made sense as dedicated community spaces. Whether you were a seasoned veteran of the field, or someone new to the space, for two days of GDC you knew where your peers were. Where likeminded individuals would attend. That’s a great place for people to network, to meet respected voices in the field, and foster a sense of community. That’s a responsibility that the advisory board took very seriously. We curated the talks, we mentored the speakers, we ensured they received an introduction and applause as they took the stage, we helped them with tech issues, and moderated their QnA. All to make sure that when someone gets up and presents in that hall that it’s a celebration of them and their work.

The Game AI Summit was the longest-serving community space that this field had, and for all its problems, I know how important it was to a lot of people for them to get up there and present to that audience.

Sure, there was still a Game AI presence at GDC this year, but like every other community who lost their summit, the fundamental lack of a dedicated space for a fixed period of time was detrimental for those communities. Over the past six months I have spoken with people involved in many of the other summits at GDC, and none of them are happy about the decisions being made - and in some cases led to them deciding not to attend this year.

Now there’s a chance that Informa changes their mind after they saw another decline in attendance numbers this year and bring the Summits back. But the issue here is two fold:

1. It highlights how all too quickly an institution that has come to hold some sway or impact in our field can be brought down despite our best efforts.

2. All of this is not just a reflection on how priorities can change and impact the communities that we cultivate, but not necessarily control, but also how broader political factors can also prove detrimental.

The Political and Linguistic Lines

GDC in the past two years is a great example of socio-economic and geo-political factors impact the game development community. After all attending GDC is an expensive proposition, and frankly it has only increased in cost the past couple of years as flights, accommodation and other expenses continue to increase. But also people are concerned about entering the United States as a result of its border control and immigration policies. All of this culminating in a situation that attendance is down by a third in the space of two years.

But this is not an issue that is unique to GDC, nor is it even the first time that this criticism has been held aloft against the event. GDC has for as long as I can remember had a negative reputation given the significant cost to attend, and the US not being an easy country for people to enter if they don’t arrive from very specific corners of the world.

Of course I’m Scottish - so technically British (ugh) - and that opens doors for me in ways that others simply lack (and I am highly aware of it), but then our own border control has proven problematic in recent years.

“The British? Problematic as a result of socio-economic and geo-political policy?” I hear you say. I know, what a surprise…

We’ve dealt with this first-hand with Brexit impacting travel for people to enter the UK for the AI and Games Conference. We provide support where we can, notably in letters of support for visa entry for speakers and partner delegates. But we have people who want to attend our event in London and can’t given they won’t be granted the visa they need to enter the country for even a couple of days - and as event organisers we cannot support for attendees given there’s no legal basis on which we could argue why we should vouch for them (especially if we don’t know them).

All of this reinforces the need for us to branch out and try and run events in other spaces. To try and find ways to bring ourselves together. By providing more options it at least helps foster community at smaller levels and then we can work to build the bridges internationally.

I mean full disclosure we’ve been blown away by the level of enthusiasm for our conference. We hoped in 2024 to maybe get 100-150 people together, and by end of 2025 we had recorded attendance of just shy of 400. Our estimates in attendance data for 2025 suggest that we’re seeing increasing numbers of attendees from Europe and North America. So now we have the two (great) problems of ensuring we have a space big enough, but also try to ensure we don’t grow to a point where we become part of the problem! I look forward to somebody complaining about me in the same way that I have moaned about GDC for much of this piece.

I am curious how things will play out for events in Europe this year. Whether it be Develop, Devcom/Gamescom, and even our own AI and Games Conference. The sentiment is clear that people are avoiding GDC and US-related events. Does this translate into increased attendance at events over here? I wouldn’t be surprised if most major UK and EU events record increased attendance this year.

I do feel there is a space for more Game AI events, and having opportunities for our community to converge a couple of times a year would be great. They can exist in various sizes, cater to specific disciplines, and don’t need to be huge developer conferences to have value. Just having something helps support pockets of our community in the long run is always great - like all the regional indie game dev events I have attended over the years. As I mentioned at the top, I try to use AI and Games to filter people into other relevant communities. I am big on building bridges versus burning them. It’s why I go speaking at industry events all over the world, because we need to be bringing ourselves together more readily.

Don’t Forget Linguistic/Cultural Barriers Too

Plus it’s worth mentioning as I begin to bring this to a close, that there are also the linguistic barriers as well. We’re still exist in a world where game development practices, cultures, and success stories are seldom shared beyond the global east/west divide.

We still exist in an age where there is a lot of mystery about how games made in China, South Korea, and Japan. Yes part of this is the aforementioned political aspects, but there are also linguistic and cultural barriers. It’s not common for ‘western’ studios to present at say a Japanese game developer event or vice versa. In all the years I’ve been involved in disseminating knowledge about Game AI, it’s incredibly rare to find studios from Japan share their work with European and American audiences. We’ve never had Capcom come and present at GDC about the AI of Resident Evil or Monster Hunter. The only studio I can think of who does this with any sort of regular cadence in Square Enix, and that’s largely courtesy of Youichiro Miyake being a strong advocate for building bridges and sharing knowledge.

Heck, did you know that back in 2019 that Miyake-san wrote an entire book just about the Game AI in Final Fantasy XV? A complete, 250-page book on the subject? Miyake-san has published several books not just on specific games, but anthologies designed to communicate to the broader Japanese game-playing community on how Game AI works in some of the most beloved games made by the publisher.

I have contemplated more than once to try and crowdfund getting these translated and either re-published in English or turn them into content on our site: I even spoke with Miyake-san about this more than once in recent years and he was up for it. Like, this is a treasure trove of material locked off from us. And I suspect this is just the tip of the iceberg.

I mean first of all, if that’s something you’re interested in, let me know in the Discord or in the comments. Goal State will launch later this year and I’d be up for crowdfunding some more projects, and I would love to find a way to bring this information to the west somehow.

But more importantly, it once again highlights that we need to find ways to build bridges between different corners of the game development community. I mean did you know that a lot of mobile games coming out of China and South Korea almost exclusively use Machine Learning now for Game AI? I mean I do because this is the stuff I spend hours of my day researching (ha, nerd). But what are they learning over there that we could benefit from (and vice versa)? What is it about their games, their development cultures and practices that lead to different philosophies in how they build Game AI? I’d love for us to work to build those connections even further if we could.

No, this doesn’t mean we’re planning to run like AI and Games Conference: Tokyo or something. God that sounds stressful, but also, cool?

Facing the Challenge

So I think, having reached this point, I’ve got most of the big issues to mind off my chest. So I need to start wrapping this up, and I want to focus on my suggestions on how we move forward.

I think there’s a lot we can all do at various levels to address this. Some of them major, others are minor. But the key thing is I believe this is a community endeavour. We all need to take a little bit of responsibility for this, and work together to help support.

Some Suggestions for Action

So what can we do? I have some thoughts on this at varying levels of depth and complexity. But I wanted to list as many as I could think of. Some of these range from the simple to the complicated, and I appreciate some of these are very difficult to achieve. But if I didn’t think they were valuable, I wouldn’t raise them!

I’ve grouped them around roles and functions in the sector to try and give it some direction:

Developers at Games Studios

I appreciate that many of these are a challenge depending on how your studios operate and communication guidelines that are in place. But

• Share Your Work: Write blog posts, submit talks or book chapters, do social media threads, simply work to encourage discourse about the development of the tech you’ve made. Regardless of whether you’re indie or AAA, talk about what you did. What inspired you? What did you play/see/read that drove this implementation?
  

• Share Your Failures: We’re too quick to talk about when things went right. It’s important we continue to discuss when things went wrong. We often learn the best through failure. Did you try something new that didn’t work? What issues in Game AI development have plagued your career?
  

• If Not Your Work, Share Your Experience: We’re often quick to focus solely on the game we shipped, and not the experience that surrounds it. Can you talk about problems you’ve solved in commercial projects without discussing the game itself?
  

• Be Curious of Academic Works: There is a wealth of research in both Game AI and AI for games that is published on an annual basis that isn’t really read outside of that ecosystem. Try and find niches that interest you. Perhaps attend a conference or similar event if you can? Engage with academic researchers who will be more than happy to talk to you about their research - and even explain the papers if they’re impenetrable!
  

• Try and Encourage Academic R&D: Where it makes sense, try and engage with researchers about the work they have done and how it can impact a specific niche or aspect of your work. There are a handful of academics out there who participate on the regular - and I’m essentially a lapsed researcher who consults for games studios.
  

• Sponsor and Support Endeavours: Naturally for many of the folks at the coalface, they’re not in charge of the budgets. But consider how to work to support education providers and initiatives, academic partnerships, event sponsorships etc. There is budget there at larger companies that can be put to good use to benefit everyone.

Academic Researchers and Students

• Get Yourself Out There: We know how important it is to get out there and publish, but if you find there are other avenues you can take, then do so. Attend industry events ranging from the big ones to the little ones wherever your budget can afford. Bridging the divide where can on both sides is always a win for both parties.
  

• Publish Outside Academic Lines: Much like the previous point on sharing your work, academic researchers are far too prone to only writing in academia about their work. Hence outside of that space you’re not known. Write blogs about your research. Talk about the journey. Share social media threads about your papers and what they mean.
  

• Be Aware of What the Industry Problems Are: I don’t mean this as a dig, but far too often academic research has a rather naïve take on what the problems are in day-to-day industry (I’ve been guilty of this in the past). What are the things developers are still struggling with? These can sometimes lead to new avenues for your research.
  

• Consider More Industry Collaboration: Now this is admittedly a lot easier said than done. But anywhere we can find that brings these often disparate corners together can be of value. This doesn’t need to be massive research projects with huge budgets. But having discussions about the validity of research in context of industry work is useful. Though note I say this only in the situations where this makes the most sense. After all, not all research is intended for real-world application - even if shareholders often insist that it is.

Games Press

A quick one for all of my friends out there in the games press. You seem to have forgotten Game AI is a thing.

• Don’t Just Regurgitate the Headlines: Get out there and find people who can give you a comment on these issues. Or in the worst case scour the internet for a spicy take on BlueSky you can share alongside it.
  

• Pay Attention to What We’re Really Doing Here: 99% of the discourse around AI right now in games is not what most AI practitioners in games are actually doing. There continues to be innovation happening out there and you’re often missing out on fun and interesting stories.
  

• Continue to Take An Interest in Game AI: It’s not often you hear a game get plaudits for its NPC AI, but if you do think it’s good, or even if it has issue, be vocal about it and talk about it if and where you can.

Devs/Researchers at Local and Regional Levels:

Not everything needs to happen at global and international level…

• Host and Attend Meet-ups: The latter is easier than the former, that much I can attest. But fostering community is valuable. You can do this at your local college, or as part of an indie space. Simply getting together to discuss what you do and how you do it can be helpful.
  

• Share Your Learning Experience: Write that blog/video/talk about attending GDC or the AI and Games Conference. Summarise book chapters or talks that excited you. Think about how you providing a 10-minute long insight in sharing what you learned can help others.
  

• Communicate and Reach Out: Speak to your peers, and reach out to others in the space to see if they can you in any way they can. I’ve presented virtual talks and recorded introductions for small Game AI-focussed events all over the world. For those with a little bit of clout, remember sometimes you reposting the work of others and sharing a message can be a huge benefit to them.
  

• Better Knowledge at Representation and Governance Level: Far too often I have to correct people in positions of authority all over the world about what Game AI is, and how current trends in AI are a disservice to this corner of the sector. This needs to be reinforced wherever we can and why this isn’t going to change.

Archival and Resources

A little something for everyone to be thinking about. We’re losing knowledge and we should work to archive it as best we can.

• Consider Archive.org: If you don’t fancy maintaining a webpage of old materials, perhaps put it up on Archive.org and share social media posts with the links.

  • One day, when I’ve finally had enough, I am preparing for my endgame where I upload everything I have to Archive.org. All the videos, the scripts, the research notes, all of it. I have TB of data that I plan to just release into the wild one day.
    

• We Need to Think About Collective Ownership: A recurring theme throughout this piece has been that we’re often let down by the institutions that support us. What happens when the next event organiser changes their minds? When the current book publishers give up on us? When the next figurehead of the community disappears after being found to be problematic? We need to be thinking more broadly as a community on how to support our own endeavours, and not just rely on larger organisations and individual efforts.

  • And yes, I am also referring to myself in this. Not only will I not be doing this forever, but also I need to be held to account for what I’m doing in this space.

TL;DR

• Make Some Noise

• Learn From One Another

• This is a Collective Effort

• Take the Initiative

• Stand Up and Be Counted

• Get Out There, Be Nice, Have Fun

What We’re Doing

As I bring this series to a close, I wanted to talk about what we’re doing about all of this. In the same year that this sense of unease fell over me, that the broader questions over how and where Game AI is going really took hold, I also come to recognise that I have some influence over this.

In 2024 I decided it was time to try and fight back, and find some ways to make a positive impact.

• I launched this here weekly newsletter - which now has thousands of readers each week from across the games industry.

• We successfully crowdfunded the first of my online courses under the Goal State brand. I am currently in the middle of writing, recording, and editing the final product, and we’re on track for a release in 2026.

• And lastly, my friends and I formed our non-profit event company Game AI Events CIC, and that’s how the AI and Games Conference was born.

I am publishing this final piece of the essay while I am knee-deep in preparations as we seek to announce the 2026 edition of our conference. It’s a huge amount of work. It’s incredibly stressful to put something like this together. Plus I won’t lie, I am not getting rich of the back of this. I mean I’m doing okay, but like… AI and Games quite often only has six to nine months of runway on a regular basis. So hey, provided the money is coming in, and we can keep the lights on, we will continue to do what we’re doing as best as we can!

So yeah, I will continue to be annoying to ask for your support. Because the things that we do to help archive and communicate Game AI - including the conference - is the things that pay us the least!

But regardless, I am so proud of our team across both AI and Games and Game AI Events CIC and their commitment. I am grateful to everyone we work with in our sponsors and speakers who give their time, energy and resource to help us do this. We have some pretty grand ambitions for the AI and Games Conference, but that’s going to take us a bit more time to achieve it. However if we can pull of what we have envisioned for the next 2-3 years, that would be pretty amazing stuff.

Now more than ever I am 100% committed to trying to make this work: conferences, courses, case studies, newsletters, content, etc. Not just because I believe in it. Not just because I feel we need to address these issues, but also that failure to maintain momentum now will be detrimental for everyone. As I’ve spent the past three articles expressing, I feel the situation for us is pretty dire, and I’d rather not look back and regret not trying to do something about it when I had the chance.

Naturally if you have opinions on what we’re doing I’m welcome to discuss them in the comments, or in the Discord. Tempting fate with that one I know…

Ultimately, in an era where our YouTube numbers are dwindling, it would be all too easy to just give up. I mean I’ve been doing this for more than 11 years now. I’ve done my time. But if anything it highlights to me that the problem is evergreen, it’s just the parameters have changed, and so has our strategy. AI and Games will continue to work to be the voice on Game AI for newcomers and experts that you can trust, and I look forward to working with all of you to keep fighting that fight.

Stay safe, take care, and I’ll be back.

The AI and Games Newsletter brings concise and informative discussion on artificial intelligence for video games each and every week. Including industry news, innovative research, emerging trends, and our own exclusive editorial and reporting.

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Hello and welcome to this week’s edition of . I had planned to write part 3 of the Game AI Existential Crisis this week, but figured I should comment on everything happened at GDC.

Oh and before we get started, I wrote this issue prior to Nvidia’s announcements at GTC on Monday, including the horrendous DLSS5 demo. I’ll save that rant for another time.

Announcement: My GI.biz Op/Ed

Before we kick things off, a quick announcement that I was invited to write an op/ed for GamesIndustry.biz as part of their ‘AI Week’. Entitled “Biting the Silver Bullet: AI in the Games industry in 2026 and Beyond”, I took the opportunity to summarise a lot of the big talking points I’ve made in this here newsletter over the past year.

You can read it here, or at the image above. If you’re curious what I presented at the Gamescom Dev Leadership Summit last month, imagine this article but as an hour-long talk and you’re not far off it.

A huge thank you to Lewis Packwood for inviting me to submit this piece. I’ve been reading GI.biz for the best part of 20 years, and while I’ve been interviewed for articles on the site in the past, it’s pretty cool to now say I got to write an article for their editorial.

Follow AI and Games on: BlueSky | YouTube | LinkedIn | TikTok

GDC 2026 and the Generative AI Conversation

This year I made the decision to not attend GDC. This decision was the culmination of a number of factors: I have a lot of work going on, the US is increasingly expensive to visit - and not particularly welcoming - plus the changes made to GDC itself suggested that the value I attribute to the event through high quality talks was on the way out. I had opted to use what little time I could spare out of the office this quarter at the Gamescom Dev Leadership Summit, which I wrote about a couple weeks back.

Naturally it’s a shame I didn’t go, after all I have a lot of friends and contacts in North America that are great to reconnect with when over the pond. But perhaps one of the hidden benefits of being at GDC is I don’t hear as much about what is actually happening at GDC. The conversations are much more focussed, and I seldom spend too much time reading up on announcements and big stories until the week after. However this year, was a very different story.

Last week my inbox was inundated by press announcements either from PR wings of big companies, or from agencies trying to secure interviews and coverage by offering me information under embargo. All of them advocating for the latest AI thing these companies are pushing. I think I have to give you all the credit here as the good folks reading this newsletter and spreading the word. It seems we’re now a big enough outlet that it now warrants trying to get our attention when some new AI shiny gets announced.

So yeah, thanks I guess? No seriously thank you all for reading and supporting our work. This is just a natural by-product of building our wee modestly successful publication.

For this week I figured, given I can’t comment on being at GDC this year, why not comment on the narratives surrounding AI at the event. The sentiment I have surmised both from reading all the big announcements, and from folks on the ground sharing their thoughts with me, was that for every step forward, we’ve taken two backwards. A reek of desperation to advocate for generative AI as people are either increasingly over it, or are seeking more meaningful conversation. I’m sorry to say that if you’re looking for meaningful discourse on AI in the games industry, GDC has opted against that in pursuit of the marketing dollar.

A Round-Up of GDC Headlines

Rather than do a topic-by-topic breakdown of everything that was announced - because I value both your and my sanity - here’s a list of stuff that caught my attention to warrant including:

• ComfyUI, which has built a reputation as being a generally well-liked generative AI open-source toolchain, has now got local AI video generation courtesy of RTX acceleration with Nvidia.

• Google Cloud had a lot to say at GDC. In amongst a very flowery presentation on the sunny uplands of AI in the games industry, they also shared some real work on AI-native games and generative AI production workflows.

• Microsoft’s new PC/hybrid console ‘Project Helix’ will support neural rendering (i.e. AI upscaling), (AI-driven) frame generation and texture compression.

• Xbox’s Copilot will launch on consoles later this year. Providing means to automatically record ‘fun’ moments of gameplay (which your Xbox One could do without AI btw), as well as provide guidance and support on the games you’re playing.

• Razer announced a ‘companion’ AI for QA and their own agentic toolchain.

• Arm is collaborating with Nvidia to build stronger integrations between the former’s CPUs and the latters GPUs.

• Arm is also collaborating with UK studio Sumo Digital to help them evaluate their new AI-upscaling technologies.

• Tencent (re)announced MagicDawn - which was already shown at SIGGRAPH Asia last year - which is their own AI-powered game engine technology for supporting things like global illumination (i.e. lighting), spatial audio, and occlussion culling.

• Not so much a headline, but rather the one thing I heard people get ‘excited’ about, was not one but two different websites have cropped up to try and share insight into which generative AI tools studios are actually using to work on games.

Now this is only the stuff that I felt warranted a mention. I think I read around 30+ news stories and press releases on AI from GDC that ranged from ‘hey that’s actually kinda neat’, to ‘hmm, interesting’, followed by ‘oh well that’s a thing’ to just laughing, deleting the email, and moving on. Sadly, there was far more of the latter than there was of the former.

There was of course some positive stuff when you push pass the PR and focus on the talks. I heard good things from the content my colleague Steve Rabin put together under the banner of game AI, plus from all accounts Rez Graham did a good job in taking over the AI roundtables as Neil Kirby stepped down from the position. I’m looking forward to seeing the talk from EA on how they trained machine learning for the goalkeepers in FIF- sorry, EA Sports FC 26. This looks really interesting.

“Did I ever tell you what the definition of insanity is?”

Despite all of that, the real conversation was once again generative AI as a tool in the games industry. Lots of sponsored talks on the subject, lots of booths both in the various halls, and a lot of opinions of varying quality.

Speaking of opinions, a lot of headlines were put together off the back of one panel hosted on the GDC ‘Luminaries’ stage, in which Moritz Baier-Lentz, head of gaming partnerships at Lightspeed Venture Partners, i.e. an investment firm with a lot of fingers in AI cookie jars, stated he was “shocked and sad” about the lack of enthusiasm for generative AI and that the industry had not embraced it as much as he had hoped.

I mean I’m sorry, but are we really meant to take that sentiment seriously? With all due respect to the four gentleman on stage - all of whom have been very successful in their respective careers - but between them they have no experience working as an actual game developer (go look them up on LinkedIn, I’ll wait). So once again, we have online discourse on AI in game development being driven by a headline from a panel with:

• Zero experience of actually developing a game.

• Zero experience that helps give context to the value (if any) of an AI tool in a creative workflow.

• Zero experience in the impact of using AI in a creative workflow.

• Zero desire to engage in the issues surrounding generative AI in games.

GDC’s conversation on AI has sadly not evolved over the past 3 years (despite the best efforts of many a speaker) because it feels like we’re still where we were in 2024:

• Lots of booths showcasing tools and tech that, thus far, has not been proven in production. Ranging from the big players, to start-ups that will die in 18 months.

• The discourse of AI entering the industry continues to be surface level and vague.

• Little to no talks on the impact or value - positive, negative, or otherwise - on generative AI tools in production in the main programme.

  • But by god more and more sponsored talks on AI huh?

• The majority of developers, and players, are cemented in their stance that all of this is a waste of time.

We’re having the same conversations again, and again, and again...

A Lack of Meaningful Insights

Now of course a lot of what I would consider to be a lack of meaningful insight stems from the fact that we’re still only 3 years in to this era of AI-tooling in the games industry. Outside of the predominantly small-scale and indie teams shipping games, or at least trying to, there’s very little data out there that can speak to the efficacy of AI tooling in a traditional game production, because nothing at AAA-scale has really shipped yet where AI tooling was there from day one.

So here we are with another year in which a whole bunch of stuff is thrown at us, all in the hope that somewhere, somehow, all of this will turn into profit? There’s no doubting that AI tooling has its uses in specific use cases, but the conversations in most circles are still tinged with a desire to avoid it, or work around it, because we simply don’t know whether this is worth our time. Fortunately the ‘NPC as GPT’ hype has died down (sorta), we’re now entering the ‘AI for everything’ phase, and it’s just another round of the same empty statements and hollow platitudes.

Now yes, I sound horribly cynical, but let me take a moment to reiterate that there was a lot of good stuff mixed in with the ‘meh’. Stuff that has caught my attention as I think ‘hey, maybe they’re onto something?’. Like the work by Arm and Qualcomm in trying to make AI efficient to deploy on mobile. The Double Helix specs talking about texture compression on consoles which would help reduce install sizes if anyone can afford a new Xbox in 2027. Tencent’s MagicDawn also sounds interesting because it’s trying to solve known issues in lighting and audio - high performance low cost audio occlusion would be huge! These are things that are meaningful to the end-user - be they game developer of player - and that’s what the AI discourse continues to lack.

Instead we’ve got one level of discourse happening at conference stage level showing off the new shiny, while trying not to engage with the lower-level - the developer and player level - of conversation. I saw Baier-Lentz lamented that the ongoing layoffs may have dampened people’s enthusiasm for a technology often being used as their replacement. I wonder if he stopped to chat with anyone outside of the barriers placed in Yerba Buena gardens for their perspective? He might get an earful.

Meanwhile I admittedly lost my cool last week when it became a headline across various outlets that Google DeepMind stated in their GDC talk slot for their AI world model Genie 3 that it’s not a practical tool for use as a video game engine, given it cannot retain model consistency.

I mean, not only has many an AI expert pointed this out, but we dedicated multiple issues of to this topic nearly a year ago.

Despite this, we continue to let this superficial discourse dominate the conversation, rather than treat as what it is: hollow. I did state in my BlueSky post that I don’t want to speak ill of the likes of GamesIndustry.biz and that originally reported on this - these are great outlets, they do great work, I read both of them. However, we’re still in an age where too much reporting on AI lacks appropriate editorial critique. If anything the real story here is that Google admitted something that anyone with a solid background in AI in context of game development already knew.

For all of the noise coming out of GDC. I don’t feel like I missed anything major. Outside of the talks - which are the things I value the most - the rest of the AI discourse just feels exactly the same as it did in 2024 when everyone was doing something behind closed doors but few of the big names wanted to commit. The only difference is now there is a larger evidence of commitment but with little to show for it.

No doubt this will change over time, but it highlights once again that for all of the interesting and valuable work happening in the space, a lot of it will be drowned out by the hype.

Oh Just… One More Thing

A big thank you to everyone who reached out to share with me the update on the Arc Raiders situation.

In a recent interview at GamesIndustry.biz, Embark CEO Patrick Söderlund discussed how they have been working to re-record a lot of the dialogue to no de-emphasise the use of AI voices.

It still doesn’t change my thoughts on what is the biggest issue with their approach, in that the game uses the tech without delivering any real value. For studios keen to replicate Embark’s success, the message is that premium quality voice acting can be replaced with AI models, and the audience will (largely) be okay with it.

Fingers crossed I’m not proven right on that one.

Okay, that’s it for this week. Next week: Game AI’s Existential Crisis - Part 3!

Or do I got on a rant about that DLSS5 thing?

Perils of talking about AI in games, there’s always something new to talk about…

Have a good one folks!

• The House of Lords rejects virtually all of the UK government’s prior plans on AI legislation.

• The 2025 public consultation led to over 11,500 responses. Well done!

• A greater need for tighter regulation, transparency, and sovereign AI development.

The AI and Games Newsletter brings concise and informative discussion on artificial intelligence for video games each and every week. Including industry news, innovative research, emerging trends, and our own exclusive editorial and reporting.

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Hello one and all, and welcome back to . This week I would typically be out in San Francisco for GDC. But frankly I’m so busy I really couldn’t afford losing another week out of the office having just been at the Gamescom Dev Leadership Summit last month. So here I am writing away. For those of you out there at GDC this week, I hope you’re having a great time, and this will no doubt help explain why you haven’t seen me tromping through the Yerba Buena gardens!

But of course for this week’s edition, I didn’t make life easy for myself. I decided to spend a good chunk of my Sunday reading through the recent report from the UK government’s House of Lords on the state of AI in the creative industries. A topic that has loomed in Ol’Blighty for quite some time now.

But dare I say it, it’s far more optimistic than I expected. Read on!

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Unpacking the House of Lords Report on AI and Creative Industries

With the UK’s acting government having been in power close to two years now, there’s been very little positive movement in legislation towards AI. As the government continues to push forward with initiatives that are largely disliked by the general public, we have the latest report on the issue from the House of Lords. This 85-page banger not only calls out the naivety of the current plans of the Labour government, but they largely fall in line with public opinion.

See this is why you subscribe and support us. You need someone willing to spend a lazy Sunday burning through coffee and reading through government reports.

A Quick Recap

As we’ve reported over the past year or so, the government had made a number of suggestions as to have to move forward, many of which aligning with big tech and giving them access to the copyrighted material without oversight. These suggestions then framed a public consultation on the issue that was launched over a year ago, which advocated for providing an opt-out system, whereby major AI players could scrape data by default, and allow for the training of (generative) AI models without consent of IP holders and citizens lest they explicitly stated otherwise.

It took the government almost a year to respond after more than 11,500 responses were sent responding to this issue - by comparison a previous consultation in 2024 on generative AI and data protection laws received less than 250. Published in December of last year, It was reported that 88% of submissions supported mandatory AI licensing, and that having a proper regulation on the protection of copyright and IP, alongside transparency in data, was the way forward. Meanwhile the likes of OpenAI and Anthropic continued to lobby the government and pushed for all of this to be resolved as soon as possible.

Since the consultation closed in February of last year, the government has been working to push forward with its initiatives, albeit with a bit of a reset given the overwhelming consensus on AI licensing, but also a change of minister in charge. Having spent just over a year in office Peter Kyle MP moved from his position as Secretary of State for the Department of Science, Innovation and Technology (DSIT), and moved into a new role as Business Secretary. It was news I welcomed at the time, given Kyle had shown zero effort to actually engage with the creative industries, yet had numerous meetings with virtually every major player in AI. Perhaps unsurprising that his opinions seemed a little skewed towards screwing over IP holders in pursuit of sunny uplands.

However it’s not been all that rosy since. Liz Kendall MP took over the role in September with an intent to focus more on safe regulation in AI, including challenges issues around deepfakes - something that is long overdue. That said, the DSIT has had little to say on where they’re going to go next with AI and copyright. They’ve since said after the overwhelmingly negative response that "they have no preferred option.” Meanwhile, Kendall has had to continue to put out fires due to not only the disastrously conceived and implemented Online Safety Act, plus the government’s embarrassing ‘free AI training’ imitative in January. Including a bunch of generic, rather uninformative and low-value courses, many of which offered by the very big tech companies who are not interested in actually teaching you about the real issues that AI introduces.

AI, Copyright and the Creative Industry (4th Report)

This brings us to last week, where the House of Lords published their 4th report on “AI, Copyright and the Creative Industries”, responding to the current stance that the UK government has on its proposed legislation.

For anyone outside of the UK, our government operates in two houses: the House of Commons, and the House of Lords. The former is responsible for passing legislation and authorising taxes and expenditure, but is held accountable by the latter. The House of Lords conducts investigations and reports on legislation the government wants to enshrine in law. It’s far from a perfect system, but it has its merits sometimes.

In summary, it’s pretty damning. The House of Lords calls out the previously advertised plans of the government as means to “drift towards tacit acceptance of large-scale, unlicensed use of creative content”. With any gains being made from this arrangement being given “to a small number of US-based firms while harms to UK creators grow.”

Yeah, they did not mince their words.

The house has made six suggestions on where the government should go next. Amongst those we find the following:

• Setting out clear guidance on AI and copyright that will remove rights for companies scrape data in an opt-out model.

• Set out protections both for ‘deepfakes’ and digital clones, but also necessary transparency obligations for training AI models.

• Establish a market for licensing UK IP for AI companies should they wish to use it, and work to prioritise development of UK-based AI models.

There’s a lot more to cover here, so I want to start by looking at their thoughts on copyright and training issues in an age of Generative AI.

Read more

In December of 2024, the first Kickstarter campaign for Goal State was 154% funded. Every month I will be providing updates on the ongoing work to complete the project, and deliver the end reward of complete video lecture and tutorial series on the foundations of AI for game development. While the original 30-day campaign has since closed, you can still sign up for late pledges via the Kickstarter page.

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Hello all, and welcome to our first Goal State update of 2026. I had planned this for February, and then I blinked and the first quarter has almost wrapped. Good grief, so let’s fill you in on where we are.

Overall Project Update

Since our last update, we’ve had a bunch of small updates on what’s happening with Goal State:

• We closed late pledges, and hit one more backer goal.

  • Now we’ll be adding the Half-Life deep dive to our public YouTube offerings.

• We’ve been recording the theory part of the course.

  • We should have some of the first videos ready to review next month.

• We’ve shared the current state of all of the completed theory writing.

  • With more chapters dropping this month.

• Plus the tutorial code and assets are approaching half-way to completion.

At this point we have three of us all working not to turn the written work into the final assets, and should be in a position to start showing off the final videos in the next month or so.

Read the Completed Written Content

In our last update I mentioned that we have around 70,000 of the written work complete. As of this week we’re just over 100,000 words, and around 60% of chapters completely written. The state of these unfinished are a mixture of:

1. I want to do more research on relevant industry examples.

2. I just need to tidy them up and finish it.

3. In the case of 3 chapters (of 21), I haven’t started them.

But I wanted to show everyone where we are with this, so earlier this month on the Discord server I shared a link to be able to see and review the current state of all 12 completed chapters. Click here to access the document in the Overleaf editor (which is where I am predominantly writing the course).

There’s some key points to raise here:

• This only includes chapters that are 100% content complete and only require spelling/grammar/accuracy review.

• This version of the document includes 12 completed chapters, and is 208 pages and ~76,000 words long.

  • To give you an idea my progress in writing remaining chapters, the version I am working in as of this morning is 296 pages and ~101,000 words long.

• If you have an Overleaf account and wish to be a reviewer, where you can leave feedback on parts of the material (see Liam’s great work on the left hand side), feel free to get in touch in the Discord and we can add you to the document.

• When a chapter is completed in the main document, I will be transferring it across for you to check out.

The full list of completed chapters at this time are:

• 0-0 Welcome to Game AI 101

• 1-1 Foundations of AI

• 1-2 Computing Fundamentals

• 1-3 The Basics of Search

• 1-4 Tree Search Algorithms

• 1-8 A Brief Introduction to Machine Learning

• 2-1 Introducing Game AI

• 2-5 Finite State Machines

• 3-1 Designing AI for Games

• 3-2 The Value of Mixing Methods

• 3-3 Game AI as Theatre

• 3-4 Smoke & Mirrors

Right now my priority is to complete 2-2: History of AI in Games and 2-3: Pathfinding Algorithms in the coming week or so and add them to the document. After this I am finishing up 2-6: Behaviour Trees, and then 1-6: AI Planning and 2-7: Goal Oriented Action Planning.

The writing is admittedly a little scattershot, but that’s also because of the order in which tutorial materials are being prepared (which is in a slightly different order).

Recording Update

Right now recording is split across four axis:

1. Tidying up completed scripts for recording.

   1. After all the written version doesn’t always translate into video delivery.

2. Recording the tidied up scripts.

   1. As we get into our more meaty chapters, recording takes a couple of hours at a time such that we can get the quality we want.

3. Preparing the video content.

   1. This means gathering from our existing assets, creating new diagrams, building presentation slides, or recording some of our demo code projects.

4. Editing the videos together.

   1. A big part here is figuring out flow and how to break up material.

   2. Rather than simply give you a chapter that is 1 hour and 10 minutes long, we break up the material into the corresponding section headers - or where it makes the most sense. So one chapter can be several videos in the final edit.

Right now we’re a little behind on recording, having only recorded about half what I planned by this time of year.

A Small Health Issue

In truth this process is more challenging than expected due to health problems I have experienced in the past year. I have suffered from an ongoing case of laryngopharyngeal reflux (LPR), commonly known as ‘silent reflux’. This is an ailment where an excess of stomach acid creeps up the throat and into the vocal chords. It affects your voice, while also leading to an excess of mucous / phlegm in the throat, and a sore throat.

Let me stress that, overall, I’m fine, and in good health. However LPR can have a severe impact on your voice and sadly that is my most precious commodity. After all in the past year I have gone around giving talks, engaged with clients, making YouTube videos and of course recording Goal State. But there are days where I can only comfortably use my voice in that ‘mode’ (anyone who knows me personally can attest the ‘YouTube voice’ isn’t my regular delivery) for an hour at best.

It has also meant my voice sounds deeper and more ‘croaky’. You may have noticed this particularly if you watched the episode on Amnesia: The Bunker last year where my voice is notably lower than usual (viewers even asked about it in the comments).

The good news is, I have been on a range of medication combined with small changes in diet in an effort to address this. I am generally a rather health conscious individual, but specific food, drink, and lifestyle can exacerbate this, and I’ve spent much of the past 2-3 months trying to get on top of it given the medication alone was not enough - and it was also causing side effects due to prolonged usage.

So this is a long way in saying, we’re still pushing forward, but this has slowed me done somewhat.

Practical Update

As detailed in the previous update, Andrew Roper has came on board to support getting all the tutorial materials up to my intended level of quality. Andrew is doing a great job right now as he builds the two strands of practical materials in parallel across two engines (Unity and Unreal). At this point most of the codebase is complete for the early segment of the course on uninformed and informed search algorithms, plus tree search algorithms (Minimax, MCTS), and the next step is implementing all the other pathfinding algorithms (Flow Fields, D* Lite, JPS etc.) in both engines.

But here’s a little of some of the stuff we’ve designed in the Unity project. We wanted to be able to visualise how different algorithms work by visualising how states spaces operate. So these examples show we can run different algorithms in a grid structure and how it leads to us finding paths to states. Not here we show visited states (gold/orange), states in the agenda to be visited (red), the active state (blue) and then the path (purple).

Plus of course we want to get some Dijkstra’s in there given that’s also useful for pathfinding.

Right now the grid is rigid given in the pathfinding tutorials we start playing around with the space by changing its shape, and then you start seeing how these algorithms differ, and then as we go into in the pathfinding chapter we start allowing you to run A* with different heuristics, and then variants of the algorithm to get better results.

As I say, these are all implemented in both Unity and Unreal, and then for the tutorial videos we’ll be providing you with some boilerplate code to start, and then walk through to implement the algorithms.

We should have more to show on this as we continue to put it together.

Grab Your Desktop Wallpapers

One of the backer rewards that I’ve just forgot to get done - sorry about that. We have a collection of wallpapers using the background art assets we had designed for Goal State. You have two versions of each: one with the logo as shown above, and another with a smaller version of the logo in a more reduced format in the corner.

You can find them right here at this link. They’re available in 4K format (2160p). If you have a custom size that would be beneficial, then let me know and I can ask Andy (our graphic designer) to make some updates for me.

Wrapping Up

So there you have it. We’ve made a lot of great progress since the start of the year, and my hope is for the next update you can start to see more written material ready to review, and the first videos will be edited enough for us to show them to you.

It’s all finally coming together, and I have milestones set internally for what we want done for Goal State by end of Q1. So I better go make that happen!

-Tommy

• Metacritic Reacts to VideoGamer’s AI-Generated Reviews

• TikTok Generating Inappropriate AI Adverts Without Permission

• My time at the Gamescom Dev Leadership Summit

The AI and Games Newsletter brings concise and informative discussion on artificial intelligence for video games each and every week. Including industry news, innovative research, emerging trends, and our own exclusive editorial and reporting.

Subscribe now

You can subscribe to and support AI and Games, with weekly editions appearing in your inbox. If you'd like to work with us on your own games projects, please check out our consulting services. To sponsor, please visit the dedicated sponsorship page.

Hey all, and welcome to this week’s edition of . I’m back home after travelling to Lisbon for the Gamescom Dev Leadership Summit. So I figured as I try to get my working life back together I will catch up on the news and give you an insight into what it was like to attend.

Follow AI and Games on: BlueSky | YouTube | LinkedIn | TikTok

Announcement: Vote for Your Reader-Selected Newsletter Topic

It’s time to have another ready-selected issue of the newsletter come your way next month. While it was a tad delayed due to all sorts of editorial timelines, the first voted for issue was the breakdown of AI surveys and finding some meaning in amongst the various editorial spins being put together by various organisations.

I had some thoughts on what might be of interest for you all. Some are unselected topics from our last year’s poll, but also I added in some more current topics that might be of interest. Check it out below:

• Comparing EU and South Korean AI Laws: As South Korea’s legislation comes into effect, how does it compare to the EU and what should games studios be wary of?

• Digging into Steam Data on AI-Tagged Games: The number of AI-tagged games continues to surge on Steam, but are they actually making any money? We dig in to find out.

• Explaining the DRAM Crisis and its Future: The recent surge in DRAM prices hasn’t emerged from nowhere. For the people in the know, this has been coming for a while now. How did we get here? And where are we going.

The plan is for the voted issue to be published around end of March/start of April. So get voting and we’ll make a judgement after the poll closes in a week’s time.

The Gamescom Dev Leadership Summit 2026

So yes last week I was out in Lisbon for Gamescom Dev (i.e. Devcom’s) leadership summit: a 3-day event positioned towards people in leadership across the video games industry. This ranged from the leads of smaller businesses, be they indie studios, co-dev teams or vendors, to the managers and C-Suite of some of the largest players in the industry. I was invited to be the closing keynote speaker of a bumper second day that included a variety of talks, roundtables, fireside chats and hot take sessions.

One aspect of these events is that they operate under a veil of secrecy. A non-disclosure is signed by all participants, and I am limited in how much I can report back to you. However, I want to stress that this is far less nefarious than it may sound if you’re not familiar with these types of events. An NDA is vital given many people here are discussing aspects of their business, be it strategy, performance, and upcoming products - in fact I spent over an hour at dinner one evening having a really fun discussion about the underlying tech behind a highly anticipated 2026 AAA title. But also they’re sharing their own thoughts about issues that affect our sector. Given the nature of this industry, should I report back on some of the things said, that could have an impact on that company for no other reason than the person involved expressed an opinion. Not because anything said was questionable or concerning - in most instances at least - but rather in a world where business leaders need to be seen as resolute, confident, and pragmatic, to reveal yourself as anything to the contrary - to be, dare I say, human - can have consequences.

It’s also a matter of trust. It creates a bubble of transparency and openness that wouldn’t exist elsewhere, and it was interesting to hear the thoughts of people who are in critical leading positions of some of the most beloved and successful franchises and studios in the world as they tell me about the things that keep them up at night.

I don’t sugar-coat it when I say it gives them sleepless nights: this was a point raised in presentations other than mine, and a recurring theme that emerged among attendees was the sense of validation in knowing that other people in similar positions are worried about the same things they are. As cliché as it sounds, it’s lonely at the top, and knowing what to do in the moment is daunting.

This segues nicely into my area of expertise: the boom of generative AI in the video games industry. I was invited both to present a talk on the subject, as well as be a roundtable captain alongside Tsahi Liberman. Having open and frank conversations about whether studios are using generative AI in their games, what their concerns are for its adoption, and what impact all of this could have in the long run.

It was encouraging to see that many of the conversations I had, be it during the roundtables, after my talk, or throughout the week, were focussed on issues we have discussed in this here publication in the past year or two:

• Knowing where to draw the line on generative AI adoption. Focussing on generative AI in processes, but not in game production.

• The importance of recognising need for good AI policy in studios.

• Acknowledging the strong dislike of generative AI appearing in products in the PC and console spaces.

• The lack of understanding and knowledge of whether generative AI will actually deliver value.

• The long-term implications of embracing generative AI be it in player sentiment, flooding of the market, regulatory hurdles, and the quality of games.

Again, I can’t get into specifics, but it was encouraging to see a lot of the issues I raise are things that are being discussed at these companies, and that my presentation helped validate a lot of their concerns on how the industry is moving forward.

Ultimately it was a really interesting event, and a pleasure to get to hang out with a lot of really fun people who had been involved in the development of some of the biggest games in the industry. A thank you once again to the organisers for having me present.

AI (and Games) in the News

Let’s wrap up this edition with some of the headlines of the past week or two.

Publisher Finji Fights Back at TikTok’s AI-Generated Manipulation of Assets

A really bizarre and quite disturbing story that broke on IGN last week was about game publisher Finji, famous for their involvement in titles such as Nights in the Woods, Tunic, and last year’s Usual June. Finji made public of an ongoing dispute with TikTok of using generative AI to create modified version of their advertising assets without their knowledge.

TikTok has AI features that allow for them to publish variations of your advertisement using generative tools so as to reach broader demographics. These are opt-in by default and Finji had refused to adopt them. However, CEO and co-founder Rebekah Saltsman stated that they have been in an ongoing dispute with the social media company in the past few months as it was creating adverts that showcased "sexualised, racist, and sexist representation" of the Usual June game from last year. TikTok initially denied being responsible for this, and now an investigation is underway.

VideoGamer Removed from MetaCritic After AI Review of Resident Evil Requiem

Once beloved gaming website Videogamer has fallen from grace in recent years. It had a strong following in its early days and had a team of rather eclectic voices who would subsequently go on to do great work in other areas of gaming press (including Chris Bratt who would later found the YouTube series ‘People Make Games’).

More recently the publication was bought up by the notorious Clickout Media, who are renowned for buying up sites to then fill them with SEO-optimised clickbait to push their advertisements towards gambling and casinos. During this time most of the staff were fired, with the intend to move towards maintaining a crew that essentially micro-managed AI.

Well, this all blew up last week when their review of the recently released Resident Evil: Requiem got the internet ablaze. Not just because it’s AI-generated nonsense - see the quote below - but also that it was still considered a valid publication on Metacritic.

Resident Evil Requiem is not just a victory lap for Capcom’s survival horror dynasty; it is a chainsaw-revving, blood-soaked testament to why we love getting scared stupid. It is the sort of finale that effectively grabs the franchise by the lapels, shakes it violently, and demands you acknowledge just how far it has come since the tank-control days of 1996. While other series limp toward their conclusions, RE9 arrives with the confidence of a Tyrant smashing through a brick wall.

I mean, I know not all games journalists are poets, but this is so cliché-laden and lacking in any nuance that you get the gist it was generated by GPT.

Further digging into this found that while the review clearly looks AI-generated, the author and their bio and headshot have been generated with GPT as well - plus those of other journos at the site. This has subsequently lead to Metacritic removing the publication from the site, and a statement being issued that highlights that their policy is to never include AI generated reviews, and will remove any publications found to be adopting this approach.

The shadiness of this aside, it’s important that Metacritic takes a stance on this given the (over-inflated) importance it has in the eyes of executives. Given it’s often used to highlight critical reception of titles in investor calls, and has also been the source for decision making in bonuses given to developers. AI content in this space has the potential to manipulate this process.

New Tool for Catching AI Disclosures on Steam

The recent Steam NextFest has once again raised questions surrounding the adoption of generative AI in PC games. To that end, an new browser plugin for FireFox and Chrome, entitled ‘AI Warning for Steam’ is built to identify whether a Steam page has an AI disclosure and put it front and centre in your face.

Should the disclosure be identified, it presents it as shown above as a modal pop-up, and blurs out the rest of the page until you have acknowledged it. Thus ensuring you know 100% that there was an AI disclosure for this game.

At a time where it feels Steam is de-emphasising the adoption of AI tooling - an issue I complained about a few weeks back - this is the consumers working to make it front and centre.

At the time of writing, this plugin now has over 4000 active users across Chrome and Firefox.

Wrapping Up

That’s it for this week. I’m still trying to get back into the swing of things after the Leadership Summit trip tired me out. But expect a Goal State update for backers by the end of the week!

Welcome to The Take, our editorial issues of the AI and Games Newsletter where we dig into the bigger issues impacting artificial intelligence in the video games industry. Issues of The Take are exclusive to premium subscribers of AI and Games.

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Hello one and all and welcome to this week’s edition of . Today this issue lands in your inbox as I am attending the Gamescom Dev Leadership Summit in Lisbon: a 3-day retreat for leading professionals in games to come together and discuss the issues impacting our sector. I was invited out here to present a keynote on AI which will take place later this evening, wish me luck!

The leadership summit is designed largely to operate behind closed doors, and we agree to an NDA upon arrival. This means that my ability to report back on this for readers will be quite limited. That said, I will strive to put together a summary next week that covers some of the talking points raised throughout my time here, and reflect on my own experiences with respect to my non-disclosure.

In the meantime, I was around 30-40% through writing another topic for this edition of The Take, only for the news about Microsoft’s leadership swap to blaze across the internet last Friday. Usually at this point I’d just soldier on and we’d make that but one of the headlines in our news round-up, but actually this felt worth changing my existing plans given it touches on a point I raised just last month.

Onwards!

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Announcements

Just one this week, short’n’sweet.

New Case Study on GameBot’s COTA Demo

Not content with launching a case study on Snowcap at the start of the month, we just published a new piece both on the website and YouTube about COTA: a technical demo created by GameBot designed to showcase how they have built an LLM architecture capable of playing entire rounds of a tactical first-person shooter.

The COTA demo is available now for anyone wanting to try it out. I was invited a few weeks in advance to try it out and give my impressions. Plus we had a stack of questions for GameBot about how it all works, and had the pleasure of getting insights from the project lead Mu Yang. You can read it on the site now, or check out the accompanying YouTube video which has a lot of footage of the demo in action.

The Take: Microsoft Gaming’s Change of Leadership

Last month I wrote my 2026 predictions issue: my overview of every major talking point I expect to be coming our way in the next 12 months. After publishing, I spoke with some members of our Discord community as well as folk out in the industry about what I wrote - it’s true I do actually meet folks who read this newsletter in the real world! While some readers argued I’d went for low-hanging fruit, the one that raised a few eyebrows was #9: The Death of Xbox as a Platform.

To quote the end of that segment:

By the end of 2026 there will still be Xbox consoles on the shelves - assuming stores keep selling them. But unless efforts are made to improve the public image of Xbox and the value it is bringing to players as a platform, the console space they operate in will be largely a net loss, and the brand would be best served as a games publisher on PC, PlayStation and Nintendo.

This argument was driven largely by both the repeated failure to give a reason and justification for the Xbox as a console, but also with how the gaming vertical sits within Microsoft’s broader business. To my mind, it’s not a sustainable strategy in the long run for them to maintain Xbox as a portfolio of hardware to sell subscriptions given the parent company’s broader goals and AI-focussed aspirations.

Now one thought that had crossed my mind - that I wasn’t confident enough to predict - was that Phil Spencer could step down and allow his next-in-line, Sarah Bond, to take the mantle. Spencer would then assume a different role within the Xbox space at Microsoft. However what transpired last week, was even worse than what I had anticipated, and it only further accelerates the trends I’ve observed that my prediction was based on.

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February 24th 2026 saw the release of COTA: a technical demo showcasing GameBot’s new AI bots that are powered by large language models (LLMs).

COTA, which stands for Cognition, Operation, Tactics, and Assistance aims to highlight how the developers have built an LLM-driven AI architecture that can reason on micro- and macro-gameplay levels, react to changes in game state, plan strategically to achieve tactical goals, and coordinate a team of both AI agents and humans in real-time. Though the real highlight, is that GameBot asserts that their solution gets around the latency problem, with the underlying architecture capable of coordinating all of these bots with a response time of less than 100ms.

For this edition I’m going to dig into how COTA’s underlying AI architecture works. With the demo now live for anyone to download and try out, we were invited to playtest a pre-release version to get an idea of how it all works, and put together some initial impressions of how it all plays in the moment.

It’s an interesting idea for sure, and I can attest that it works: the bots are fast, responsive and capable of playing through entire rounds of gameplay in ways that feel coordinated and sensible. But it feels like there’s still a bit of work to be done both in the quality of underlying behaviours as well as how this is all communicated to the user.

We’re going to dig into the underlying architecture of the bots and how they operate in action, plus we also had GameBot answer my questions about how this all works and what the future of this tech is shaping up to be.

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GameBot and the COTA Demo

So a quick overview of what the demo is all about before I get into the weeds of it. Built in Unreal Engine, this demo has you play a stripped down clone of Counterstrike’s Dust 2, and has players face off in a 5v5 game of bomb defusal - with the team of counter-terrorists defending their side of the map while the terrorists seek to plant the bomb and set it off to score for the round.

But the focus is on the bots you play alongside. In each round of the demo I was playing alongside four bots, against a team of five bots. However unlike a regular playthrough, I can observe at any time not just the strategy the bots are making, but deep-dive into their decision making, plus I am being told by the bots what to do in the moment. Given I’m part of the team, I am given instructions on how to proceed in ways that fit the broader strategy, and this updates and changes as the teams overall gameplay progresses. The devs are confident that this architecture provides a general purpose decision making framework that can adapt to different genres as well as scale to other game modes and situations.

The project stems from a company called GameBot, who have dev teams across North America and Asia, and have been involved in building bots for mobile games since their inception in 2019. The company has cut its teeth building AI bots for the likes of PUBG Mobile plus League of Legends: Wild Rift, the portable version of Riot’s beloved MOBA. These bots have ranged in their technical complexity but often using a combination of traditional game AI alongside supervised learning and reinforcement learning techniques - which is an increasingly popular approach to bots in mobile gaming. But this is the first time around - to my knowledge at least - that they have built a bot that is being driven by generative models.

It’s worth stressing as we move forward, that this is distinct from the MLMove project that we discussed late last year. MLMove was the use of a lightweight 21MB transformer - the type of neural network used for large language models - that sought to handle the movement for modded bots in Counterstrike by learning from data from esports players. COTA on the other hand is dealing with more than just the movement, it’s handling both individual actions and team tactics, while also recognising and responding to the player’s actions - and as we’ll discuss in a moment, it does so without the use of player data.

So let’s kick things off with a quick breakdown of what it’s like to play the demo, and what is happening under the hood as you play. As you can see in the image above, I can bring up a UI the left hand side of the screen what our teams strategy is - both the global strategy, as well as what my priorities are for the round. As the round continues, both the strategy of the team, as well as what individual team members should be doing shifts accordingly.

For this to work as shown, the underlying COTA architecture is running a two-tiered system, there is the commander layer, which is the strategic layer for all the bots, that is thinking on the global or macro scale. It’s assessing the map control, the intensity of combat, and potential strategy of the opposing team, all while analysing the overall status and health of your team. The commander will then dictate the overall strategy: are we going to attack a point, maintain control over a section of the map or rotating to another, or fall back.

Then there is the operator layer: which is the individual bots. Each of the bots is focussed solely on their own individual behaviour in the moment: reading the game state to then decide how to move, aim, shoot etc.

Decisions from the commander layer are filtered down into a individual strategies for each operator. Meanwhile the operators acknowledge the strategy, and factor that into their decision making alongside how to create a movement path (deciding where to move towards and how to angle the view), alongside the contextual placement and actions such as firing or throwing grenades.

Now as you can see from the image above, the output of the LLM is a ton of text, but how does that turn into gameplay? Let’s go a little deeper into the tech stack.

The COTA Tech Stack

Given we mentioned it from the top, we know COTA is using Large Language Models, but I wanted more information on what’s really going on, and credit to GameBot - after I sent a stack of questions about the structure of input data, processing of game state, the training mechanisms for the LLM, the size of the model, the context window and prompting practices, and behaviour execution, I got my answers from the devs directly, with help from COTA’s project lead Mu Yang, who is also the director of algorithms at GameBot.

The first thing Yang clarified for me is the system is dual-layered, meaning it runs multiple models in the architecture. Separating the commander from the execution was a deliberate decision given LLMs historically have been shown to struggle with handling macro and micro behaviours in parallel. Hence having the commander do the big thinking while the operators acknowledge this in their own behaviour seems like a natural fit. This also helped keep the 100ms limit on reasoning that the team had planned for, given this was considered an acceptable timeframe for fast and responsive behaviours.

But how are these models are trained? As I mentioned earlier MLMove was achieved by pulling down scores of data from professional players, but COTA is running this entirely without user data. First up, the Commander needs to have a broader understanding of how the game plays, and be capable of processing information about the game state effectively.

Mu Yang: We ran extensive internal tests and found that an 8 billion parameter model is the right balance [totalling 16.5GB in disk size]. It’s large enough to reason and understand the complex situations. We begin with supervised fine-tuning, or SFT. Based on prior commercial projects, we built a data synthesis pipeline to generate gameplay samples. Each sample contains a game state, a text instruction, and a game action. A subset of this data is annotated with chain-of-thought reasoning. We then apply GRPO-based reinforcement learning on the remaining data. We created rewards for action correctness and output validity. Finally, we used reinforcement learning from human feedback to align the commander’s decisions with human intent.

Meanwhile the operators require a similar but different approach, given they need to have clearer understanding of the rules of the game, such that they stay on target and on point.

Yang: The operator follows the same overall training structure, producing a ‘teacher’ model we call ‘Operator Thinking’. Operator Thinking receives richer inputs than commander, including first-person visuals, map information, game rules, and high-level instructions from the commander. Its output includes both reasoning and the textual action descriptions. At this stage, the model demonstrates strong generalization and can adapt to new maps or rule sets.

So as Yang described, the original operator model is capable of making intelligent decisions about what to do in the moment. But the thing is, it’s too big. Hence as described, this first operator model is what is known as a teacher. GameBot then use an approach known as the Teacher-Student model, also referred to as knowledge distillation, where a smaller version of the model - called the Student - is trained by distilling down the information in the original teacher model into something smaller.

This modified student model also has game rules and map knowledge being mapped into it directly, alongside compressed state descriptions and a game specific action head to the attention layers to help with multi-action execution. So while distilling down key information from the original model, plus making these additional tweaks, it means it can make decisions within the 100ms limit.

Now what you see in the commander and operator UI layers is the outputs being generated by the LLM. This is being fed from information from the game state, and then it’s being processed. Each operator is gathering information from the current frame using traditional game AI methods such as environmental queries about whether they can see opponents, as well as basic information as to their current position and movement and status. This character-centric approach prevents giving bots any information from the game state they should not have in the moment. This is then translated into a text-based prompt that is fed into the LLM, and what you’re seeing in these overlays is the output. This text is then parsed and translated into actions in-game, and this is all being done server-side behind layers of security to prevent it being manipulated.

Yang: All inference runs server side. The operator runs on the server, and its actions are sent directly to the game server. Both systems run in the same server cluster to minimize latency. There are no predefined behavior scripts. All actions are generated by the model itself.

Our First Impressions

Having spent several hours playing through the COTA demo over the past couple of weeks, it really got me thinking about on multiple levels. The efficacy of the tech: does it actually work in context? But also how does it feel to play a demo where I am working these bots, and am also - to a certain degree - having my behaviour governed by one.

I’m left with some mixed feelings about it. For one thing it is technically impressive. The bots do work: the team are executing entirely via the LLMs. There is a sense of overall collaboration, they react to changes in the game state, they are capable of acting in the world in ways that make sense the majority of the time. Outside of a few hiccups, the performance of the game was generally quite smooth, and I didn’t notice any impact from the LLMs on the server running their inference. However, there are a number of qualitative factors to consider, both in the performance of the bots as well the way in which this is integrated that make it difficult to enjoy the demo itself.

Strategically the commander is capable of both devising tactics, breaking them down for individuals, reacting to changes, and then reformulating the plan in real-time. This was interesting to observe as things changed, during a round, as well as having it observe what I do. After all I would sometimes follow orders, and other times just ignore it - or actually fail to understand what it wanted. It’s capable of reacting to this accordingly - though sometimes I noticed it just doesn’t give me anything to do? Perhaps it’s just fed up with me. Admittedly it was more fun to watch teams of bots go at it against one another. It strikes me that could be a game mode in and of itself if you can feed your ideas to the commander.

Though I noticed several times that it employed some... questionable strategy, or felt repetitive. Far too often the strategy as an attacker was to push up on Alpha by splitting the team between ‘alphalong’ and ‘catwalk’. We very rarely, if ever, attacked Bravo. Meanwhile it feels like there’s a need to dictate to operators the level of urgency with which the commander’s strategy should be executed, or by having more global state knowledge. I watched as my team lost several rounds where we either failed to catch a defender defusing the bomb, took too long to rotate given they would go all the way back to spawn, or in some instances failed to defuse the bomb in time despite us having control of the point, and the opposing team was all dead.

I do think more could be done both in the movement and in the final execution layers. Given I would see bots bunch up turning corners or entering areas of the map, making it all too easy for them to get wiped out. Meanwhile I noticed in spectator mode that a lot of bots take shots when they’re behind cover, or have their view either lurch around, or snap to an enemy’s location too aggressively. The latter is certainly a difficulty feature, but a lot of this could be refined by building more fleshed out behavioural macros that the LLM outputs could be processed into.

Ultimately for me, the big problems with the demo - which was addressed to some degree during the preview window - was the lack of UX design surrounding the bots. This isn’t a generative AI problem, it’s a game AI problem - and if you’ve followed for a while, you know how often we talk about using additional flourishes in art, animation, UI, and audio to help communicate the behaviour of NPCs - and for me a lot of what would really help sell these bots is currently missing. Naturally of course this is a demo about the tech, but I don’t think you can sell one without the other, and so I want to break down what was perhaps for me the biggest hurdle I had when playing.

As you’ll have noticed throughout, there’s a huge amount of text on screen, be it the global strategy, or my individual actions, and those of others. Even when it’s just the immediate actions sent to me by the commander, it relies on a lot of built-in knowledge about the map design and even some terminology about what I’m meant to do. Of course I’m going to learn that over time (and I’m not a Counterstrike player so it did take minute) but the issue is I have to stop looking at the centre of the screen - where the action is - to focus on text coming in via a text field. This also updates frequently and trying to read all of that while in the thick of combat is a big ask. For me this can be mitigated in a number of ways:

• Adding voice lines and barks for the bots and the commander.

• Having the UI and HUD highlight where I’m meant to be going.

• Simple UX cues to indicate whether I’m operating in line with the intended strategy.

During the preview window the demo was updated to include barks - which for those unfamiliar is a way to communicate information in a condensed format - and while it’s going through a text-to-speech pipeline that sounded pretty rough, it already made a huge difference. Suddenly having a lot of game state information - and the intended actions of the bots - be condensed into short audio soundbites was really useful. I could just listen to them speak to me, and then react accordingly. The thing that’s now missing is having the commander clearly tell me whether I’m adhering to the strategy or not, given I would rather not have to focus too much on that text field.

The most recent version also includes the ability to speak into the microphone, where I use a speech to text pipeline to communicate with the bots. I sadly didn’t find much value in it, given I didn’t really feel like anything I said was having any material impact. I would try and share information about my current strategy, where I spotted targets and ask for what to do. But I never really felt like this input had value, nor were they really responding to me. I will stress as well I don’t enjoy talking to NPCs, given it adds an additional level of cognitive load where I had to think about not just what I want to say, but how I say it such that an AI bot will interpret it. After all first it has to get past my Scottish accent - and I noted several times the speech-to-text only understood half of what I said, but also I have to make sure I’m having to think of how to express this information such that the LLM will process it. This was a similar issue that I had not that long ago when Ubisoft invited me to try out the Teammates demo - which I wrote about in our weekly newsletter over at AIandGames.com. So it’s not necessarily an issue specific to COTA, but rather a problem that this type of game design will have to reckon with in the future.

For me it’s about doubling down on the UX design, particularly in audio barks and the HUD. If the devs can work through that, then it could really add value to the player’s experience.

Closing

So that’s the COTA demo for you. As mentioned earlier the project is out now, and it’s free to download and check it out. I’ve spent a few hours with it over the past couple of weeks, and I started getting more adventurous with it over time. Plus GameBot are encouraging people interested in the project to join them in their Discord server to share your thoughts and give feedback on the project. Links are at the bottom of this article.

• Check out the COTA demo at:
  https://gamebot.ai/product/cota-apply?channel=kl_01
  

• Visit the GameBot Discord:
  https://discord.gg/vWrGCHGsKc

A thank you to GameBot for reaching out to us try out the project and collaborate on this issue, and for taking the time to answer our questions as well. It’s nice when we get to ask more technically complex questions to the PR team and then the devs answer them for us. It’s very much appreciated.

• We talk to Supercell about their AI 2026 Innovation Lab as applications close this week.

• Game AI Uncovered volume 4 is out now, with words from yours truly.

• EA Sports FC using generative AI support commentary.

• Plus tech specs dropping on PC a reaction to AI-driven RAM shortages?

The AI and Games Newsletter brings concise and informative discussion on artificial intelligence for video games each and every week. Including industry news, innovative research, emerging trends, and our own exclusive editorial and reporting.

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Hello one and all and welcome to ! For this week’s edition I sat down for a chat with Taavi Paananen and Matias Varjonen to talk about the 2026 iteration of Supercell’s AI Innovation Lab. What was a 10-week event located in Helsinki in 2025 has now expanded into a 9-week programme being hosted at multiple sites around the world that is providing financial support, AI resources, and mentoring for aspiring teams and individuals to experiment with how to use AI to build games never seen before.

With the deadline for applications closing this week on February 22nd, I dig into what Supercell have been up to, give you a breakdown of what this programme is offering, and chat with Taavi and Matias about the broader plans and aspirations of the AI innovation team.

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News and Announcements

Alrighty, before we get into our big story, a quick run through of some announcements, plus a couple of headlines.

Game AI Uncovered Volume 4 is Out Now

The Game AI Uncovered series, which includes a chapters written by game AI professionals on their projects, has released a shiny new 4th edition. Edited once again by Paul Roberts, this edition includes behind-the-scenes insights in the making of games such as Undisputed, Dirt, Grid, Wherewolf, Psychonauts 2, and Hawken Reborn.

In amongst all this awesome stuff, I have also written my second chapter for this series - a beginner’s guide on AI character design. It’s great to be part of this all over again, though as I discussed on LinkedIn I had forgotten which volume my work would appear in. I almost bought a copy last week until Paul reminded me I get one for being a co-author. It speaks to the amount of work that is required to go from initial draft to launch, and congrats once again to Paul and my fellow co-authors.

The book is out now via the Routledge website, and other booksellers.

AI-First Publisher Krafton Clarifies AI Use in Project Windless

Announced last week at PlayStation’s most recent ‘State of Play’ event, Project Windless is developed by Krafton Montreal Studio, and has players control a 9-foot humanoid rooster named Rekon. Inspired by the book series “The Bird That Drinks Tears”, the game appears to borrow from the Dynasty Warriors formula, yet somehow looks even more violent and ridiculous. I am officially intrigued…

Given that Krafton have previously declared they’re moving forward to becoming an AI-driven business, it does lead to questions about pretty much every single production they’re working on as to how much Generative AI is involved, given it continues to be something that the vast majority of players are simply not interested.

As reported by Victoria Phillips Kennedy at Eurogamer, Krafton responded to questions on this and stated that the game doesn’t use generative AI in the game itself. Only exploring it “internally during exploratory phases”:

"For Project Windless, the Montreal team is taking a traditional, craftsmanship-driven approach to single-player development. The team primarily uses AI internally during exploratory phases to support iteration and efficiency rather than as a central, player-facing feature of the game.

The game is currently aiming for a 2026 launch date and is planned for PC and PS5.

Upcoming Lego Batman the Latest Game to Drop RAM Specs During AI Drought

Releasing on May 26th, Lego Batman: Legacy of the Dark Knight is looking to be on the big releases of Q2. Heavily by the wide range of movies of the popular DC character, and the Arkham series of games, this caught many people’s attention when it was announced during the Game Awards last year.

The other reason it caught people’s attention was that it originally had a system requirement of 32GB of RAM, which is quite high for a new title even now in 2026. However it was noted last week on a Steam announcement - much like IO Interactive’s 007: First Light before it - that it has since dropped the RAM requirements down to 16GB.

In an age where RAM costs continue to increase due to AI datacentre demand choking up supply, I think we’re going to see a lot more effort by studios to optimise titles at release and trying to low the memory requirements as much as possible.

The AI Crunch on Hardware Only Gets Worse

As we’ve discussed in recent weeks, the situation with hardware shortages driven by the rush to build AI datacentres is really ramping up. I knew things were going to be bad this year, but it’s interesting - and depressing - to see just how quickly this is ramping up.

In the last week I’ve seen four different stories crop up on this trend:

• The Steam Deck OLED is currently out of stock in the US and Japan, with Valve confirming there will be stock fluctuations throughout the year.

• The ASUS Rog Ally X has seen a price increase of just shy of $200 in Japan - because it runs on a faster version DDR5 RAM.

• Rumours are abound that Sony will delay any PlayStation 6 plans due to the current RAM crisis - which lets face it, could last for a couple of years.

• Hard drive manufacturers Western Digital and Seagate have sold their entire 2026 production quota already. Where is it going? AI data centres.

It’s only going to get worse before it gets better. Who knows, maybe when the bubble bursts you can some new hard drives and memory at a discount?

Unity and Godot Share the AI Headlines For Completely Different Reasons

So yeah, two stories this week that are very different for each other. The first came from the recent earnings call from Unity where CEO Matthew Bromberg addressed their current AI offerings by stating their new AI toolchain - which will be showcased at GDC 2026 - will “remove as much friction from the creative process as possible”. Essentially they’re expanding their generative AI tools to make it easier to create assets and code.

As Chris Kerr wrote on GameDeveloper, Bromberg suggested that it will “enable developers to prompt full casual games into existence with natural language only, native to our platform—so it's simple to move from prototype to finished product.”

Spoken like someone who has never shipped a game before, but okay…

Meanwhile, Unity’s emerging (and still largely liked) competitor Godot has suffered from some of it’s own AI woes given it’s an open source game engine.

Thanks again to Chris for writing up this piece about how the team maintaining the GitHub repository for Godot are being inundated by pull requests (changes to the engine code that are being offered up to integrate into the project) that they suspect are being generated by AI given their quality. You can catch Godot engine’s project manager Rémi Verschelde’s comments below.

EA Using Generative AI in Sports Commentary - A Natural Evolution?

Last one for you this week comes from a recent interview in the BBC with football commentators Guy Mowbray and Sue Smith on their voice work for EA Sports FC. More specifically for us, they highlight that EA is now adopting generative AI to help support the workloads put upon each of these presenters.

While the adoption of generative AI in voice performance is a contentious issue - ranging from SAG-AFTRA strikes to even my own op-ed on its usage in Arc Raiders - sports commentary always struck me as a sensible place for it be adopted. As Mowbray himself states, working on commentary for sports games is a “never-ending job” as they need to update voice work for new player - with over 20,000 names in more recent entries as they include more leagues in both the men’s and women’s sport - plus addressing new terminology, and adding flavour. As Smith says the team works on this for hours a day for months of the year, and it adds a lot of strain to their voices as they add lots of different variations on the same sentence - given it has to have contextual relevance - all the while ensuring their voices “have to be perfect”.

The use of AI is seeking to remove some of the strain on their workload, while working to maintain the overall quality. It’ll be interesting to see how this all comes together in future versions of the game.

Supercell’s Plans to Kickstart AI Innovation

As regular readers can attest, 2025 was a pretty crazy year in the space of AI for video games. There’s a lot of companies making moves throughout, but the one I was watching from afar is perhaps not who many would think of, the mobile gaming giant Supercell.

Headquartered in Helsinki with offices and studios across the world, the studio famous for titles such as Brawl Stars, Clash of Clans and Clash Royale had been exploring the current state of machine learning and generative AI for game development; hosting an AI meet-up in San Francisco during GDC, and at other events in cities where their studios were based - ironically I was invited to one in London last year, but I was visiting a client in Helsinki.

The Three Horizons: The company has established an AI strategy focussed on ‘horizons’ that lean on three verticals: of operating smarter and faster, of proving out features for new game ideas, and experimenting with new frontiers for players to engage with Supercell IP.

All of this is supported by what would become Supercell’s AI Innovation Lab: an idea that originated as a 10-week pilot programme for game/AI creators in the spring of 2025 in their Helsinki offices. The studio has since become very excited about the possibilities, with this year’s initiative running as a 9-week incubator programme across multiple sites around the world. This year the studio is now having three cohorts run in parallel, having opened up a new AI innovation lab in their San Francisco offices last fall, and the dedicated hub in Tokyo opening in March this year.

Here Comes a New Challenger: Now let’s face it, Supercell isn’t the only company making these kinds of moves. But unlike many others they’re moving fast, and they’re increasingly public about their efforts. All that said, from the outside-in, it’s difficult to determine their intent, and ultimately what they hope to achieve. Late last year I had a chance to sit down with Taavi Paananen and Matias Varjonen, the team behind the first Supercell AI Lab in Helsinki, to find out more about their work, and whether all of this would pass the sniff test. It was a fun and interesting conversation, and it was great to see that we are aligned in many respects. So we had a follow-up chat earlier this month to discuss the 2026 iteration of Supercell’s AI Innovation Lab as applications are about to close on February 22nd.

Supercell’s Approach to AI

When I started hearing rumblings about what Supercell were up to at GDC last year - I had people texting me updates during their meetup while I was at another party - I couldn’t help but be a little cynical. After all, I’ve spent much of the past two years reporting in this year’s publication about all the half-baked and ill-conceived pushes companies are making into AI. Be it AAA companies delivering nothingburger statements for investors, to start-ups promising the earth and quietly fading into obscurity.

Of course for parity’s sake we’ve also seen a lot of companies come out, saying the right things, and doing interesting stuff, be it Ubisoft, Studio Atelico, Meaning Machine, Lingotion etc. But what was Supercell’s take going to be?

Focussing on the Players: What struck me from the get-go was the insistence on avoiding the very pitfalls and trappings of other studios. As Varjonen explained, the intent of the innovation labs is to act as an incubator for finding out what AI could offer to players, and not simply investing as an exercise in efficiency or cost-cutting .

“We see AI as one tool in the toolbox, while the player experience remains at the forefront. We don’t believe in AI for the sake of AI” said Varjonen. The intent wasn’t to jump into this wholesale and have the rest of Supercell fall in line, but rather have the work bubbling up from the labs be presented more broadly across the company; discussing whether this makes sense in the broader scheme of their development pipelines. After all, something that works in an incubator isn’t guaranteed to work when the complexities of real-world production bears down upon it.

“For us, the AI innovation lab is Supercell’s in-house incubator program. Its mission is to explore what is now possible in games that was not possible before.”

As we discussed over coffee, while many studios in the games industry are having conversations about the value of AI - be it tinkering with tools, running pilot programmes, or working to placate investors - very few speak about it publicly. Heck it’s how we wound up sitting down together, given I knew they were making moves - and while we’re one of the few publications out there discussing both the pros and cons of AI in the games industry. As he explained, it was important for Supercell to not conduct this R&D behind closed-doors, but instead try and encourage the conversation on AI in the sector.

An Opportunity for Game Creators: As Matias explained, “AI has levelled the playing field for builders: allowing anyone with a vision to hop on the developer’s seat. Yet there is a lot of unhappiness within the industry, be it lack of funding, a shift in the market, or changing player expectations.” These are issues I’ve discussed on the newsletter throughout this past year. The game market is currently highly volatile, and inconsistent - with the likes of Wildlight’s Highguard and Riot’s 2XKO sadly being the first casualties of 2026. Plus as we discussed with Carli Stein and Cassia Curran last year, the investor market on both sides of the AI/gaming sphere is still a challenge.

This is where the innovation lab hopes to provide an opportunity for people interested in exploring recent innovations in AI. Both in terms of the all-important monetary support, but giving people an opportunity to gather meaningful feedback from developers and players. Varjonen describes their ambition for the innovation lab to “be a lighthouse. To help people find their place, and launch their crazy visions. We have the launchpad, they just need to build the rocket.”

The 2026 AI Innovation Lab

The plan for the 2026 innovation lab is for selected participants - be they individuals or entire teams - to spend 9 weeks with a suite of tools and resources at their disposal to work on crafting new game ideas and concepts using contemporary AI technologies.

Starting with a week-long kick off bootcamp in Lapland, Finland, the remaining 8 weeks take place at one of three labs sites (Helsinki, San Francisco, Tokyo). Participants receive financial support to cover housing and essentials during this time, and will be provided office space to set up their projects, mentoring from staff at Supercell, as well as have the opportunity to engage with the company’s broader ecosystem to get feedback on their ideas. Including participating in a demo of their projects that could lead to their projects being spun up internally within the company, and a permanent job alongside it.

Support Comes in Various Forms: Naturally if we’re talking about modern AI, especially generative AI, that also comes with a cost attached to it. Training and deploying generative models is an expensive proposition, and so Supercell are providing 50k in credits for compute - allowing for AI models to be trained, iterated upon, fine-tuned, and then deployed - plus an additional 20k for testing their ideas out with real users. This can mean running pilot programmes on prototype projects, and supporting the overheads of deployment, and ensuring the additional compute costs for hosting an AI model on the server are covered.

While there is an opportunity to demo the projects at Supercell HQ, the thing that did catch me by surprise is that despite so much investment, they are not enforcing equity or intellectual property rights. Should participants conclude their time with the lab and decide to take their ideas elsewhere, they’re free to do so.

Paananen summarised it pretty succinctly: “It is not often that the best company in its field opens up its doors for innovation, takes no IP, and simply pays for all flights, housing, and other necessities for 9 weeks.”

Well, no… it’s not that often at all.

Apply by February 22nd

I’d be remiss to point out that the deadline for the innovation lab closes this week!
If you’re interested in applying, here’s some key information you:

• Application Deadline: February 22nd 2026 (i.e. this Sunday)

• Program Period: March 23rd to May 2nd 2026.

• Location: At one of Supercell’s AI innovation labs in Helsinki, San Francisco, or Tokyo. With the opening week being a bootcamp held in Finland.

• How To Apply: Visit ailab.supercell.com and smash that apply button.

Participants are expected to be on-site at one of the three sites throughout the project. So do bear that in mind. Someone’s going to need to look after the cat!

Wrapping Up

What comes out of Supercell’s Innovation Lab this year will certainly be worth watching out for - and who knows we might be able to deliver a follow-up on that later in the year.

In the meantime, thanks to Taavi and Matias for his time, and best of luck to everyone applying for the innovation lab. It certainly seems like a unique and exciting opportunity.

As for us, we sadly don’t have time to spent 9 weeks hacking away at prototypes, we have work to do! In fact next week I am in Lisbon as I present a keynote for the 2026 Gamescom Dev Leadership on AI in the video games industry - shock surprise - and while I won’t be able to talk much about what I’m up to, we will still have an issue of in your inbox on Wednesday. See you then!

• Take-Two insists GTA6 will be free of generative AI.

• Chappell Roan’s Fortnite collab celebrates human artistry.

• Roblox plagiarises Expedition 33 for its AI world model.

• And China’s games industry is all-in on AI investment.

The AI and Games Newsletter brings concise and informative discussion on artificial intelligence for video games each and every week. Including industry news, innovative research, emerging trends, and our own exclusive editorial and reporting.

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Hello one and all, and welcome to . We’ve got a lot going on behind-the-scenes right now, so we figured we’d dedicate this issue to all our premium subs to let them in on what’s in the pipeline. From our 2026 conference to our case studies, 2025 conference recordings, Goal State, and of course this here newsletter.

But before all of that let’s quickly round up the news from the past week, including more generative AI plagiarism, and both GTA6 and Fortnite advocating for human-crafted games!

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Last Week’s Headlines

A quick round-up of interesting stories that crossed my path in the past week or so.

Roblox Showcases Their Own ‘World Model’, Plagiarising AAA Games In Process

Roblox have been diving head-first into the world of generative AI research for some time now: investing in tools they can support creators ranging from texture generators to 3D asset construction. But last week they showcased some of their work in World Models - just like Microsoft’s Muse and Google’s Genie 3 that we’ve reported on already - via a thread on Twitter/X.

However unlike Genie 3, where Google at least had the smarts to try and showcase the tech without using any copyright infringing works (even if users were able to weed it out quite easily), they thought it was a good idea to demo the behaviour of the system using output that clearly infringes upon both Claire Obscure: Expedition 33 and Avatar: Frontiers of Pandora. While the latter is a little more vague, the opening of the video (including the thumbnail above) clearly shows the character Maelle wandering through an area inspired by the ‘Flying Waters’ locale in the opening 2-3 hours of the game.

As they stated later in same thread, they’re training NPCs by learning from 13 billion hours of player interaction data they accumulate every month on the platform. Thought they don’t seem all that enthusiastic about mentioning where the world model data comes from…

Take-Two Insists GTA 6 is Gen AI Free

In a recent earnings call, Take-Two CEO Strauss Zelnick insisted that the eagerly anticipated (and repeatedly delayed) Grand Theft Auto 6 will have zero evidence of generative AI in the final product. To quote (lifted from reporting by NME):

“With regards to GTA 6, generative AI has zero part in what Rockstar Games is building. Their worlds are handcrafted. That’s what differentiates them.

They’re built from the ground up, building by building, street by street, neighborhood by neighborhood. They’re not procedurally generated, they shouldn’t be. That’s what makes great entertainment.”

Now the thing that sticks out for me here is he conflates procedural generation with generative AI, which are very two different things. It’s not the first time I’ve seen Zelnick present his strong anti genAI stance while also showing he doesn’t really understand AI in game development. It’s frustrating. That said, the comment does speak to what Rockstar has advocated for throughout their history, of crafting bespoke experiences that no other studio has the capacity - read: financial runway - to attempt.

That said, he did state in the same interview that Take-Two are running “hundreds of pilots and implementations” for generative AI adoption, which I have heard some rumblings of from my contacts. I suspect this will align with my expectations of a silent adoption of generative AI in processes across the sector while avoiding putting it in product. While GTA6 is arguably too big to fail, it’s not worth taking the risk of having generative AI sully the product if they can avoid it.

China’s Games Industry “Quietly Bankrolling Generative AI”

An article that cropped up over on the South China Morning Post (paywalled) that caught my eye was about the level of adoption and investment in generative AI that is coming from the Chinese games industry.

It’s not just that companies such as Tencent and miHoYo have utilised and implemented generative AI models in there games, such as the Deep Seek LLM being introduced into Game for Peace (the Chinese version of Playerunknown’s Battlegrounds [PUBG]) or AI voices in Tears of Themis (a popular romance detective series). But they’re also investing in start-ups to support them in their broader adoption of AI-enabled development.

Publicly trading start-ups such as Z.ai (an LLM company formerly known in the west as Ziphu AI) and MiniMax (arguably China’s equivalent of ElevenLabs) have seen significant investment from Tencent, miHoYo and 37wan. With these companies seeking to showcase the potential of these innovations in their products - and having the inside track on new developments.

We’re seeing a significant increase in enthusiasm and investment in generative AI from Asian markets in the past year. With countries such as South Korea and Japan also keen to show their efforts in exploring and investing in the technology. This is, in many respects, an attempt to have ‘homegrown’ AI rather than be reliant on the bulk of western AI models given they originate from the United States.

Chappell Roan’s Fortnite Collab is Celebrated for Hand-Crafted Art

Last week Fortnite’s new collab with the pop star Chappell Roan came to the platform, and was publicised courtesy of the trailer above. It’s a rather fantastic piece of animation as it blends between multiple styles and approaches. I mean I was impressed by it as someone who wouldn’t know a the artists work if it bit me in the ass - no disrespect to Roan, but I’m a metal guy, it’s just not my thing. As a promotional piece for a video game it’s very well done, and no doubt there’s a ton of easter eggs in this collab for fans to get excited about.

As NME reported, the promo has gone down very well with fans on social media, who are excited by having such large-scale commercial art showcasing human-crafted techniques rather than with generative AI.

It speaks to how audiences are so fed up of AI slop infecting every part of their commercial consumption, that going the other route and investing the time and energy into it will pay dividends - with NME mentioning that some fans of Roan are now downloading Fortnite to try it out as a result. Proof that, in some corners at least, divesting from generative AI in commercial product could pay dividends.

Of course it’s worth saying this comes just two months after some small-scale drama over whether Epic Games used generative AI assets in the launch of Fortnite Chapter 7.

Behind-the-Scenes Updates

Okay here we go. There’s a lot of stuff happening for us right now in the background, be it the 2026 conference, new case studies, Goal State, newsletter issues and more. So let’s dig into where we are with all of these and what to expect as a regular reader and fan of our work. It’s important to me that our audience can get a bit of an insight into what we’re doing, plus how we’re investing the funds we raise from our premium subscriptions. Okay, let’s do it!

General Update

Let’s start with an update on all things AI and Games and where we’re at. We started the year with a very long list of things to do, but also a sobering assessment of our finances. We’re in a position right now where we have enough cash to keep our wee enterprise running more or less until the end of the year. But in the meantime we need to bring in some more work in our consultancy and training business, plus work on fleshing out our revenue streams in others - this is why subscribing right here is a huge boost for us, it really does add up.

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• A plugin for the Snowdrop engine, Snowcap estimates performance for consoles in real-time using a training AI model.

• By gathering data on different performance configurations, Snowcap is game-agnostic and can adapt to changes in engine development.

• We hear from three developers behind the tool, and how it is being used throughout Ubisoft’s productions.

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Building games is difficult, we know this, but building games that are designed to be released on multiple platforms at once, well… that’s a whole other problem. As any developer will know, getting your game running smoothly on one platform is first part of a much longer battle, the next part is ensuring it runs as smoothly as possible on all of the other hardware you want to release it on.

And this brings us to Snowcap: a plugin built for Ubisoft’s Snowdrop - the game engine used to create titles such as The Division, Star Wars Outlaws, and Avatar Frontiers of Pandora - that uses AI to estimate performance on different consoles but without actually running them on device.

In an age where questions are quite rightfully being asked about the value of AI in game development, Snowcap is - for me at least - one of the coolest examples I’ve seen of how to use artificial intelligence to support game developers, because it’s helping not just speed up the process of porting to other platforms, but it’s helping developers anticipate and remove peformance issues before they even deploy the game on the target hardware.

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The Challenge of Cross-Platform Development

So to get into the weeds of this, it’s worth stressing the real problem that Snowcap is trying to solve, and that’s helping support cross-platform development. As you’ll know when AAA studios ship a new title, it typically is released on PC and consoles at the same time. If you’re porting to console - and assuming we’re focussed on the current hardware on the market in 2026 - then that means you’re working on the PlayStation 5, the PS5 Pro, the Xbox Series S and X, and potentially now the Nintendo Switch 2.

Each of these devices have very different performance profiles, as a result of their makeup of CPUs, memory, and GPU. Quite often when larger studios have a game in development they’ll have teams of devs focussed on optimising for each platform: addressing a memory issue on the PS5, dealing with the GPU performance on the Xbox Series S, and so on.

Speaking from my own experience of porting games to consoles, this is a long process: you work on the issue, make a new build of the game, deploy it to your devkit version of the console, and then begin to run profilers and other performance tests to ensure you don’t wind up with a bad review over on Digital Foundry.

Now this is all par for the course in game development, but as I said, it’s a long process. You can easily lose hours of development time re-building the game, deploying it to the hardware, and hooking up the profiling tools to check whether any incremental improvement has been made.

And this brings us to Snowcap and how Massive used AI to help make that process easier.

In the video above, Snowcap shows us the impact on performance on different platforms (Xbox Series S, X, and PlayStation 5) as a result of use of procedural environment decoration tools as well as a real-time shadow casting light source. Note the frame rate widget on the bottom left.

Snowcap is a plugin built for the Snowdrop engine that predicts in real-time the performance of a game in the engine’s editor based on a particular hardware profile and graphics presets. It achieves this using a trained machine learning model that is gathering a lot of data about how games perform in Snowdrop under a variety of conditions on the target hardware, and then the trained model can predict how well the current game in the editor would perform on that target hardware. As we can see in this demo footage provided to us by Ubisoft, this version of Snowcap is predicting performance for the PlayStation 5, Xbox Series S and Xbox Series X at the same time.

A Change in Philosophy

This is quite an impressive technical achievement, and we’ll dig into the weeds on that shortly, but it’s worth taking a moment to highlight that this is not just a technical innovation, but also something of a change in philosophy over how games are developed.

As Franck Maestre - a senior engineer on the engine - explained to us, the tool started development when Snowdrop was being upgraded for the current generation of consoles, taking into account how Ubisoft’s games are built and the changes in rendering techniques.

Franck Maestre:

The idea of Snowcap was born while we were upgrading Snowdrop for the next generation of platforms [PlayStation 5, Xbox Series S|X] and while we were upgrading the engine, we started discussions with technical artists, world builders, rendering guys: people working on those new platform and new capabilities; new rendering techniques, object materials etc.

We realized that the old process of setting up [art/world] budgets in a traditional way, could work at some extent. But as some rendering techniques are more expensive than others it was introducing a level of complexity to get a deterministic overview of the final performance. So we started investigating injecting in-engine metrics very, very, deep.

When you are defining world generation rules, object placements, avoidance, density, it’s difficult to estimate the resulting GPU workload of what you are doing, without creating builds and running tests. Also keep in mind [Snowdrop] is node-based. So technical artists, can actually edit the object materials properties using the graph, which means that our metrics should not be located at this level - the node level itself - but at the renderers’ underlying operations: the rendering pass, the amount of meshes, primitives, etc.

And in fact, it didn’t start out with the ambition to be AI-driven, it was only after an internal demo was shown around the studio, that Nikolay Stefanov - who is chief architect for Snowdrop and the Technical Director of the upcoming Tom Clancy’s The Division 3 - suggested that this diagnostic process to be modelled using AI. This led to David Renaudie - an Expert AI Scientist at Massive Entertainment - to join the Snowcap team and start exploring how to implement the machine learning model.

But while the technical part is critical, as I said it’s also about the change in approach to how games are being built. We heard from Elia Wrzesniewski, an associate production director on Snowdrop, explain how this is changing the way in which games are made in a more sensible way. Rather than letting performance issues creep into the game in ways that other automated tests will miss, only for them to be ironed out later. Snowcap helps the developers become more proactive in nature: identifying problems as they arise when changes are made to the game, and try to minimise any immediate performance issues that could emerge as they go.

Elia Wrzesniewski:

It’s really about prevention, so it’s a bit of a mindset shift. Just like you described, you want to ship the features, you, have a deadline to meet, so everybody’s focused on gameplay, on features, and sometimes it can create that kind of bottleneck on the optimization later in the production cycle.

And so here, yes, it’s, really the goal to prevent introducing - unintentionally - performance issues along the way, so you don’t create these bottlenecks.

On the Snowdrop pipeline, we had very natural adoption from game production. Nikolai Stefanov, the games he works on, are adopting this tech. People naturally see the benefits of using it.

And as Elia elaborated, by reducing the number of regular or basic performance issues being added to the game, it allows for the QA teams to focus much more on finding issues that arise from regular gameplay - as well as what happens when you just let players loose and start causing chaos.

How Snowdrop Works

For any studio wanting to use Snowcap in a given game, they setup their own project definition file, which defines the performance parameters and technical specifications of the game, and this helps determine the expected performance.

In order to work both in supporting developers in the moment, but also providing more accurate prediction over time, Snowcap operates in two modes. The first is of course the performance prediction mode that we described but also there is the data collection mode. After all, in order for it to predict the performance, it would be good to know how well the actual game you’re developing works in practice on the target hardware - especially as the game itself begins to evolve and change over time.

However, as described to me by the team, given so much of the data capture is focussed on the engine itself, Snowcap is largely game-agnostic, and instead is focussed more on the version and configuration of Snowdrop. This means that over time they can curate datasets reflective of specific permutations of SnowDrop based on the range of pipeline configurations and technical specifications that can be set.

David Renaudie:

It’s pretty simple. There is the hook in the engine that is going to be activated, on a basis that we decide for. So we sample the capture, because we cannot capture like, 60, 80, 100 FPS for all machines during their execution time.

It would be a huge volume of data but it would be also kind of useless because we don’t actually need all this volume of data.

So to build it, we gather millions of data points - and it’s really easy because we are at frame level - and we randomly sample them across a variety of hardware and presets. We aim to have a good distribution of this data, with all the targets that we want, to use this for our predictions. Then we use it to build a model for a given version of the engine.

Since we run play tests regularly - internal play tests are being done - we gather new data and we enrich the model or we retrain it and to make sure that we have no regression and, and so on and so forth.

And then when another games comes in, then we redo this exercise of making sure that we have the right metrics because some rendering techniques differ from game to game, and so sometimes we have to retrain specific models and sometimes we can just reuse one off the shelf that we already have.

But it’s more than just running under the hood without any guidance. As Elia explained, Snowcap can be configured for specific setups and pre-configured paths in the game. In fact if you recall way back in 2020 when we released a video about how Massive had built testing bots in Tom Clancy’s The Division 2, including autotesters that could run through the level based on a pre-built configuration set by the developers. Well now Snowcap can be attached to an autotest bot so that when it gives data reflective of a players normal playthrough, this can be processed into heatmaps and other reports that can give the developers a much clearer insight into which parts of the level have performan`ce issues and what might be the cause of it.

Wrzesniewski: We also can tweak the data tracking frequency, to run what we call a ‘camera performance’ or an ‘auto test’. And so basically what it means is that the camera moves, through the environment to automatically and generate heat maps. So it gives the developers a clear picture of how the level performs even before gameplay elements are added so you have an idea of how your vanilla level performs.

It’s a useful way to spot potential issues very early in the game’s development. To guide you to make smarter optimisation decisions right from the start and not too late.

An example of a recorded playtest, and the resulting heatmap data that is generated. Allowing developers to dig further into where issues are being found.

Visualisation

While we’re talking about Snowcap now in early 2026, the tool has existed in Snowdrop for some time now and has been adopted in most projects built in the engine in recent years. In fact I first heard about it in the summer of 2024 and in that presentation that was shown behind closed doors we saw its ability to track GPU performance in a complex jungle biome and it was highlighting two things.

• FPS Prediction: Predicting the frame rate based on the target resolution for the platform.

• Dynamic View Scaling: Predicting the level of dynamic view scaling that is being applied - which is when the game is adjusting the rendering resolution on the fly such that the framerate remains consistent. This is useful given each project defines not just the desired resolution and frame rate for a given platform, but the limits of the dynamic scaling as well.

Renaudie:
When we talk about GPU performance, it’s not unidimensional. There are actually two dimensions of it, and this is the entry point of the use of Snowcap in the editor.

But if the user will say, “Okay, I, I need to dig a little more into details here,” it’s possible to open it into more a detailed view where you can see the evolution of all the predictions in time and with more complex graph showing all the breakdown, all the details for the predictions

The user can also see the engine metrics that are being actually used to make the predictions. The user can have a look at what’s happening right now in the engine and have an idea of, “Hey, I have a predicted performance drop here. What should I be looking at? Oh, I see. There are too many lights, too many particles, too many somethings, and I have to act upon this.”

And this is, again, just a first level of, of entry, but we saw that it’s still helping and speeding up [the process].

Demo highlighting the change in dynamic view scale. Note this appears both in the Snowcap output window (the larger window), plus in the information widget on the bottom left. The outer (green) bar is the framerate, the inner (blue) bar is the ratio of view scaling.

But in addition to this, it can now show the engine metrics that are being used to make the predictions within the model. This is can be useful for developers to more readily diagnose why there is a performance issue in a particular area of the map. But it’s not just tracking aspects of the game that impact GPU performance - such as the number of meshes and tris within those meshes are being rendered - but it’s also tracking CPU objects as well courtesy of an integration with Snowdrops Performance Analytics Pipeline (PAP). Which is of great use given many CPU-bound aspects of the game can also potentially have GPU implications as well.

Maestre:

We integrated [PAP] through Snowcap for the CPU part. We have data coming from this pipeline that we can see in editor, and we can see if an entity performs in one place [versus another].

Because depending on the context, like say being in a wind corridor where a constant force is applied to the object, then the rigid body for the object will activate, and generally they activate on collision, - and this will cost.

This can also break the frame rate. Of course the GPU is the most important for us, ‘cause this is where we try to anticipate things, but you got the other one, which is the CPU this can also make the frame rate drop.

Wrzesniewski:
But we will still have edge cases, because these systems are so complex that even if you have a clean map. Even if everything is clean, there is still the probability that something goes wrong if the player, I don’t know, opens everything, or puts too many explosions in a specific location.

So, I think this also relieves some bandwidth for QA to really try to break the game and find these edge cases.

And the developers they can be more confident knowing, ‘okay, I did my level, I create my art and I know that, it should properly on the target console.’

But yeah, games are so complex today that, uh, even with, uh, these tools, uh, I think it’s still difficult to, we, we will have edge cases to, to find.

So of course, the one thing that is worth bringing up - and I think David would be heartbroken if we didn’t put this in the video - was just how big, how complex and expensive this model is.

Renaudie:
Something that I think will be interesting for your audience is to mention that we went the way of artificial neural networks, but we didn’t go in the deep neural network direction, because it wasn’t actually needed.

In the early experimentation phase, we tried with simple feedforward neural networks, and I’m gonna tell you just - without telling you about the architecture or anything - the size of it.

So you know today we are in a world where it’s the big race, you know, among the big actors of the biggest model in terms of billions of parameters and so on.

Snowcap model is running over a whopping 18,000 parameters. So 18k parameters, which is approximately making it big as 80 kilobytes.

That is still, you know, going very well in terms of accuracy for the prediction. We have like less than 4%, error rate, I think 3.33% is what we showed at the conference [the 2025 AI and Games Summer School]. Which is really good!

But it also runs in real time on the developer’s workstation without impacting the frame rate on said workstation and at frame level.

Both Snowcap, and our recent deep dive on MLMove, are a nice reminder that - contrary to the narrative surrounding AI these days - that we can often solve complex problems, with simple yet well considered solutions.

Renaudie:
You don’t need a complex ML model to solve even complex problems like this.

When you tackle the problem and say, “Oh wow, it’s really not, not simple, not something we can easily solve. Oh, we might need a big model.”

Well, sometimes not. I think here that the learning is also interesting. We can solve this type of problem with really lightweight models that just do the job, and it’s beautiful. Simple is beautiful.

Closing

It’s not often an idea comes along that catches me by surprise, by Snowcap is certainly one of them. A really innovative way to apply AI to support game developers in a sensible and practical way. Allowing developers to get on with their day to day job, but helping them find the issues in their work faster and more readily so that they can do their best work first time around rather than having to go back and fix everything later.

Plus it’s clear as the range of platform specifications grows with new platforms coming to market, tools such as this can help streamline the process of porting these games. Hey, if it means more of these running pretty slick on portable platforms, I’m all for it.

Special thanks to David, Elia, and Francke for sitting down to chat with us. Plus to David Antell and Joel Morange from the PR teams at Massive and Ubisoft for their support in making this happen - and for giving us permission to share some behind-the-scenes footage of the tool in action that you’ve seen throughout this piece.

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The AI and Games Newsletter brings concise and informative discussion on artificial intelligence for video games each and every week. Including industry news, innovative research, emerging trends, and our own exclusive editorial and reporting.

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Hello one and all, and welcome to . I hope you’ve all had a great week. We’ve been a little rough around the Thompson household as some sort of January cold/crud has hit us - sadly ruining much of our highly anticipated weekend. But hey, we’re on the mend, and things are looking up once more.

This week we’re catching up on some of the news in between our deeper dive issues - i.e. I’m writing a lot, just not all of it for this week’s edition!

Plus, I figured we better talk about one of the big headlines that from last week that we’ve already discussed in this here publication, that is perhaps the most ridiculous reaction to an AI announcement I’ve seen in recent memory.

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A Word From Our Sponsor: Lingotion!

We’re grateful once again to the good folks over at Lingotion, who are not just leading the way for legal and ethical AI acting in games, but sponsoring this weeks issue!

You may recall that we had a conversation back in December with Lingotion’s CEO and Founder Andreas Rodman about the company seeks to provide a legal and ethical framework for AI voice acting. Their aspiration is to give performers legal control and renumeration for their voices being adopted in AI models. You can find out more about Lingotion’s platform and their approach to supporting actors and performers through AI at lingotion.com

News Round-Up

Alrighty for this week, it’s a whole bunch of news stories worth catching up on. So let’s do it!

Nintendo Switch 2 Price May Increases Due to AI Demand For Memory

As discussed in our predictions issue last month, the price of consumer gaming is continuing to increase on account of AI datacentres and related hardware scooping up as much of the available capacity from DRAM manufacturing. This is already led to consumer-grade DRAM becoming increasingly expensive, and it’s expected that this will be the next in a long list of reasons as to why consoles will increase in price in 2026.

As reported by VGC, Nintendo president Shuntaro Furukawa recently responded to a question at the company’s latest financial reporting, stating that for now at least, the price of the Switch 2 will not be affected. However, there is a possibility that should the situation worsen, the company will assess the market and take action.

Stockpiling for Launch: It’s important to acknowledge the the Switch 2 didn’t suffer much from US tariffs as they began to wreak havoc in global trade last year. Though much of this stems from the fact that the console was delayed from an originally intended launch in 2024. This was in part to ensure the console had strong titles in its launch quarter such as Mario Kart World and Donkey Kong Bananza (my 2025 GOTY), but could also address consumer demand and minimise scalping. Hence millions of units were already shipped to the US before the tariffs were underway.

As such, they’re already well ahead in production and have plenty of stock available. Plus they have purchased a lot of the base materials needed for manufacturing the Switch 2 in advance. Though if AI continues to scoop up available memory, it is increasingly likely that all consoles will see a price increase by the end of the year.

Bitmagic Announces ‘Creator’ Platform - With ‘Idle Civ’ Demo Free to Play

Helsinki-based AI-first games company Bitmagic earlier this week unveiled their AI-driven game development platform ‘Bitmagic Creator’. The engine advertises its capability to build fully functional 3D games entirely from written prompts. Removing the need for users to engage with the ugly day-to-day of writing games, and have the AI prompting generate the necessary components you require.

To show this off, the company is offering up to 1000 EUR in credits to try out their tools in the Bitmagic Game Lab. But in addition, they showcased the tools capabilities with their latest effort to demake/clone existing games in their engine. Having already showcased that the engine can make clones of games such as Vampire Survivors, the team showcased ‘Idle Civ’ - their own version of Sid Meier’s Civilisation.

Impressive Results With Limited Scope: As always, it’s important to read between the lines of a lot of this rather than treating it at face value. I mean it’s important to stress that this engine is quite impressive. By training a Large Language Model (LLM) on the intricacies of the engine - and no doubt building the engine to allow for ease of crafting relevant code and art assets via the model - has allowed for quite a broad range of games to be built. That said, having tried some of them out, I’d consider it generous to suggest these demos are fun to play . They’re certainly functional and reflective of these games to some degree, but it’s a far cry from replacing the originals.

You can see the potential of something like this for aspiring developers and kids hooked into ecosystems like Roblox to craft their own experiences. I imagine Bitmagic has a profitable future in that arena should they find a way to monetise it successfully.

Sony Patented AI-Driven Podcasts?

Chris Scullion over at VGC caught a story about a recently approved patent for Sony that uses AI to create personalised podcasts on the PlayStation platform that feeds players updates on games they’re playing, what their friends are up to, and recommends games you haven’t played yet.

The patent - available to look at via the World Intellectual Property Organisation (WIPO) - details the use of an LLM combined with an image generator of some sort to craft a video podcast where you can watch hosts discuss what’s happening of late that’s worth your attention. The weird part of this being that the hosts of these podcasts may very well be the characters from Sony’s roster of characters across the PlayStation brand.

“Tony’s Hit a New High-Score on Sektori”: So this is really an elaborate and expensive way to summarise stuff that PlayStation’s ecosystem already tracks - leaderboards, game recommendations, purchase history, unlocked trophies, friend status updates, and new game updates pushed to release - wrapping it up in a bow for Nathan Drake or Kratos to read it out to you. I wonder if they ever got far enough to consider the implications of that given the performance actors involved in those characters? How about Vicar Amelia? That would make for some interesting viewing.

Actually, I wonder if they’ll let the podcast hosts respond to viewer feedback? I always wondered how Joel felt about ‘the Gamers’ failing to recognise the point of The Last of Us is that he’s a piece of shit human being…

Genie 3 Spooks Investors Who Don’t Understand How Games Are Made

Without a doubt the big story of last week was a new announcement about Google DeepMind’s Genie 3 model. As we’ve discussed previously, Genie is a ‘general-purpose world model’, meaning that it simulates an space within which agents (i.e. you) can take action. It then renders an image that simulates the world in which it exists within. By repeating this process of reading user input, then rendering an image, it creates the illusion of interactive video (games). Genie like other world models relies on vast quantities of video data in order to interpret, simulate, and regurgitate everything from real world scenarios to video games. I wonder where they could find all that video data…

Genie 3 has made headlines since it was announced last year, but given it’s an experimental research demo only a handful of people have tried it out - I did not but I know a few people that did. However, Genie 3 is now to try out provided you have the Google AI Ultra subscription, are over 18 years of age (I wonder why…) and are based in the US. The Ultra subscription will set you back $249.99/£234.99 a month.

So yeah, for the price of an original Nintendo Switch, you can access Genie 3 among other things (basically using Google’s AI models at their full capacity).

Once again, as I sit alternating between my ‘former AI researcher’ and ‘game developer’ hats, my opinion of Genie and other world models hasn’t changed. These are most certainly impressive AI developments, in that we can prompt a machine learning model to simulate a behaviour space and also render it in the style of something we have seen before: embracing style transfer, reproducing particular art styles, and more. But of course some corners of the internet think that the games industry is on a road to ruin courtesy of this technology - and sadly some of those people are involved in investing in it.

Impressive Tech With Limited Application

Wearing my ‘game dev’ hat, I still don’t see any value in this outside of some visualisation of how a piece of concept art might be playable, or using it for ideation within a game I have already built. The latter was what Microsoft Research did with their ‘Muse’ project that was announced last year. I wrote about this in a dedicated research digest issue, in that the project showcased how small edits to map designs could be simulated using a model such as this - but it of course relied on the game already existing, and hundreds of hours of footage of the game being played.

But outside of these limited edge cases, this is not a replacement for games in any meaningful sense. These models are incredibly expensive to host and deploy, are not capable of crafting new ideas - though as we’ll see are certainly capable of regurgitating existing ones - and more importantly struggle with consistency. I wrote up a case study episode on this last year in which we looked at a handful of these examples, and highlighted that as impressive as these things are they are incredibly limited, and are in no way, shape, or form, a viable alternative to conventional video game development and distribution. The Bitmagic story from earlier in this issue has much more weight to it by comparison, given it is implementing a game within a defined engine - meaning it has some sense of ground truth for maintaining consistent and reliable outputs.

Okay But Make Me Free Zelda

Of course it’s no surprise that as soon as this became accessible, what did everybody do? Make cheap clones of existing games, such as this delightful example from Twitter/X.

Again, technically impressive, but I’m sure Nintendo’s lawyers are having a lot of interesting conversations at the moment. It’s one thing to use video footage for training the model, it’s something else create a low-end reproduction of their game, right down to the animations and wind trails.

Tell Me You Don’t Know How Video Games Are Made…

So yeah, AI company makes big breakthrough, it’s made public to drive hype and influence stock price. Another day, another Doug. In fact it did little for Alphabet’s (i.e. Google’s) stock price. It went up less than 2% and that’s already been negated within a week. But this time around it had a much bigger impact - as reported by VGC among many other outlets - on various games companies who saw their stock drop anywhere from 5-10% after the announcement.

The worst offender was Unity, who saw their stock drop over 35% and then recover, but still with around a 25% reduction on this time last week. I don’t think it helped that their CEO Matthew Bromberg, posted a statement on Twitter/X stating that the company would “operationalise these advances”, by finding ways to build AI frameworks that could essentially parse and reproduce a world model’s output into the game engine. Not only does that sound like the company is conceding to world models being a replacement (they’re not), but it’s kind of the opposite of what most users of the engine want.

Once again we’re in a situation where an AI advance is being discussed and disseminated such that it has material impact on an industry despite said innovation not being of any real material use.

Sure, I think there is an argument to be said for world models to exist in some use cases, but considering the operational costs, repeated evidence of copyright infringement, failure to successfully reproduce assets from the same prompt, and the fundamental lack of contextual awareness and memory - did I mention Genie 3 only lets you ‘play’ for a minute at a time? - this is not going to have any broader value in the games industry anytime soon.

It’s been a rough news week huh?

Wrapping Up

A short and sweet issue this time around, but we’ll be back next week with a deep dive for next week’s edition. Plus, we have a brand new AI and Games case study launching this Friday both on the site and on YouTube. Looking forward to sharing it with you!

In the meantime, take care and I’ll be back!

• Intel’s Downgrading Consumer Output to Pursue More AI

• Ubisoft’s Recently Announced AI Push Is Also Politically Motivated

• South Korea’s AI Legislation is Kicking In

• We chat with Studio Atelico About Their Newly Announcement AI-Native Card Battler

The AI and Games Newsletter brings concise and informative discussion on artificial intelligence for video games each and every week. Including industry news, innovative research, emerging trends, and our own exclusive editorial and reporting.

Subscribe now

You can subscribe to and support AI and Games, with weekly editions appearing in your inbox. If you'd like to work with us on your own games projects, please check out our consulting services. To sponsor, please visit the dedicated sponsorship page.

Hello one and all and welcome to this week’s edition of . Now we have a quick apology to make given this is going out on Thursday, and not on our regular Wednesday. I hope this wasn’t too disruptive to your week, and that you survived not having us with you yesterday. Don’t worry, things will go back to normal next week.

The reason we got pushed back is the focus of today’s issue. Earlier this week Studio Atelico hosted a PR event for their new game Bobium Brawlers, a mobile game that is using Generative AI models running on device to create a monster battler game. Players can create their own monsters in real-time by designing them using natural language, and and then refine them into your very own king of ring.

This is the first game out of Studio Atelico, and the team were keen to highlight Brawlers will showcase how they aim to adopt generative AI in ethical ways in game productions. So we sat down for chat to discuss what that really means, and what the studios hopes are for this project.

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Announcements

A quick round-up of interesting things happening right here at :

Design Dive Returns for 2026

We published our first video of 2026 over on YouTube. Design Dive is back as we talk about Ninja Gaiden: Ragebound - one of my 2025 GOTY picks - and how it keeps the core difficulty brought on by enemy NPC encounters consistent and then provides players with a range of difficulty options. You can catch it as a video or in the written version below.

Thanks to Game Republic

Special thanks to Jamie Sefton and the team at Game Republic for having me present at their 2026 Trends and Opportunities event in Manchester yesterday. It was a great evening with a lot of cool presentations, and it was good fun catching up with new and familiar faces. My presentation was largely built on my predictions for 2026 newsletter from a few weeks back - with some additional flourishes from my Devcom talk last year. So yeah, if you just caught me presenting last night - welcome aboard - and would like to know more about many of the topics raised, check out the link below.

Oh also, speaking of Devcom, or Gamescom Dev as they call themselves now…

Keynote at Gamescom Dev Leadership Summit

I’m sure it was announced already on socials but I noticed there was a bit of a news push behind it earlier in the week, what with it appearing on GamesIndustry.biz and a few other places, but yes I’ll be presenting a keynote next month at the Gamescom Dev Leadership Summit in Lisbon. One of the big talking points in the press release was about talking about “AI disruption” in the industry, yeah… that’s me.

I have my work cut out for me, but it should be a fun event! Looking forward to it.

AI (and Games) in the News

A quick round-up of some headlines that crossed my path earlier this week.

AI Backlash in Games Garners Mainstream Attention

Short and sweet, The Washington Post wrote up a piece about recent AI backlash on everything from the failed Postal reboot, to Claire Obscure and Larian’s spectacular PR goofs. It further cements the idea that gamers are increasingly unhappy about AI slop creeping into their games, and that this is going to become a long-term issue that will become a louder and more consistent narrative in this year and beyond.

Ubisoft’s Restructuring Highlights Further Investment in (Generative) AI

Ubisoft’s announcement of significant restructuring - which includes closure of two studios, the cancellation of numerous projects (including the seemingly imminent remake of Prince of Persia: Sands of Time), a re-commitment to existing franchises, and potential layoffs - was undoubtedly the biggest story to drop last week.

One part of this story that received focus across numerous outlets, notably PC Gamer, was the company’s intent to double-down on their investments into Generative AI. To quote the announcement shared around last week:

"The new operating model will further empower the execution of the Group's strategy, centered on Open World Adventures and GaaS-native experiences, supported by targeted investments, deeper specialization, and cutting-edge technology, including accelerated investments behind player-facing Generative AI."

Now understandably, this reads rather out of touch as the company shuts down both Ubisoft Halifax in Canada and their offices in Stockholm, Sweden, plus opening a consultation to cut 200 jobs in their Paris HQ. It sucks, frankly, but I wanted to give a bit more context to the political motivations behind stuffing AI in the announcement.

If you’ve been following Ubisoft’s work in AI over the past 10 years, you’ll know they’re no stranger to R&D in the technology and how it can be employed in their productions. They have dozens of sites around the world focussed on exploring and experimenting with AI in their games - be it front facing or in production. More recently they’ve worked on a handful of Generative AI demos. Notably the NEO NPC and Teammates projects - both of which we’ve reported on - that are coming out of an R&D team in headed up in Paris. This isn’t ready for primetime yet, and I argue it probably won’t be for a couple of years yet: a point that the developers themselves acknowledged both times I was invited to try these demos.

So why the emphasis on AI in the announcement? Well for one thing I imagine appealing to investors at a time when stock is taking a hit wouldn’t hurt, but the bigger story is in political alignment. Ubisoft are heavily involved in the France 2030 project, a €54 billion investment by the French government to ensure businesses and broader society are ready to engage with and maximise utility of AI systems (by 2030). The initiative is but one part of the country’s much broader PIA: ‘Programme d’Investissements d’Avenir’ (i.e. Investments for the Future) programme to stimulate economic growth and innovation.

Ubisoft have already received some financial support from the French government towards their AI projects courtesy of France 2030, so it’s in their best interests to bang that drum.

Intel’s Committing to AI - and Gamers Will Suffer

As reported over on ArsTechnica, Intel profits have continued to slip in recent years, but only in the commercial side of their business. Meanwhile the AI side of things - providing chips to data centres - continues to see healthy growth year-on-year of around 5%.

But as discussed on Intel’s earnings call, they’re struggling to supply enough AI product. They simply cannot make enough chips to meet the demand coming from data centres and other AI companies. As such there is a good chance that this will mean a reduction in capacity for consumer-focussed product, and an increase in cost along the way - just as the new generation of Core Ultra Series 3 processors are expected to hit the market.

Intel have been an interesting beast in the past decade or so, leaning heavily into the data centre market having completely missed out on mobile, and with the consumer PC space largely levelling off. Data centres, and AI especially, are now critical to them maintaining the product margins they need in order to continue to invest in their own tools and technologies.

As an aside, I’ve been reading Chris Miller’s ‘Chip War’ recently, and so its been interesting to see all these recent pivots by chipmakers in context of their historical business practices.

How Will South Korea’s New AI Laws Impact the Games Industry?

Well hey, I haven’t mentioned the law here for a few weeks, but here’s an interesting one that slipped past me. Earlier this week South Korea’s Framework Act on the Development of Artificial Intelligence and Establishment of Trust came into effect. As reported this does have some key elements that games studios both in South Korea and beyond have to take into consideration. Most notably the labelling of AI-generated content in games, and how this will apply to any game from any studio should they wish to ship in South Korea.

I need to dig into this some more, alongside the responses to the AI consultation by the UK government in a future issue.

Studio Atelico Announce ‘Bobium Brawlers’, the Ethically-Built AI Card Battler

Earlier this week, Studio Atelico - an AI-first games studio founded by former developers at Uber, Meta, and Sega, announced Bobium Brawlers, a turn-based card battler launching on iOS where players get to design their own monsters to do battle against other players. The trick behind it, is that players use generative models to create their monsters, both in terms of their name, description, attacks as well as their visual look and overall style.

If you're a regular reader, you might recognise the studio given they presented at the AI and Games Conference last year about the work they’ve been doing in building the Atelico AI engine, with a focus on small generative models that can run local on device - meaning they don’t run in the cloud and require an internet connection - but also with an emphasis on ensuring they are built ethically. Sadly we’re still editing up the talks, but we hope to share it with you in the coming months.

Having previously worked on the Generative Agent Realtime Playground (GARP), which sought to reproduce the Stanford AI ‘sims-like’ generative agents project on device and without the use of cloud-based AI, Bobium Brawlers is Atelico’s first real push into shipping their own game. It’s also a real test of their overall philosophy, both in terms of using these technologies to make something interesting for mobile platforms, but also in trying to set the tone for ethical AI adoption that could resonate with players. So I sat down to chat with studio CEO and co-founder Piero Molino to talk about the team’s experiences, and to go a little deeper on what to expect when the game launches on iOS in the coming months.

Finding the Fun

The game’s card battling mechanics struck me as a real deviation from the GARP project we’ve previously seen come out of the studio. So it was interesting to me to see how they’d transitioned from one concept to the other. As Molino explained, it was a process of finding game mechanics that could both utilise the foundation of their AI engine, while also providing a sense of fun in exploiting what the models could generate for them.

“Very quickly, it became clear that the most fun part of the experience was creation.” Resulting in them leaning into the idea of giving players the opportunity to craft weird and wacky monstrosities, with the aesthetic pulling on the likes of Futurama and Rick and Morty, and even Mega Man.

But of course the game needs to have something of substance underneath it, and it’s notable that Bobium Brawlers is building these AI-generated characters within an established card-battling system designed by the team at Atelico. “[With GARP] the joy was entirely driven by emergent character behaviour”, but this time around the team wanted to explore how you can build using a generative model that is constrained by an existing gameplay system and architecture.

“This introduces a much trickier balance” as Molino explained, given the game mechanics are constrained by a domain-specific language (DSL) that reinforces the core logic of the game. Both in terms of how the player’s input influences the creation of the brawlers, but also the constraints that impact what is attainable given both the player’s current resources, and the underlying balance of the game’s design.

Building Thematically Sound Brawlers

While the main push in the announcement was about the ability to create your own brawler that takes on your ideas in its metadata and aesthetic (which we’ll come to in a moment), for me I was really interested in how it influences gameplay. After all we know that an LLM can be used to tell stories and summarise or describe things as verbose or as succinct as we’d like, but how are they interfacing that with the underlying rules of the game?

Brawling Within Constraints

As Molino explained, the Studio has been learning that “finding the right spot on the spectrum between ‘the LLM decides everything’ and ‘every detail is hand-designed’ is the central challenge of building games with generative mechanics.” My first thought was the studio needs to be feeding a lot of information to the LLM that designs each battler, such that it retains the overall design and balance of the systems they’re playing in. Otherwise the LLM will simply build a card without understanding the context of how it fits into the game’s overall meta.

The core of Bobium Brawlers battle system is built by the dev team themselves. Not just with the aforementioned DSL language they’ve built to define brawlers, but also they have a complete bible of how the game operates that is fed into the LLM when it runs. This includes the rules of the game, handcrafted examples of cards that make sense in the game world, and a series of archetypes evocative of decks that players might craft. The resulting cards are then output in the DSL which means they can immediately be parsed and interpreted in-game for use.

But the LLM is doing more than just the surface-level information of the characters name and personality. It’s also deciding how the character is designed for combat. Like similar games in the genre, the attack system relies on mana for using specific cards, with different attack types using different types of mana. The system both from its own internal musings and the players inputs, will generate attacks that are thematically relevant to a given character - complete with appropriate mana usage and status effects. Hence should the player asked for a pyromancer mummy, the resulting output has most of the attacks be fire-themed, deal fire damage, and require the appropriate mana.

This concept is expanded further, with the player’s descriptions often influencing the attack design itself. Asking for a “forgetful tortoise” will lean towards more defensive and tank-like gameplay styles, while a “wild wolverine” will be fast and aggressive.

Balancing for the Long-Term

Naturally the game designer in me wondered just how far down the rabbit hole the team had evaluated this. Feeding the design and balancing rules to the LLM is one thing, but playtesting it such that you can guarantee that players don’t discover a game-breaking loophole or that the meta doesn’t stagnate within a few generations of monster evolution is something else entirely.

At this time the team has ran a statistical evaluation of the model and corresponding outputs that refined the design decisions of the overall game blueprint. Only time will tell how well this fares, or how fun it remains, when the game is put into hands of players.

Deploying (Generative) AI on Mobile

While Bobium Brawlers isn’t the first AI-native game to cross our paths, given we’ve talked about everything from Retail Mage to Millenium Whisper, AI2U, InZoi, Dead Meat and more this past year on the newsletter, it is doing something that stands out. Some of those games were moving towards on-device deployment of AI models, but they were all destined for PC and Steam. But Studio Atelico decided to launch this game on iOS: a completely different and equally demanding market, albeit with a more streamlined and consistent hardware profile.

The studio is doubling-down on this approach, given they see on-device as means to showcase the potential to use Generative AI more responsibly, describing the approach as “more private, and more environmentally friendly” and giving users “greater control over their data”.

But on top of this, there are also pragmatic business reasons, given hosting a game like this on a server and having it repeatedly poll the LLM would be incredibly expensive. This why I’ve repeatedly stated in my predictions issues that on-device is going to flourish, because it’s the only way to make these generative models economically viable in a game production.

But this brings with it another challenge, given the models have to be smaller, and in doing so often begins to impact quality. This was a point that was raised during our conversation with Meaning Machine late last year as they try to bring Dead Meat to market.

Given the experience of the engineers at Studio Atelico, the process of fine-tuning the models to be smaller was one they were prepared for. For them it was about ensuring the models are adapted specifically to suite the game while ensuring it retains their desired quality.

Right now the models fit within roughly 2GB of RAM when being used on the device -for context iPhones have had at least 4GB of RAM since the iPhone 12 in 2020, with the base iPhone 17 from 2025 running on 8GB. This model can then generate creatures within tens of seconds, which Molino feels is “a reasonable compromise”. Right now RAM is the main constraint the team are worried about, and our experimenting with keeping the base installation of the game smaller by having models download and update as you play.

Ethically Source AI Models

Since I crossed paths with Piero and the Atelico team last summer, the one thing about their business that’s been reaffirmed time and time again is that the studio is focussed on ethical AI adoption. Either using existing AI models that are derived from fully licensed datasets, or building their own using their own data. The studio went so far as to outline their ethos in a blog post last year in part as a response to Rez Graham’s “Human Cost of Generative AI” presentation at GDC 2025 - a talk that leans on a comment I made at the GDC roundtables in 2024.

It was certainly amusing given I didn’t anticipate it, and I was sitting in the front row.

So when Bobium Brawlers was unveiled, a big talking point from the studio was their desire to do this as ethically as possible, and it was important for me to dig into what that meant and taking them to task. Given I think we can see studios wax about how ethical they are provided it fits within some defined capitalist framework - see my piece on Arc Raiders from late last year.

But unlike GARP, which only relied on an LLM, this new project is also generating the art assets for each card. Hence it’s now also dealing with art generation as well, and the challenges involved in that process.

For Molino, it was important to “demonstrate that [Generative] AI can be used in games in a way that feels morally responsible and sustainable.” The on-device aspect is but one part of a larger approach which influences using base often from explicitly licensed data, fine-tuning the models using their own data, and remuneration and royalties for artists who contribute to the art generation process.

Artists who come on board are providing a contract the “defines exactly how the art will be used, and any limitations based on the artist’s preferences”. Right now they have only worked with a couple of artists, but the goal is to open source the contract in the future as an example of how to approach making this framework equitable.

The game’s rather colourful art style has required a more structured approach given the team wants to ensure that the art assets are consistent between monsters. With art director Mollie Boorman defining the overall visual style that would not only lead to the initial training data, but also give other artists direction on how to build within the game’s established universe. Encouraging artists to make lots of examples of different types of objects, animals, robots, and otherwise that would later influence the generation. With Molino stating they could start getting reasonable results with just a few dozen images in relevant categories.

Perhaps one of the most important things in the art, is that they lean into the quirks of art generators. As we know, AI art generators are prone to be illogical and inconsistent, with extra limbs, bonus fingers, and a lack of understanding of basic human anatomy. However, given the cartoony style of the art, combined with the rather wacky humour, it feels more like part of the charm. Molino stated that creature designer Jose Luna “has genuinely enjoyed seeing his style emerge in so many unexpected and wacky ways.”

Wrapping Up

That’s us for this week. Quite a meaty issue if I do say so myself. Thanks for sticking with us to the end, and big thanks to Piero Molino, Chris Olson and the team at Studio Atelico for giving us a behind-the-scenes look at Bobium Brawlers. We’ll be keeping an eye on it when it comes to market on iOS.

We’ll be back on Wednesday next week as we return to our regular release schedule. Meaning I better get started writing the next edition already. Can’t stop, won’t stop, etc. etc.

Take care folks!

Design Dive is our dedicated series on the intersection of AI with game design. Sometimes we dig deep into the technical challenges, other times it’s all about finding how it brings the fun to your favourite games.

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2025 brought not just another lap around the sun, but the latest entry in the never-ending conversation surrounding difficulty in video games. Now yes, for the most this was brought on by the release of Hollow Knight: Silksong, but I’ll be honest I still haven’t played the first one yet.

But what I did play was Ninja Gaiden: Ragebound! Developed by Spanish studio The Game Kitchen - known for the Blasphemous series - and published by Dotemu, this hack’n’slash platformer harks back to the classic entries of the series on the Nintendo Entertainment System and is the first 2D game in the franchise in 30 years. It’s fast paced, requires precision in movement and combat, and while not as challenging as the originals, it is a worthy addition to (Koei-)Tecmo’s beloved franchise.

But what is perhaps the best part about Ragebound, is that it not only provides a challenge worthy of classic Ninja Gaiden titles for more seasoned players, while also being remarkably accessible to newcomers, and it largely comes down to how enemy AI sits in the mix.

The 5 Things Ragebound Gets Right

There are five key elements of Ragebound that make it work as well as it does:

• Normal difficult is tough, but not overwhelmingly so.

• The suite of accessibility features help give newcomers a means to get in and enjoy the game.

• Talismans if you want to remove friction, or increase the challenge.

• The secret hard difficulty is where things ramp up.

• And it’s all driven largely by an element of fairness that helps keep the game consistent.

So let’s break this down a bit more, by starting with the last point on this list. Given it’s perhaps the most critical.

1. An Element of Fairness

Let’s not sugar coat it, Ragebound can be pretty challenging at times. But while the game is an homage to the Ninja Gaiden games of old, it finds ways to embrace the challenge of those older titles, but without relying on many of the punishing aspects of the originals. The NES Ninja Gaiden had awkward fallback from taking damage alongside short invincibility windows, combined with level design where the fallback would often drop you into pits, and enemies that would repeatedly re-spawn off screen. It forced players to repeatedly tackle sequences such that rote memorisation was more important than skill in order to progress successfully.

Ragebound avoids all of this, and focusses instead of having you face off against waves of enemies in fixed encounters, and while you have to pay close attention to which archetypes are in play, what auras they present, and sometimes even the order in which you should eliminate them, it does so in a manner that keeps the overall ‘fairness’ of the game’s design consistent. Encounters are largely deterministic, meaning we can guarantee how they will go down each time, and as such while you might struggle on the first go around, you can learn from this experience to try again in a subsequent attempt.

2. Normal is Tough, But Consistent

While subtle, it's this element of fairness that is the cornerstone of the entire difficulty scaling of Ninja Gaiden: Ragebound. Sure, it means that this game is ultimately nowhere near as hard as many of the originals, but I think that’s to the game’s benefit: it helps establish the rules of play, and how encounters are designed. From there the player can begin to understand how each NPC archetype works, and the challenges that are introduced when they are presented in specific configurations.

This core balance means that the game can retain a sense of challenge that players can understand and more readily learn to overcome. And in turn the game can begin to increase the pressure, creating more complex encounters and introducing new enemy types. Each enemy presents a new ingredient to each encounter’s recipe, and one addition or removal can fundamentally change how you might approach one group of enemies versus another. The game expects you to learn how these combinations mix, and also how their placement combined with level geometry will make for a more challenging sequence.

While the levels are increasingly challenging, the push from survival into mastery often comes from the rankings. With each level having the player score anywhere from a D rank up to S. The ranking system encourages you to go back and replay levels to learn their patterns, not just to ensure you take out enemies quickly, but avoid taking damage, maintain your combo counter, complete challenges and grab all the collectables throughout each level.

3. The Accessibility Features

While focussing on the ranking system is bound to keep many a player busy, getting to grips with the core of the game may still prove a challenge for novice players, or for those who have disabilities that may well prevent them from engaging at the level of dexterity Ragebound requires - and this leads us to the accessibility settings. Turning on the assist modes in Ninja Gaiden Ragebound allows you to modify a bunch of the core gameplay to suit your needs. Be it reducing the game speed to 50%, removing any and all damage received, removing knockback, and increasing hypercharge durations, it all works to support the core experience of the game.

Perhaps the one aspect of this that people will and no doubt have complained about, is that the assist mode does not affect skill ranking or progression. As such, you can enable these settings as you aim for the loftiest of challenges the game presents you with. Which hey, that’s a good thing. Because for every person who might cheese these settings to save themselves time, for others it’s a vital feature that enables them to enjoy everything the game has to offer.

4. Talismans Increase and Decrease the Challenge As a Choice

In addition to the assist modes, the game’s Talisman unlocks work to both make your life easier, and if you wish, make it harder. By finding Scarab collectables throughout your playthrough you can then purchase and equip up to two Talismans be it to change how the game plays to help you progress and complete the level, but equally to remove features you rely on when trying to progress.

This is a really neat feature, given it fits into my earlier point of allowing for players to slowly build up skill and gradually develop their understanding of the game. You’ll often start out by equipping Talismans such as Bloody Frenzy which recovers health when building a combo, Traveller’s Blessing for resetting health at checkpoints, Last Stance which increases damage at low health, and Ghost Shell to increase your invincibility duration after taking a hit. These act much like stabilisers on a bike, in that over time you won’t need them anymore, and you start to learn how to play the game without them. Ultimately it helps remove a lot of the earlier friction you might experience until your skills adapt.

And it’s expected that ultimately you will eventually do without them, given there are another set of Talismans designed to make the game harder. Scarcity removes health orbs, Perilousness triples damage received, Unworthy removes health recovery at checkpoints, and No Rest for the Wicker removes checkpoints entirely. Applying each of these nerfs, essentially removing safety nets, also increases your overall end-level rank by one. Meaning you can push yourself to hit the S rank on every level you play through by equipping them.

5. Hard Mode is Where It Shines

All of this then comes to a head as you complete the game. Defeating the game on normal mode unlocks a harder difficulty, which does a lot more than increase the damage dealt by enemy NPCs. It also changes the makeup of some encounters, and in some instances the layout of the level itself. It builds on what players have already developed in understanding how the game works, and how to excel in dodging attacks while also timing their own. Presenting you with essentially a sort of Director’s Cut of the original game that is attuned to your new skill level.

And on top of all of this, this is where players can aim for the S++ rank, by stacking the Talismans on top of the harder difficulty you can now push to achieve the highest rank possible in the game, and prove your overall mastery. Personally, that isn’t for me, but it is very much in keeping with lineage of Ninja Gaiden as a franchise, and allows for players to push themselves to that peak of their skill.

Self-Serve Difficulty

The sort of ‘self-serve’ challenge of Ninja Gaiden Ragebound works because it means that the games overall difficulty curve is malleable, allowing players to customise the game enough to allow them to stay in the flow. To build up their skills and face the ever increasing difficulty. It’s a smart approach that ensures that while the game sticks to the principles the series is built upon - even if it isn’t as hard as its 80s contemporaries - it provides players the option to dictate how the game ramps down, or up, without reaching a point of frustration.

• Maxon’s PR Aren’t Sure if Their New AI Tool is Even Real.

• Valve’s Updated AI Disclosure is a Step Backwards.

• How Surveys on AI Adoption in Games Never Tell the Full Story

The AI and Games Newsletter brings concise and informative discussion on artificial intelligence for video games each and every week. Including industry news, innovative research, emerging trends, and our own exclusive editorial and reporting.

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Hello one and all and welcome back to this weeks edition of . This week we’re catching up on a topic voted for by readers last quarter on the AI surveys. I dig into some of the results coming out of surveys from Google, AWS, GDC and more and give a breakdown of what’s nonsense, what needs taken with a pinch of salt, and the things to keep an eye out for when another survey headline crosses your internet feed.

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News Round-Up

A quick summary of some headlines that cropped up in the past week.

Maxon Announces a new AI Tool at CES, Angering Consumers, and Confusing Staff

So this story dropped a week or so ago, but I heard a wee bit of inside gossip on it worth sharing. As discussed over at 80LV, Maxon - owners of 3D modelling tool ZBrush and animation tool Cinema4D - announced a new AI tool at CES 2026 for ZBrush known as ‘Maxon Digital Twin’. This tool promised to help turn any “3D product model into a marketing-ready asset”. So in theory you could take a CAD model of a product, and it would render it complete with appropriate lighting and backgrounds. Saving you the need to do photo shoots and the like for promotional works by building the object as a physical device/object/thing. Or of course getting a human to render it for you in an industry standard tool.

Now I say all this but this is rather speculative, given outside of a handful of posts on Twitter/X, it wasn’t exactly clear what Digital Twin was going to do. They announced it at CES, but with no demonstration on the show floor, just a promo video. But the announcement alone was enough to anger much of the ZBrush community, frustrated at AI being slapped into a tool with many outstanding issues and feature requests that users have asked to be addressed. Since then the original Twitter/X post has been taken down, and the website now implies that it’s a standalone product and not part of ZBrush.

What I learned from folks familiar with the situation was that a lot of people involved in the PR and marketing for Maxon were caught off guard by this announcement. Not only had they not been briefed that Digital Twin was a thing, but didn’t know what it is, what it does, or how it worked - which as you can imagine in their line of work is… a headache. People on the stand at CES were contacting the PR teams asking for guidance given the demo video (shown above) left more questions than answers. According to Maxon, Digital Twin is still in development. Whether it actually exists, is something we’ll find out in due course.

Valve Updates Steam’s AI Disclosure the Wrong Way

Last week industry commentator Simon Carless posted on LinkedIn stating that Valve’s AI disclosures as part of a games submission process on Steam has been updated. The form now removes the need to disclose use of AI tools that help make developers more efficient. The question on use of generative articiial intelligence now has the following description:

We are aware that many modern game development environments have Al powered tools built into them. Efficiency gains through the use of these tools is not the focus of this section. Instead, it is concerned with the use of Al in creating content that ships with your game, and is consumed by players. This includes content such as artwork, sound, narrative, localization, etc.

Does this game use generative artificial intelligence to generate content for the game, either pre-rendered or live-generated? This includes the game itself, the store page, and any Steam community assets or marketing materials.

Now contrary to most of the comments on this update on Carless’ LinkedIn post, I think this is a terrible idea for a number of reasons:

1. There is a baked assumption here that the person submitting the game understands the distinction between AI, machine learning, and generative AI, and to this day I find a lot of developers, much less players, are not in a position to answer this correctly.

   1. It would really help at this point if Valve provided a clearly written statement on their distinction of AI/ML/GenAI for users to understand.

2. Removing this need to qualify ‘AI powered tools’ in game engines absolves developers of actually understanding what AI tools - if any - they’re deploying in their production. Naturally for a professional studio this won’t be a problem (identifying tools and their risks is a key part of pre-production), but for many indies and students this is a problem as they may not be aware of the tools they used in larger commercial products (say Unity, or Adobe Photoshop) and the implications that could have for them.

   1. Furthermore, Valve make zero effort to contextualise what they mean by this. What are these AI tools they’re referring to? Give us examples of what might be considered exempt.

3. Stating that such tools only focus on “efficiency gains” when they’re interested in “[content] consumed by players” is disingenuous, given it can be argued that AI-generated code - which constructs the game itself - crafts the content consumed by the player. So this removes the need for developers to acknowledge use of code assistance tools, or whether they just vibe-coded the whole project.

   1. It is stated above that part of the “content” is ‘the game itself’, but the question deliberately avoids providing ‘code’ as an example. Again, this is rather ambiguous.

4. It’s a willingness to avoid addressing the underlying issues of whether these ‘efficiency tools’ were built on copyright infringing materials. Sure you might have used a code generation tool, but where did it come from and why?

   1. Yes the submission process states that your work is still subject to content rules - meaning don’t violate copyright law - but then efficiency tools are exempt from that? So a code generation tool that uses stolen assets is fair game? Bear in mind the GitHub Copilot class action lawsuit is still ongoing (though looks likely to be dismissed).

   2. Also yes there is an implication that ‘AI tools’ mentioned here are not generative AI tools. But fun fact kids: you can still use AI to infringe on the rights of others without a generative model.

I’ve said it before, I’ll say it again. As consumers become increasingly more savvy to how different forms of AI work - and the implications it has in creative industries - they want more clarification on where and how these technologies are being used. Similarly, it’s important developers are aware of the implications of these technologies and take responsibility for that. All-in-all, this is a step backwards.

It strikes me this is an effort to walk back Steam’s own AI disclosures to avoid dealing with the granularity of the issue - which sadly doesn’t surprise me in the slightest. Another disappointing if unsurprising effort from Valve.

Total War: Warhammer 40k breaks 1 million Steam Wishlists

An impressive achievement for a game only announced back in December. We’ll be keen to see how the AI shapes up. No release date has been set by developers Creative Assembly, but fingers crossed we see it in 2026.

Our Main Story: Digging Into AI Surveys

We exist in a world where both really interesting and engaging work that is occurring in AI for game development, while equally many games studios don’t use it in any real way whatsoever. Given the current hype-laden landscape, it has meant there are broader efforts to advocate for and promote the narrative that AI is everywhere, everyone is using it, and if you’re not already then you’re behind the curve.

The games industry is fertile ground for this agenda. The sector has used AI in various forms now for decades. Combine this with the significant investment in new AI start-ups whose technologies promise to address the sectors fears over audience retention, faster content production, cheaper development, and overall stronger pathways to success. As we’ve discussed at length on this newsletter there is some truth to this, but we’re far from a point where there is clear consensus on what works and what doesn’t, be it from a fiscal, practical, or ethical standpoint.

As such, we’ve had a whole batch of surveys come out on in the past year telling us what the lay of the land is like: what percentage of developers are using AI, what they’re using it for, the demographics of users and much more besides. But more often than not there’s a bit of shady behaviour hiding within as numbers are fudged to suit the narrative.

But the truth is often hidden in the details. So I wanted to take a moment to look at some surveys, and discuss the common tactics adopted to help support particular narratives. In the hope that you, the reader, can more readily catch these issues if and when they’re presented to you. Including:

• How the obfuscation of the term ‘AI’ helps support narratives.

• Sample sizes and demographics seldom reflect the industry.

• Understanding importance of who is responding to surveys.

• How question design influences narrative.

Read more

• With over 4000 AI tagged games in 2025, expect 1-in-3 games on Steam to have AI disclosures in 2026.

• Microsoft’s push for AI dominance will only make Xbox suffer.

• Nobody is going to like the UK’s approach to AI legislation.

The AI and Games Newsletter brings concise and informative discussion on artificial intelligence for video games each and every week. Plus summarising all of our content released across various channels, like our YouTube videos and in-person events like the AI and Games Conference.

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Hello one and all and welcome to . For this week’s edition, now that I’m all caught up with my regular day job, I figured let’s dig into some predictions for the year ahead. What am I expecting to occur throughout the next 12 months - both good and bad - that will impact the video games industry its adoption of artificial intelligence technology.

If you were following the newsletter this time last year, I kicked off the year with seven predictions that I was largely on point with. This year I decided to be a little more specific, particularly after we dug into a lot of big conversation points throughout 2025. So it’ll be interesting to see how well I polished the crystal ball for this years antics.

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2025 Prediction Scorecard

So as mentioned above, I had a whole list of stuff I covered this time last year, and I figured before we go any further, let’s quickly recount my thoughts in early 2025 and whether I was right on the money.

• A Make or Break Year for AAA: This was rather vague, but I still think my point of high profile failures and lacklustre response was largely accurate - I’ll give myself half a point. The recently reported top 10 games of 2025 on PlayStation being the exact same as 2024 highlights that new releases seldom hold the attention of players in the same way as big live service games that now deliver regular incremental updates.

• Layoffs will Continue: Yup. I hated being right about that one. Survive ‘til ‘25 always struck me as a rather naïve perspective given it feels like we’re still suffering from a variety of aftershocks from poor decision making at the turn of the decade.

• NVIDIA’s Push Into Full-Fledged AI Company: An easy point on my end. The most valuable company in the world is making the bulk of its money off AI, but it still sells graphics cards too!

• More AI Demos, More Start-Ups, More Local Inferencing: While the market isn’t throwing around free money as much as it was, there are still plenty of AI start-ups cropping up left and right. Plus as we saw at the AI and Games Conference back in November, on-device deployment of machine learning and generative models is very much the driving conversation as companies (finally) realise that cloud-driven AI deployment is simply not practical in many use cases.

• AI-Native Games Will Start to Ship, But Mostly Indie: Yeah there’s been a bunch of these titles - where generative AI is the driving part of the experience - on Steam, and virtually all of them are indie. While I mentioned games like 1001 Nights and Dead Meat last year, neither of those shipped. But still we saw games like AI2U: With You ‘Til The End in January, Millennium Whisper in February, all the way through to Vaudeville in November.

• Someone, Somewhere, Is Going to Put Their Foot in It: Oh where do I start with this one? Nvidia’s whitewashing neural face rendering? Activision using generative art in Black Ops 7? The pointless use of AI voice models in Arc Raiders? Don’t even get me started on that Darth Vader in Fortnite thing. Though it seems nowadays that the easiest way to get away with making mistakes like this is to simply push forward, ignore it, and hope that players stop grumbling.

• Platform Holders Will Begin to Dictate Policy: Well, egg on my face. I got this one completely wrong. Nobody did anything of substance here, and as a result all of the storefronts are now littered with even more slop than ever before. I point I dug into further in the middle of last year.

Okay, so all-in-all, I scored 5.5/7. Not bad at all! Admittedly I think some of these were rather low hanging fruit. So I figured for this year, why not be a little more ambitious?

Predictions for 2026

Okay, I worked to distil my predictions for this year into 10 main topics, and there are even some sub-predictions in there as well. I figured last year I was a little sceptical about a lot of things happening in and around AI, and sadly I think this year I’m even more gloom’n’doom. Because for all of the great innovations that are happening right now - that I am of course going to keep on top of and report to you - the state of the industry combined with another year of rampant over-enthusiasm for mediocre AI tools will mean we’re going to be dealing with a lot of these big issues going forward.

#1 AI-Tagged Steam Games Will Explode

Let’s start by returning to the AI disclosures on Steam. Last year I reported that by the middle of 2025 there were over 2000 games on steam that had reported their AI disclosure. By the end of 2025, that number reached 4311: a 100% increase on 2024 when Valve’s policy became more formalised, and a 4750% increase since Steam started monitoring AI use on the store in 2023. In addition, at the time of writing we are well on our way to having the total for 2026 exceed all of 2023 - and it’s only the middle of January.

20,004 games were released on Steam in 2025, an 8% increase on 2024, and a 42% increase on 2023. Meaning 22% of all games released on Steam in 2025 ticked yes on the AI content disclosure. While I expect the total number of games in 2026 to increase on last year by around 8-10%, I expect far more low-quality games to continue to use AI tools for art and code, to a point that I’m willing to make two predictions:

1. At least 7000 titles will have the AI content disclosure in 2026.

2. One third of all games released on Steam in 2026 will have AI content disclosed.

Is this something I’m excited by? Not really. As I discussed in my article on the subject last year, the broader adoption of generative AI in game development has led to a fundamental problem of AI shovelware flooding storefronts on everywhere from Steam to PlayStation, Xbox and the Nintendo eShop. A problem of quality control that makes it harder for small indies making decent product to stand out in the crowd.

#2 Valve Will De-Emphasise the AI Disclosure on Steam

While I believe thousands of games will submit the AI content disclosure, I also think Steam’s owners Valve will de-emphasise it some degree. In fact it was interesting to see George Osborn made a similar comment over on his VGIM predictions last week, but I don’t quite agree with him 100%.

In his issue George states that the AI content disclosure on Steam will be removed entirely, rather than going for a smarter solution of having more granularity in their submissions process - a point I have argued for several times.

While I agree Valve would rather do away with it, I suspect they will keep it around given the likes of EU AI Act has transparency obligations for when software users are interacting with an AI system. Meanwhile generative AI providers (and users) must have a way of identifying what outputs are artificial. So I suspect for legal reasons it will be useful as a storefront to still have the AI disclosures as part of Steam’s submission process. At least they will have a record of which titles fall under this should lawmakers in Brussels start having a look at what Valve is up to.

That said, I think they’ll go the route of de-emphasising the disclosure on store pages, potentially removing them entirely. While this will no doubt anger many a gamer who actively hunt down and call out the slop filling up the storefront, Valve will be more interested in placating the bigger players in the space. Larger AAA studios who are continuing to explore generative technologies, as their adoption is becoming more pervasive - notably in non-creative aspects of game development. Larger companies will see it as an issue they don’t want to face blowback from, and so minimising the disclosure from the consumer-facing side of Steam will be considered.

#3 AAA Studios Will (Quietly) Double-Down on Gen AI

2025 was the year consumers began to notice how generative AI had crept into game production. But while the Steam numbers are largely in relation to indies, there was a significant increase in AAA studios serving nothingburger statements on the potential of the technology alongside use of generative AI for often incidental aspects of their games: ranging from in-game cosmetics, to loading screens, background text, voice work, and much more besides. This has received significant - if inconsistent - backlash from gamers. But as discussed recently, I sincerely doubt outcry from potential customers will stop AAA studios desperate to cut costs to abandon the technology.

It’s important I take a moment to state, we need to delineate between using generative AI to support game production and the more commonly recognised use of the technology for in-game assets or the AI-native gameplay concept.

Projects such such as EA’s AgentMerge project to keep on top of JIRA tickets, or using multi-modal models for QA purposes, or Activision’s multimodal retrieval model for asset retrieval are a great example of how to use generative AI to support game development without being a part of the final product. These projects are vital not just to generative AI’s ‘success’ in the industry, but are part of the make-up of the gradual evolution of how AI influences game production, and as always I’ll work to share some insights on this as the bulk of the gaming masses - and the games industry - remains simply unaware of it.

However, alongside this is the much maligned use of generative AI for in-game assets, be it dialogue, story, textures, 3D models, code, animation or otherwise. This will continue, and in many instances we’re going to even more of this, given the games coming out now no doubt did 1-2 years ago.

Many a studio are going to keep to the playbook of trying not to acknowledge that they’ve done it - notably for fear of the ever increasing backlash. Meanwhile I suspect the waffly statements we hear from games studios are going to quieten down. I think people are finally catching on that making these statements in PR is simply not good for business.

Following the public conversation on this as a game developer is important, and we’ll come back to that in a moment!

#4 The First AI-Native Title from a AAA Studio/Publisher Will Be Announced*

As mentioned we’ve seen a slew of AAA titles that have used generative AI to some degree - largely with disdain and outright revulsion from the gaming masses - but there is very little that is what hype-merchants refer to as ‘AI-Native’: meaning that the gameplay experience requires generative AI technology to work.

We have been hit with demo, after demo, after demo, advocating for these ideas, but of course it’s a lot of work to get from these rather limited experiences to a full gameplay. For AAA games studios in particular, you’re typically talking a 3-7 year window for any project to go from initial concept to release. So with generative AI only really blowing up in 2023, we’re still in that phase where any AAA game built with generative AI for gameplay is still in development. I think 2026 is the year we’re going to see a AAA game get announced that is AI-native.

BUT!

You might have noticed I have a cheeky asterisk in the title. I suspect that while an AI-native game will be announced in 2026, we might not actually know if it is in fact AI-native until later. After all 90% of game announcements are vague cinematic-heavy previews without showing gameplay, and given the current public sentiment towards generative AI, publishers will be keen to avoid having their new game be dead-on-announcement.

Speaking of the public sentiment…

#5 Player Backlash to Generative AI Will Become Increasingly More Vocal

For the studio executives and senior leadership reading this newsletter, this is the big takeaway for you.

The vast majority of your most ardent of fans - the hyper-enthusiasts who you rely on to keep the lights on - hate any and all generative AI you have presented to them.

For two years I’ve warned about the significant vocal backlash that games studios would receive as they continue to not just explore generative AI haphazardly, but deliver worthless PR statements that they hope will diffuse any issues. Customers are increasingly savvy both to the aways in which generative AI is being adopted in commercial products, and the impact that this has on both the product they receive as well as the developers behind-the-scenes.

I stated back in the spring of 2024 that game developers need to showcase meaningful use cases of generative AI that don’t simply amount to savings on the salary sheet. They need to see value for them. Something that delivers an experience that’s fresh, engaging, and doesn’t become a means to lay off staff or conform to the (understandable if incorrect) narrative that all generative systems are plagiarism engines.

Thus far everything has come up short, and people are understandably pissed off.

In the past week we’ve seen Larian CEO Swen Vincke continue to back-peddle on his statements regarding generative AI, and that is only going to continue. Going forward the most ardent of Larian’s fans are going to scrutinise everything the studio does right up to, and after, the launch of their next game Divinity. Every screenshot, every social media post, every trailer, every bit of behind-the-scenes footage. Because the implication behind the original Bloomberg interview was the use of these technologies in ways that would compromise the very thing their audience loved in titles such as Baldurs Gate 3.

I really can’t understate how badly Vincke fucked up in that moment. That is a stain the studio may never be able to remove, and it was entirely avoidable too.

Every studio faces this issue, and it is all a matter of public perception. As far as the internet is concerned Call of Duty is now a slop factory, and Microsoft have a big PR problem (one of many) to overcome going forward. Regardless of whether the next entry in the popular shooter-franchise is any good, there are swathes of players who will have abandoned that IP for good because of the AI adoption.

This is only going to get louder, more prominent, bordering on mainstream, and I suspect at least one or two high-profile games this year will suffer as a result.

#6 PC and Console Gaming Will Outpace Consumer Budgets, and Players Will Blame AI

A simple one that we’ll see come through sales data and much more besides: gaming is an increasingly specialist hobby. Thanks to AI bubble pushing RAM prices through the roof - which has a knock-on effect on GPUs - combined with global trade tariffs, games consoles and relevant PC hardware are only going to increase in price.

If you’re hovering over the buy button on a PS5 or Switch 2 right now, I’d get on with it. If you’re looking to upgrade your PC, you’re already a year too late sadly.

This is only going to add fuel to the overall negative sentiment towards AI. After all these cost increases are the result of RAM manufacturers focussing their efforts on creating the fixed spec units for data centres rather than the broader set of SKUs for personal use.

Meanwhile VR platforms such as the Meta Quest are pretty much dying out. The company’s insistence on burning ridiculous amounts of cash on a project (i.e. the metaverse) that nobody wanted - they just wanted cool VR games - has led to them more or less abandoning the platform as they shut down studios left and right. Why are they abandoning it? Well to pursue AI of course.

I expect to see broader consumer spend on new GPUs, RAM and consoles to collectively be on a downward trend in 2026. PS5 sales will slow down, Xbox sales will pretty much peter out. The only one that might buck that trend is Nintendo with the Switch 2 - provided they have something to show for it!

#7 On-Device (Generative) AI Will Surge

Last year I said deployment of AI models (i.e. machine learning and generative AI) that runs locally on the user’s device would be a big talking point. As AI models are prohibitively expensive to host on servers, and the latency often being impractical for real-time gameplay, it would mean that many games and providers will mve towards local inference pipelines and the ability to run on dedicated TPUs on the likes of Nvidia GPUs.

This proved to be dead on. Games like Millenium Whisper launched on Steam at the start of the year, while Dead Meat as we discussed last month has migrated to on-device given the issues (and costs) with running it on a server.

This will only continue this year, what with everyone from Samsung to Arm bringing new on-device AI compute to consumer hardware in 2026. Meanwhile I expect to see more games announced on Steam that rely on on-device AI compute.

However, the big thing for me, is I expect to hear one or two studios announce their intention to release games with on-device AI models on the Switch 2 - the only console on the market that can pull it off.

#8 Agentic AI Will Largely Be Ignored

Conversely, while interest in smaller machine learning and generative models running on-device will see a lot of interest, agentic frameworks - the other big AI topic right now - will largely go unnoticed.

Agentic AI is a form of AI that is expected to operate autonomously in a complex environment. Quite often an agentic framework can have multiple machine learning and generative AI systems running under the hood at once working in tandem. An LLM observes the current state of the system, determines issues and tasks it can execute, and from there start delegating these tasks to the other systems to complete - and all without supervision from a human.

Now if you’re wondering where this would actually get used? Well, think about all of those horrendous AI-based customer support systems you’ve been inundated with in the past year or so. That annoying chatbot you were dealing with would have been part of an agentic framework. It’s subsequently been employed in areas such as gambling and sports betting, cryptocurrencies, social media bots, and more significantly in software development, with AI generating tasks to complete and then writing the code needed to resolve it. I suspect this why every Windows 11 update this past year has been fucking awful. I only just got Bluetooth working on my desktop again after 2 months…

Right now I keep seeing statements that agentic AI will be the next big thing in game development, and while I’ve seen several examples of how to deploy it within a game production pipeline, I’m not convinced. Most of them amount to removing even more humans from the game development process. After all, why bother hiring programmers, artists, writers and sound designers into a studio when you can just get AI to do the whole thing? Those out there selling AI as a tool need to get past the idea of using it to replace creatives in the pipeline. If that’s all you can offer in game development, it’s not going to cut the mustard.

I think at best agentic AI has a future in areas of build automation, coding, and general project management - supporting producers to auto generate tasks based on reports coming in from error logs and performance reports, and I’m curious to see what studios could do in these areas. But outside of that, the bulk of the games industry will reject the idea. Automating creativity will never take off.

#9 The Death of Xbox As a Platform

If I was to put together a list of the biggest winners and losers of 2025, I would put Microsoft somewhere at the top of both categories. The company continues to prove highly successful, with stock prices riding high, and revenue up 15% on 2024. Meanwhile their gaming brand has pushed heavily into cross-platform publishing, with last summer proving highly lucrative as half of the top 10 best-selling games on PS5 were published by Microsoft.

But much of Microsoft’s success has been at the expense of Microsoft itself. Profits are pushed by annual mass layoffs in the thousands, with surviving games studios either shut down or reconsolidated. Projects are shut down or quietly shuffled away into obscurity. Combine this with the rather lacklustre launch of the Xbox Rog Ally - a great piece of hardware let down by an atrocious OS layer and inability to play your console library - increasing the price of Game Pass Ultimate by 50%, and the ever-dwindling sales of console hardware, and it paints an ugly picture. With these pushes coming as Call of Duty suffers its worst launch in recent years, and its stuffed full of gen AI nobody wants too.

Despite Xbox releasing some fantastic games in 2024 and 2025, the general sentiment towards the brand feels low, and a big part of that is the broader sentiment towards Microsoft. As it becomes apparent that everything from laying off developers, to increasing costs on consoles, games, and subscriptions is part of a broader effort to absorb costs for a push into consumer-grade AI products that really aren’t justifying their cost. The company is increasingly synonymous with AI in ways ‘Microslop’ won’t be happy about. Meanwhile they continue to face scrutiny from their indirect support of Israel with the Boycott Xbox movement. With them being described by the Palestinian BDS National Committee (BNC) as the "the most complicit tech company in Israel’s illegal occupation, apartheid regime and ongoing genocide against 2.3 million Palestinians in Gaza".

By the end of 2026 there will still be Xbox consoles on the shelves - assuming stores keep selling them. But unless efforts are made to improve the public image of Xbox and the value it is bringing to players as a platform, the console space they operate in will be largely a net loss, and the brand would be best served as a games publisher on PC, PlayStation and Nintendo.

It’s a real shame as I’ve been integrated into their ecosystem since the Xbox 360, but I find it increasingly difficult to continue to invest in it any further.

#10 New UK AI Legislation Will Annoy Everyone

After the past year in which I’ve written about legal implications of AI in the games industry on multiple occasions, I couldn’t possibly wrap up my predictions without making a proclamation in this sphere.

Having recently published their response to the AI consultation from around this time last year, it is pretty clear that the public hate everything the government thought was a good idea. Plus, AI companies at the time of the consultation didn’t think it was enough. I still need to report back on the consultation response. Hopefully in an upcoming issue later this month if not February.

I suspect later this year the Labour government will put forward a bill proposing their intended changes for AI and copyright, and it will once again be in this middle ground where everyone is angry, nobody is happy, and I’ll have to dig into it all again…

Wrapping Up

There we have it: 10 predictions for the year ahead. It’s a bit of a miserable set of affairs, but nonetheless I hope you found it insightful! I’ll be interested to see how far off the mark I am come the end of the year.

In the meantime, a special shout-out to fellow AI and Games Conference organiser Duygu Cakmak who appears in the video above showcasing a prototype for an in-game generative-AI powered advisor for Total War: Pharoah, powered by Nvidia’s ACE platform.

It’s an interesting idea of having an AI assistant helping you better understand how to succeed in a complex strategy series like Total War. I still suck at these games despite having played hours of several entries in the franchise.

Alrighty, catch you later folks. See you next week.