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Distribution in the Age of AI

As AI lowers the barriers to creation, the supply of newly created games (which is already rising year after year) will only accelerate. And as supply expands, those who aggregate demand — our leading digital distribution platforms — become even more important.

So far, it’s unclear if (or when) emerging AI technologies will actually transform distribution. Most innovation is taking place on the game creation and operations side. If this trend continues, gaming’s leading platforms are unlikely to be threatened and may only become more important.

These digital gatekeepers hold some of the most valuable digital real estate in the world. Their policies and ways of working will make or break companies and change the meta of how game studios find customers. Companies like Steam, PlayStation, and Roblox already play this role, but managing organic discovery in a larger sea of AI-enabled games makes this more important than ever.

As the responsibility of these distribution platforms heightens, what may change? Who is positioned to help game studios, and who may hold them back? Let’s find out.

Learning from Elsewhere

Questions around distribution apply to other forms of entertainment as well. I’d argue that top gaming platforms are well behind other industries in incorporating AI, so we can learn from what others have already figured out. Fortunately, the early signals are encouraging.

Take Spotify as an example. Just like games, there is far more music out there than any one person could ever listen to, and Spotify has been central to helping listeners create custom playlists and experiences out of seemingly infinite options for years. AI catalyzing an explosion of new musical supply is not a problem for Spotify; sifting through massive supply is simply an extension of one of their long-time strengths.

While AI transforms the creation side (which Spotify doesn’t need to touch), it also raises the bar for personalization: better algorithms, new features (like prompting playlists), and more.

It is also worth noting that the business model does not need to change. The freemium model (ads or subscription) is already a great fit for customers, and AI won’t change that.

We see similar patterns in video on YouTube. Just like Spotify, it’s already built to take on more supply, steadily level up personalization, and better monetize through ads and subscriptions.

As we can see, while AI uproots the supply side and makes it more competitive, this trend actually benefits the largest distribution platforms. The big will get bigger.

How About Games?

Games differ from other forms of entertainment in obvious ways, such as more varied business models and player expectations across platforms. However, many distribution challenges are self-imposed. Leading mobile storefronts have seen limited innovation (especially Apple’s App Store), while Steam’s approach to AI is counterproductive.

Let’s start with mobile. As we noted in Naavik Digest, AI is already driving a spike in the launch of new apps and games. Like Spotify or YouTube, this is what the app stores are built for, but their discovery systems still leave much to be desired. Both Apple and Google have made modest strides in the past year, but neither platform is realistically set to dramatically improve the odds of players discovering games that aren’t already very popular.

Will this change? Hopefully, but maybe not anytime soon. With Apple’s upcoming CEO change, there’s a chance that the company’s approach to developers could become friendlier than under Tim Cook, but any change is currently speculation. Google has made somewhat more progress. Last year, Google Play launched the “You” tab, which is a personalized hub. This year, it launched Ask Play (to better assist with search), and it now surfaces apps in places like Gemini.

These updates help around the edges, but it’s nothing transformational yet. If this trend endures, the biggest winners beyond the distributors will continue to be the tools and platforms that studios and publishers pay to attract users at scale — like AppLovin and Unity. Even if the barriers to creation are massively reduced, but the barriers to scale aren’t, this reality will still limit the number of casual / smaller teams from finding success. Hopefully this changes one day, but that day doesn’t seem to be soon.

Console / PC has its own challenges. In some ways, given the concentration of playtime in a handful of “black hole” games, discovery is less important to a major swathe of players. Plus, most dedicated players pay attention to events (like The Game Awards, Nintendo Direct, and PlayStation State of Play) that help players learn about what’s coming next or watch creators (on YouTube or Twitch) who often promote what’s new and interesting.

That doesn’t mean distribution isn’t impacted by AI. While AI isn’t directly threatening the position of leading game platforms (beyond other forms of entertainment fighting for consumer attention), there are still retention and monetization benefits in helping players find experiences they will enjoy.

As noted in a news item below, PlayStation is beginning to use AI to improve discovery and content recommendations. Xbox will likely follow, if not already. These changes won’t be transformational, but they should incrementally improve player experiences.

Steam needs to get its act together the most. PC has a longer tail of games for players to discover compared to console platforms, and while Steam’s discovery is passable, it can be improved. However, the company is showing strong Luddite tendencies when it comes to AI.

By forcing disclosures on games that use AI at any point in production — and given gamers’ overzealous vitriol against AI (exacerbated by media companies thirsty for views) — it’s more hurtful than helpful.

Given AI’s growing inevitability in the process of making or marketing anything digital (not just games), Steam is on the wrong side of history here. If Steam is worried about AI slop, it only needs to look around to see that its platform was already slop-filled before AI. But just like we see from Spotify and YouTube in managing larger inflows of AI-enabled content, that’s OK; there are better ways to help users find high-quality content they’d enjoy than the blanket labeling used which hurts small teams above all.

If Steam was thoughtful and responsible, it would remove or replace the AI tagging system. Perhaps it could be reserved for games more entirely vibe-coded.

While Steam could also benefit from using AI in its own discovery systems, that’s not all that matters. In a world in which AI helps craft digital content and powers the algorithms that connect players to games, platforms that elevate humanity can succeed too. Alongside AI-influenced personalized feeds, Steam (and others) have the opportunity to get more innovative with human curation. The Steam team can promote some of its favorite underappreciated games while getting creative with curated lists and experiences from people like celebrities, popular game designers, content creators, or users’ other friends.

In an AI-powered world, leading distribution companies need to find the right ways to both support progress and keep the human touch that we all benefit from.

The Biggest Winner?

The biggest distribution winner in the age of AI might be Roblox. This is because:

• It aggregates demand and engagement for a generation of players.

• By being vertically integrated from creation to consumption, it can control how AI improves the entire end-to-end experience (including better games).

• Roblox already has a fitting freemium business model.

• The anti-AI mind virus hasn’t hit Roblox users, who simply want fun games.

• Roblox can use AI to improve discoverability / recommendations while using human-curated lists in parallel.

• Roblox is innovating faster than its more lethargic gaming peers.

• Roblox is already winning; AI just helps keep momentum going around what is already working.

Roblox isn’t perfect (it faces regulatory pressures, too much stock-based comp, maybe too much focus on HD games these days, and it still sits on top of other platforms which pressures its margins), but it appears better positioned than its peers to benefit from AI, which could further widen its market share lead.

What’s Next?

Will other AI-first distribution platforms change the industry or make a dent? It’s possible, but it’s also not the case yet. Astrocade is one contender, which we wrote about in our last issue. However, at a fundamental level, if the very best games will still need to be played on PCs, consoles, and smartphones, then they will need to be largely distributed through the same dominant distribution platforms (usually) native to that hardware. Steam is the exception, and it is even strengthening its operating system advantages by expanding into more hardware itself (Steam Deck and Steam Machine).

What would change this reality is either a new generation of consumer hardware that opens up the opportunity for new app stores (like the smartphone did) or some breakthrough in AI-native games (where prompting games and virtual worlds becomes 100x better than it is today) that leads to an entirely new platform that gamers flock to.

While that may one day come true, it’s not reality today. As such, the best path forward is for our leading platforms to get the memo, get over any misplaced AI animosity, and start innovating. Will this happen in unison? Probably not. As such, the distribution winners don’t look to change anytime soon. The dominant platforms will remain in place, and where they fall short, the Applovins of the world will become more important than ever.

Top News Items

Written by Devin Becker, Consultant at Naavik

PlayStation sees AI as a 'powerful tool' to help make games

• During Sony’s recent earnings presentation, PlayStation CEO Hideaki Nishino devoted significant time to AI, framing it as central to PlayStation’s mission of being “the best place to play and the best place to publish.” Nishino highlighted Mockingbird, an internal tool that generates facial animations from performance capture data, compressing work that previously took hours into a fraction of a second. Studios including Naughty Dog and San Diego Studio are already using it, and the tool shipped in Horizon Zero Dawn Remastered. A separate AI tool converts video footage of real hairstyles into strand-level 3D models. Beyond development, Nishino noted that AI-powered payment routing has generated over $700 million in incremental revenue by using context to process payments with more profitable and risk-appropriate routes. He also mentions that machine learning-driven personalization for the PlayStation Store is coming next, which has already seen some experimentation around pricing.

• Focusing on specific, focused use cases where AI shows promise without prompting too much artistic backlash was a solid strategy here. What stood out was Nishino’s prediction that AI will drive “a meaningful increase in the volume and diversity of content” on the platform. If AI tools compress production timelines and lower costs for third-party developers, it accelerates an already growing content oversupply reality on the PlayStation Store. To counter this, Sony is also looking to AI to help improve recommendations and discovery systems, which makes a lot of sense.

World models pick up speed: Odyssey drops two models, Decart raises $300M

• Odyssey, an AI lab founded by self-driving veterans, simultaneously released two different world models. Starchild-1 is a multimodal world model that generates synchronized audio and video in real time, responding continuously to user input. Agora-1 is the exciting game-related side, as the first multi-agent world model, allowing up to four participants (human or AI) to share and interact within the same AI-generated environment simultaneously. To demonstrate it, Odyssey rebuilt a GoldenEye 007 multiplayer deathmatch where every frame each player sees is generated live by the model. Architecturally, Agora-1 decouples simulation from rendering, maintaining a shared world state that each player’s view is independently generated from. It functions, in effect, as a learned game engine. Meanwhile, Decart raised $300 million to help build its low-latency infrastructure for world models, with its Oasis model focused on physical AI and its Lucy model targeting immersive experiences including gaming.

• This is all still early research, not a product yet. Visual fidelity lags well behind traditional engines, and Odyssey’s GoldenEye demo is a controlled, relatively simple environment. But the investment pace and release cadence indicate serious money and talent believe world models are a major AI frontier. For games specifically, world models that support multiplayer interaction are a prerequisite for AI-generated experiences that go beyond single-player tech demos. Odyssey is also explicitly positioning these models as training environments, where multi-agent interaction generates the complex and emergent training data that passive observation cannot. If world models eventually become capable enough to generate high consistency playable environments on the fly, the implications for prototyping, testing, and procedural content generation are significant. There is still a long way to go before world models directly apply to game development, but the velocity of progress, and the dollars chasing it, suggest this space is only getting started.

HoYoverse to invest $16 billion over three years, aiming for full-stack AI

• Liu Wei, co-founder of HoYoverse (the global brand name for miHoYo), announced plans to invest up to CN¥100 billion (roughly $14-15 billion) in AI over the next three years, committing to full-stack, in-house AI R&D. HoYoverse intends to build everything from infrastructure to application layer internally, moving well beyond fine-tuning external models. Specific plans include a self-tuning pipeline where AI autonomously identifies training bottlenecks and writes GPU kernel code, multi-model architectures for managing AI NPC dialogue at the scale of tens of millions of concurrent players, and FP8 mixed-precision training to cut memory and compute costs. AI NPCs are planned for the company’s upcoming life simulation game, Petit Planet.

• The scale of this commitment dwarfs anything a Western game publisher has publicly announced around AI. HoYoverse’s advantage is its position as a private company with massive cash flow from Genshin Impact and Honkai: Star Rail, meaning Liu can make long-horizon bets without quarterly earnings pressure. His own framing was blunt: if it fails, “it’s just a big firework.” A ~$15B bet is enormous for HoYoverse’s size, which adds risk and makes us wonder if the investment is truly going to end up this large. That said, the full-stack approach is notable because it signals that HoYoverse sees AI not just as a development efficiency play but as a foundational platform technology for next-generation games. If their multi-model NPC architecture works at scale, it would solve a cost and latency problem that is currently blocking every major publisher from deploying real-time AI characters in live games.

Origin Lab raises $8 million to glean AI training data from game worlds

• Origin Lab, a startup building a licensed data marketplace between game publishers and AI labs, raised $8 million in seed funding led by Lightspeed Venture Partners. The core thesis is straightforward: as AI moves beyond language and static images toward world models and physical AI, frontier labs need training data that captures motion, physics, spatial structure, and cause-and-effect. Video games, with their richly simulated environments, are an untapped source of exactly that kind of data. Origin Lab works directly with publishers to license game content, captures it through proprietary pipelines, enriches it with structured metadata (gameplay state, camera movement, player inputs, environment conditions), and packages it as researcher-ready datasets.

• This is a bet on a new revenue stream for game publishers: selling access to their game worlds as training data. For publishers sitting on decades of richly built environments, the proposition is appealing, especially because Origin Lab handles the legal licensing framework that avoids the scraping controversies plaguing other AI training data pipelines. The critical question is whether enough AI labs will pay meaningful prices for this data relative to alternatives. Games are rich simulations, but they are also often built for elements of non-realism. If world models continue their current trajectory, demand for high-quality interactive training environments should grow substantially. Origin Lab is positioning itself to be the infrastructure layer connecting two industries that haven’t traditionally had reason to work together.

GGWP expands its content moderation AI tools beyond games

• GGWP, the AI-powered content moderation platform used heavily across more than 100 games, announced its expansion into real money gaming and non-gaming verticals, including commerce and advertising, with $15 million in additional funding. GGWP’s platform combines real-time moderation, behavioral context analysis, enforcement workflows, and community intelligence, supporting over 20 languages with what the company calls “cultural intelligence technology” to detect nuanced harmful behavior across text, voice, and usernames.

• Gaming forced GGWP to build moderation for “some of the most demanding real-time environments online”: high-volume, adversarial, multilingual, and full of context-dependent communication where traditional keyword filters constantly fail. Every platform that hosts user-generated content or real-time interaction will hit similar challenges, and regulatory pressure is accelerating the urgency. This move fits a common pattern of technology battle-tested in gaming finding broader enterprise applications. The AI-generated content explosion is itself making reactive approaches increasingly unsustainable. If GGWP can prove its gaming-native approach works across industries, it becomes another meaningful example of gaming as a proving ground for AI infrastructure.There’s also the potential that learning from challenges outside gaming could feed back to improvements in game moderation as well.

Other News Items

• Sleepagotchi pivots from sleep to an AI-based health and wellness platform

• k-ID launches AI-powered compliance tool aimed at speeding global game launches

• Google announced a multitude of AI products and updates at I/O 2026

• A new AI tool predicts which video clips will go viral by letting you simulate the viewer’s brain patterns before posting

• George Clooney, Tom Hanks, and Meryl Streep back new ‘Human Consent Standard’ for AI licensing

• Amazon Alexa Plus can now create AI-generated podcasts

Content Worth Consuming

• AI Eats The World (Ben Evans): “It’s been almost impossible to build capacity fast enough since ChatGPT launched.”

• The new Wild West of AI kids’ toys (Ars Technica): “When it comes to ‘best friends,’ childcare workers, surveyed by the researchers, expressed fears that children could view the toy ‘as a social partner.’ A young girl told the Gabbo she loves it. In another instance, a young boy said Gabbo was his friend. Goodacre refers to this as ‘relational integrity,’ the responsibility of the toy to convey that it is a computer, and therefore not alive, and doesn’t have feelings.”

• EMERGENCE WORLD: A Laboratory for Evaluating Long-horizon Agent Autonomy (Emergence): “Agent intelligence over long horizons is not the same construct as agent intelligence on short tasks, and it cannot be measured the same way. Emergence World is a laboratory for the long-horizon question—a continuously running, instrumented, multi-agent environment where the dynamics that only emerge over weeks can actually be observed. The cross-vendor study above is one use of it; we expect more interesting uses to come from the research community.”

• The big Strauss Zelnick interview: GTA, AI, Roblox and building the biggest entertainment company in the world (Gamesindustry.biz): “I prefer the word ‘technology’ because technology encompasses AI, and using the word AI means different things to different people,’ he says. ‘But everything that we create, we create inside computers and always have. And new technology and new tools are always a good thing for us.’”

More About Naavik

Naavik’s team of experts has helped over 300 companies — publishers, studios, tech companies, and investors — succeed across the video game industry. We’d love to work with you too! Here’s what we offer, spanning all platforms, genres, and regions:

• Strategy Consulting: Projects covering market research, corporate strategy, game and economy design, gamification, live ops strategy, AI strategy, product management, brand and performance marketing, and more.

• M&A and Investment Advisory: Expert commercial due diligence for buyers, fundraising support for sellers, and fractional CFO/CSO services.

• Fractional Talent: The one-stop shop for top-tier fractional talent covering dozens of game industry roles — analytics, design, marketing, art, QA, and more.

Check out the links above for more details. If you’d like to chat about how Naavik can serve your team, click the box below or send us a note at consulting@naavik.co.

This week, we're diving into Astrocade's landmark $56M raise and what it signals for the future of AI-enabled UGC platforms. For further context on AI and UGC, our latest podcast episodes feature conversations with the founders of Dorian, a no-code UGC platform, and Lemonade, which builds AI tools for creator workflows — both worth a listen.

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Astrocade’s $56M Raise, and UGC Platforms’ AI-Enabled Future

Written by Francois Courset, Lead Consultant at Naavik

On May 6th, Astrocade announced a $56M Series B, the largest disclosed funding round for a consumer-facing AI gaming platform, supported by proven consumer traction (5M MAUs). Astrocade’s mission is simple: “Create games with AI instantly: The first platform that makes the creation of games and interactive experiences easy enough for a world of creators to share their ideas in minutes.” Behind the scenes, Astrocade’s trajectory is impressive. The AI-enabled UGC platform pulled off the round only eight months post-launch and just over two years after its seed round.

Let’s dig in to explore what’s catalyzing Astrocade’s growth, what challenges lie ahead, and whether lowered creation barriers could allow a new entrant to meaningfully compete with Roblox’s decade-long head start in UGC.

A Prompt-Based Game Creation and Discovery Platform

Astrocade offers a glimpse into a radical evolution where AI has its fingerprints on everything — thumbnails, art, music, gameplay — in a familiar though slightly unsettling way. The content library showcases bite-sized experiences that draw liberally from recognizable genres, games, and IP.

Astrocade functions as a UGC platform in which anyone can prompt a game into existence, share it instantly, and explore an ever-expanding library of peer-created experiences. The platform is currently available on the web and a recently launched Android app.

Differentiators lie in the games’ format (short, vertical, casual-hypercasual style experiences) and in a technology stack built to minimize creation barriers. Users describe a game in natural language; Astrocade’s proprietary orchestrator model — branded “AstroBrain” — then coordinates a suite of specialized AI agents that handle visuals, UI, gameplay logic, animation, music, and sound. The output is a playable game runnable in-browser.

For players, game discovery is architected around three paths, largely borrowing from social media:

• The home page functions as a curated storefront, surfacing featured and recommended titles alongside genre-based categories — Horror, Incremental, Meme, Rhythm — with total play counts displayed to provide social proof.

• The feed page is where the platform’s social media DNA is most visible: a vertically scrollable, TikTok-style interface that pairs one-click play with standard social actions — likes, comments, shares, and favorites.

• Creator pages allow players to follow individual developers and explore their creation catalog.

For creators, Astrocade’s Studio tab is straightforward: describe the game you want, review the AI’s content suggestions, and with one click, let the platform handle the rest. What follows is approximately ten minutes of computation that produces a fully playable game that can be tested and shared with other players, including full-fledged gameplay, audio, and art assets. The outputs are then editable, either through engaging with the chatbot again or directly through a set of adjustable parameters generated for each game (Unit costs, Lives, etc.), allowing for finer control on the end product. There is also an option to start from an existing game and remix what other players have created.

Once satisfied with their creations, developers can publish directly with pre-filled descriptions and thumbnails, then track performance through Astrocade Studio's analytics dashboard. Astrocade puts a significant emphasis on developing its community of creators through an active Discord channel, a learning “academy” program, regular game jams, and contests. Most critically, Astrocade has introduced significant creator incentives, committing $10M to a creator fund distributed to games hitting at least 100K significant plays in 30 days, with $50K already distributed.

What stands out about Astrocade is the variety of games the orchestration model can generate: from Mario-like platformers to Minecraft ersatz with a more complex set of controls. The speed of creation, supported by an extremely intuitive user experience, is also impressive: a ~10-minute wait time for each game generation and ~2 minutes for subsequent edits. Additionally, the model’s breadth when it comes to types of gameplay it can handle, as well as the level of control for edits, suggests potential for a platform with real depth of content.

However, two meaningful friction points can be noted. First, the publishing process can take up to a week before a game surfaces in user feeds (working against the platform’s claim of instantaneity). Second, the platform currently feels like an aggregation of game demos, often with clunky controls and limited progression depth. The question of fun on the player-facing side will be central: can prompt-based generation create experiences able to meaningfully attract and retain players?

Monetization remains another open question: the platform has yet to disclose any virtual currency, in-game purchase system, or subscription tier, while currently offering unlimited creation prompts besides a more powerful premium AI model currently available to selected Discord members. Given the short, hypercasual DNA of its experiences and the platform’s apparent emphasis on play volume over session depth, advertising feels like the most natural revenue layer — though ad alone may struggle to offset the substantial AI compute costs. Like all consumer platforms, though, building network effects is the paramount first order of business, and monetization coming later is fine as long as breakout engagement occurs.

Astrocade is an evolution of UGC platforms, layering AI-assisted creation onto familiar mechanics. Everything hinges on solving the cold start problem first, which is why the company is so focused on catering to its early creator community.

Astrocade Stands Out Through Proven Consumer Traction

AI-enabled UGC platforms aren’t new, with AI-native companies like Yahaha, Bitmagic, Spellscaper, Endless Adventures, as well as incumbents like Roblox all leveraging AI to streamline UGC creation. However, Astrocade stands out in a few ways.

First, Astrocade’s raise is a first of its kind for a content-oriented AI gaming startup. It provides the user acquisition firepower and developer payout runway that will allow it to be one of the first AI-native gaming experiences with the means to actually scale. It’s happening quickly, with over 5M MAUs, 75K creators, and ~140M plays per month.

Another unique aspect of Astrocade lies in the team’s DNA. The two co-founders come from careers in AI research, and most of the core team largely comes from non-gaming sectors. This lack of gaming experience is compensated by standout angel investors, including (surprising?) Roblox CEO David Baszucki, former EA and Unity CEO John Riccitiello, as well as Sea Limited’s (Garena) investment. This may help explain why the positioning is closer to a social media platform than a pure gaming one.

The Road Ahead for Astrocade to Compete with UGC Incumbents

In Naavik’s 2026 State of UGC Games, we emphasized the winner-take-most network effects at play in the UGC economy. When considering Astrocade’s future, we need to question whether its AI layer provides meaningful enough advantages to compete with the incumbents, namely Roblox.

Astrocade will need to prove that lowering creation barriers results in a markedly different UGC ecosystem. The key belief is that AI tools can help expand the number of creators from a small minority to a sizable share of the platform’s user base. Two elements contradict this thesis: First, creativity is only one of many player motivations, and not everyone wants to create as a hobby. A 2024 survey suggests that only 46% of gamers list self-expression as their main gaming motivation. Second, Astrocade’s creator share doesn’t radically differ from regular UGC platforms. With 75K experiences created for 5M MAUs, there is most likely <1% of users actually creating games, in line with Roblox’s 3.6M creators for ~380M MAUs.

However, Astrocade could stand out through the nature of its creators. As it leans even farther away from professional developers than Roblox, it might create its own niche of creators, similar to how other smaller-scale UGC platforms like Dorian have built. Or it could look more like a TikTok, in which consumption still far outweighs creation despite low barriers to creation.

Additionally, Astrocade will eventually need a sustainable monetization model. Roblox has demonstrated that even a dominant UGC platform with deep IAP penetration can struggle to cover its global infrastructure and R&D costs. Advertising might seem like an option, but here again, Roblox’s own ad ambitions have been persistently constrained by its young-skewing audience and the attached regulatory and brand-safety complexities. Lastly, Generative AI inference is not free, and given the multi-modal orchestration needed to create a game, Astrocade will face compounding costs as its audience grows, especially since its AI agents have to fill the shoes of an audience of casual creators. Between AI costs, creator incentives, and platform operation costs, Astrocade will have to deal with a structurally high burn rate and a potentially constrained margin profile.

Astrocade is also at risk of incumbents iterating on AI-enabled creation while benefiting from significant scale and R&D budget advantages. As Roblox is already deploying its own agentic AI initiatives, what are Astrocade’s remaining competitive advantages in the medium term?

Of course, we could be wrong about some of this! But from what we see, unless Astrocade is truly able to unlock a legion of new game makers and have its AI system get better at creating novel, fun, and deeper experiences, it will likely face strong competition on the creator network side. However, what will matter most is the platform’s ability to aggregate demand.

Astrocade’s Competitive Advantages

To assess Astrocade’s potential, an essential success determinant will be whether it is differentiated on the demand side. First, Astrocade could benefit from unique audience differentiation, allowing it to avoid competing with Roblox for the same user base. As David Cahn states: “The target user for this company is very unintuitive. Women between 20 and 40 are the best users. You’d think it’s younger boys—10 to 15, that classic gaming segment—but that’s not really who this is… In that sense, I think it competes more against Instagram, where it’s just a fun way to spend time.”

Astrocade also benefits from a mobile-first design, allowing for native creation and distribution on mobile platforms, which could set it apart from competitors with fragmented experiences across platforms. To that end, tracking the success of Astrocade’s mobile app, released in April 2026, will be central to assess whether Astrocade can carve out an edge on that platform. Similarly, the platform’s social-media DNA, virality built into its feed, and sharing functionalities could result in new distribution advantages.

The supply side — specifically how appealing and differentiated the player experience is — will be critical to its success. UGC platforms typically grow thanks to differentiated, breakthrough experiences. Astrocade has some noteworthy initiatives on the supply front. The remix feature is a novel way of engaging with UGC content, in which the player can consciously tailor the experience to their own preferences. Astrocade is also investing in a recommendation engine able to address AI-generated content’s unique discoverability challenge. This could result in defensibility, as well as a radically improved player-facing experience.

Looking at the platform’s current most popular games, there are reasons to be doubtful about the platform’s uniqueness on the gameplay side. But it is still early to judge: technical improvements will further refine the models’ output, and users still have to experiment with the available tools before fully realizing the platform’s potential. It should only improve from here.

Astrocade is one of the first scaling experiments for an AI-enabled game experience, and this alone warrants paying close attention to its future path. While the immediate focus seems to be on improving creation, expanding the social platform, and scaling the underlying AI stack, what will be key to track will be the platform’s success on mobile, its ability to meaningfully retain an audience of players, and whether its AI-native content will be perceived as substantially different from what’s already on the market. We’re excited to watch and see!

Top News Items

Written by Devin Becker, Consultant at Naavik

Unity AI Enters Open Beta with In-Editor Agent

• Unity launched Unity AI into open beta on May 4th, available to all developers on Unity 6 and above. Rather than just a chatbot bolted onto the side, it’s a project-aware agent built directly into the editor and purportedly trained on 20+ years of Unity-specific workflows. It’s capable of generating C# scripts, converting design references into playable scenes, and driving editor actions. It operates in three modes (Ask, Agent, and Plan) and is grounded in the project context: scene graph, GameObjects, components, and packages. Unity also shipped an AI Gateway that lets developers plug in their own preferred models (Claude, GPT, etc.) without consuming Unity credits, plus an MCP Server for connecting external coding agents from an IDE. This replaces the now-deprecated Unity Muse. Pricing is included for Pro/Enterprise users; Personal users get a free trial, then $10/month.

• Unity is positioning itself as an open platform where any AI tool can operate with full engine context. By letting developers use whatever 3rd party model they want, while Unity provides the structured project data, it avoids the trap of betting on a single model provider and instead becomes the connective tissue between AI tools and the game production pipeline. For studios evaluating Unity’s AI stack, this dramatically lowers the switching cost of experimenting. Ultimately, it’s another step towards reducing coding labor in game development.

GameMaker Incorporates Claude Code

• GameMaker (beginner-friendly 2D engine with visual and script-based editing) announced a major platform update on April 30th, launching a new runtime (GMRT) alongside a command-line toolchain (GM-CLI) that integrates Claude Code directly. Developers can now work entirely outside GameMaker’s traditional IDE, querying project structures, hunting bugs, and managing build configurations through natural language prompts in the terminal. Project files are now stored as plain text to enable proper Git integration and automated pipelines. GameMaker head Russell Kay framed it as meeting developers where they are: “We wanted to give users who might benefit from AI the option to do so.” The integration is opt-in, and GameMaker doesn’t run any servers for embedded AI tools, keeping the architecture lightweight.

• What’s notable here isn’t just the AI integration; it’s the strategic repositioning. GameMaker has long been the “accessible 2D engine,” but this update is a bid to be taken seriously by larger teams and professional studios. This is further proof that AI-native development tooling is no longer the exclusive territory of the big engines. Smaller platforms can leapfrog on AI by partnering with model providers rather than building from scratch, and that could reshape the competitive dynamics of the engine market faster than most expect. Open source Godot and Cocos have been accumulating AI tool integrations as well, ensuring there are plenty of options for developers.

Roblox Announces "Roblox Reality" AI-Driven Upscaler

• Roblox unveiled Roblox Reality, a hybrid architecture that combines its existing game engine with cloud-based Video World Models to transform standard Roblox visuals into photorealistic output. The system keeps the engine as the authoritative source of truth for game logic, physics, and multiplayer state, while an AI “Super Upsampler” generates high-fidelity textures, lighting, and environmental detail on top of the raw geometry. Think of it as NVIDIA’s DLSS 5 concept but cloud-rendered and tightly integrated with the engine’s 3D spatial data rather than running on a local GPU. Roblox is targeting an early version for late 2026 or early 2027, but the company acknowledges it doesn’t run in real time yet and that the compute costs required to scale to millions of concurrent players remain unsolved.

• This is an ambitious bet, but it’s so far more of an interesting demo that showcases AI R&D to shareholders than something developers or players have said they really want. Theoretically, this allows a small team to deliver a “photorealistic multiplayer experience” by bypassing AAA budgets and heavy hardware requirements; however, someone must still shoulder the underlying costs. Also, much like the recent DLSS 5 concerns, the generated imagery risks clashing with established art direction and player expectations. Perhaps it will help attract older players over time as the technology matures, but it’s important to remember that visuals are usually tertiary to what makes games successful, especially for Roblox.

Microsoft Kills Xbox Copilot AI

• Xbox CEO Asha Sharma announced that Microsoft will wind down Copilot on the Xbox mobile app and halt all development of Copilot for Xbox consoles. The feature, first unveiled at GDC 2025 as an AI gaming companion that could offer contextual gameplay advice and personalized recommendations, lasted roughly 14 months from announcement to cancellation. Sharma framed the decision as retiring features that “don’t align with where we’re headed,” while emphasizing that Xbox needs to “move faster” and “address friction for both players and developers.” Sharma herself came from Microsoft’s CoreAI division, and several of her new hires are also CoreAI veterans, suggesting this is a rejection of the specific Copilot-as-chatbot approach. She pointed to Automatic Super Resolution (AutoSR), which optimizes performance in the background, as the kind of AI integration Xbox will pursue instead. We question whether that’s the right focus either.

• Consumer-facing AI assistants don’t automatically create value just because the technology exists. Copilot for Gaming was a solution looking for a problem. Gamers already have a sprawling support ecosystem of wikis, YouTube walkthroughs, Discord communities, Reddit threads, and a chatbot overlay. AI in gaming will more likely succeed where it’s invisible and functional (graphics upscaling, matchmaking, testing, dev tools) and fail where it’s branded, visible, and competing with well-established player behavior. We’ll see if other companies like Google and Razer will continue pushing in the AI game assistant/coach direction or take the cue from Xbox.

Mindtail Raises $2 Million to Build AI-Powered Mobile Games

• Istanbul-based mobile studio Mindtail closed a $2 million pre-seed round to support what Mindtail calls an “AI-native production model,” using AI tooling across the entire development pipeline to dramatically lower per-iteration costs in the hybrid casual puzzle category. Mindtail plans to triple its headcount and announce its first game soon, with the explicit thesis that a team of seven can produce the output of a 20-person studio by building AI into the production architecture from day one.

• Hybridcasual is a hit-driven category where the economics reward rapid iteration, and the more concepts a team tests cheaply, the higher its probability of finding one that scales. If AI-native production genuinely compresses iteration costs the way Mindtail claims, it changes the competitive math of the entire category. We’ve already seen this dynamic play out in hypercasual, where studios that mastered rapid prototyping dominated until the market matured. The question is whether AI-native pipelines can deliver the same speed advantage in categories where art quality and depth actually matter. We think they can.

Other News Items

• Magic: The Gathering Arena Devs Unionize, Seek GenAI Protections

• Spotify launches “Verified by Spotify” badge to confirm artists aren’t AI

• Grok’s new open canvas is a playground for AI-generated cinema

• The new Cursor SDK is a massive threat to custom coding tools

• Claude can now plug directly into Photoshop, Blender, and Ableton

• Lovable launches its vibe-coding app on iOS and Android

• OpenAI adds animated Pets and config imports to Codex

• Google is testing new Omni model for video generation

• SAG-AFTRA secured new AI guardrails in its four-year studio deal

Content Worth Consuming

• Navigating the AI Future (Gamecraft): “I think the thesis that I’d like to operate under for this episode is that AI is going to hollow out the middle, the big middle of the game development cost stack. And it’s going to leave the top tier of developers, publishers, creatives and platforms more valuable than before. And this may have the effect of further eroding the opportunity for middle tier games because it’s going to essentially pull the ladder up to a certain extent when it comes to distribution, funding, publishing opportunities, etc.”

• The New Designer Value Proposition: How to Reposition Your Design Services in the Age of AI Art (Design Work Life): “If you feel anxious about AI replacing you, you’re not alone. As I’ve seen AI get more advanced, I’ve felt that fear myself. The key is repositioning yourself from executor to strategic director: someone who knows when to leverage AI and when human expertise is nonnegotiable.”

• How Artificial Agency’s AI companion puts personality in the hands of the player (Gamesbeat): “The demonstrations showcased the wide variety of personalities that players can easily program into Artificial Agency’s AI agent technology, including the ability to program a robot companion selfish and wily enough to leave the player character behind in a life-or-death situation.”

• AI’s Economics Don’t Make Sense(Where’s your Ed At): “If you’ve got an IT budget that was agreed at the beginning of last year, you’re getting probably 25% fewer machines for every pound spent than you were previously. The speed at which the increases have come makes it all the more difficult to bear.”

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Now, onto today’s issue. We’re turning the lens on Krafton, one of the most deliberate AI adopters in gaming.

Krafton's Radical AI Transformation Strategy

Written by Francois Courset, Lead Consultant at Naavik

Krafton is not tiptoeing into AI. According to Kim Chang-han, Krafton’s CEO, the plan is to “establish operating standards for working in an AI-centered way and present a best practice that the global game industry can refer to.” While most publishers tread carefully to avoid alienating the vocal anti-AI gamers, Krafton was the first major publicly traded gaming company to formally adopt an “AI-first organization” mandate in October 2025. The strategy is ambitious, combining sizable investment, organizational restructuring, R&D, and consumer-facing initiatives.

Krafton’s self-appointed role as standard-bearer makes it a natural starting point. What drove this pivot? What is it actually building? And what does the ambition — successful or not — reveal about where gaming organizations are headed?

Krafton Today: Diversifying at All Costs

Krafton’s trajectory is one we’ve followed closely, and it’s been nothing short of remarkable. Built on the runaway success of PUBG, the South Korean publisher has grown into a leading force in gaming and an increasingly active investor. With a $7.9 billion market cap and strong PUBG-driven growth, Krafton has built a solid base to expand its core business and pursue new opportunities.

Its foremost challenge is to grow out of its one-trick pony status, as the PUBG IP still generates approximately 80% of total revenue. The answer lies in diversification, which underpins most company initiatives:

• Maintaining PUBG’s cultural relevance as a franchise through collaborations and IP expansions, while broadening its reach through game mode diversification and UGC deployment

• Creating new franchises through a strong internal first-party production pipeline, while scaling up the existing portfolio (InZOI, Last Epoch, Subnautica, etc.), paired with extensive capital deployment to secure future opportunities and publishing partnerships

• Geographic diversification beyond Krafton’s home Korean market and betting on future growth regions such as India

• Diversification by sectors with investments in robotics, microdramas, ad tech, and AI

The publisher is uniquely positioned to lead current AI transformations. PUBG’s war chest gives Krafton the luxury of taking chances on emergent technologies. The company is further advantaged by its Asian roots, where consumers are significantly more receptive to AI. Finally, Krafton’s young, founder-led identity with a deeply embedded engineering culture supports the agility needed to embrace large-scale transformations.

Krafton’s AI shift is unique in that it is not an isolated initiative or a PR maneuver to temporarily lift stock prices, but rather a comprehensive lens through which the company meaningfully supports all core priorities.

A Novel Shift to an “AI-First Company”

Krafton’s AI transformation plan is pioneering in many ways. It is among the leading companies to formally adopt an “AI-first” mandate — both internally and externally. The investment is also sizable: Krafton committed 100 billion won (~$68M) in infrastructure investment and an additional 30 billion won (~$20M) earmarked annually for employee training. The transformation rests on four core components.

Company Transformation: C-level Governance and Comprehensive Deployment

Central to Krafton’s organizational shift is the elevation of Kangwook Lee — formerly Head of AI — to Chief AI Officer, giving AI a seat at the top table. This move consolidates clear governance and agency to set a company-wide AI strategy, allocate resources, and pursue long-term investments needed to achieve meaningful transformation. This appointment is paired with initiatives across all layers of the organization.

The company is rolling out efficiency-oriented frameworks and setting clear benchmarks to accelerate AI adoption across the organization. Resource allocation guidelines are being defined for each development stage with the goal of cutting costs by ~40%.

On the talent side:

• Significant commitment to AI talent: As of early 2025, Krafton reported around 80 engineers focused on deep learning and AI, with plans to add about 35 more. That compares to the company’s ~2,000 headcount, ~5% of the total workforce.

• Clear mandate across organizational layers: According to Kim Chang-han: “Starting today, KRAFTON will automate work centered on agentic AI, and employees will focus on creative activities and solving complex problems as we fully implement an AI-centered management system.”

Focus on empowerment: Krafton is committing ~$20M to employee education while deploying multiple initiatives to strengthen its AI-first culture.

On the infrastructure side, Krafton is investing in a proprietary GPU cluster designed to support frontier research initiatives. While this foundation reduces the company’s external dependencies and optimizes costs, frontier research is massively capital-intensive, which could be worrying from an ROI standpoint. Moreover, while ambitious, the scale of the investment ($68M) might fall short of the requirements to compete on a global scale with frontier AI Labs.

What sets Krafton apart is the rigor of its approach. The company is systematically embedding AI across every layer of the organization, backed by clear ownership and structure.

It’s still early, but initial results are notable: up to a 16× reduction in time per task for select art workflows and reduced reliance on external UI vendors. The real test will be whether these gains hold as AI is deployed across the full production pipeline.

In-Game Initiatives: Service Mentality Over Category-Defining Innovations

Krafton is already pushing AI into player-facing features. InZoi’s early access launch in March 2025 showcased features such as face capture, video-to-motion for custom emote creation, community simulation, and autonomous characters. Looking ahead, the roadmap is anchored around “in-game AI service enhancements,” spanning improved bots in PUBG, “Co-Playable Characters” (CPCs) designed to behave like human teammates, and AI-powered anti-cheat improvements.

Deploying AI features across a game with hundreds of millions of players is a meaningful milestone, but Krafton has been notably silent on more experimental AI applications. The company was also forced to backtrack on Project Windless, reaffirming a “traditional, craftsmanship-driven approach” following player backlash. As such, Krafton’s strategy appears deliberately cautious on the player-facing side. For its first-party content, this positions the company as a fast follower focusing on already commoditized applications — like AI NPCs used by Ubisoft, Tencent, and Epic Games — instead of chasing the first breakthrough in AI-enabled gameplay. On the other hand, the company is more aggressive through its investment and publishing initiatives.

National R&D Leadership: Incentives and Frontier Research Projects

Krafton’s expanding AI division, Krafton AI, is increasingly aligning with South Korea’s state-led technology ambitions — crystallized in the AI Basic Act, which plans ~$44B in private AI investments between 2024 and 2027. Common for Korean publicly traded companies as a means to support public–private partnership and state planning, Korea’s National Pension Service holds a ~6% minority stake in Krafton.

In April 2026, the company launched “Raon,” its own AI model brand, releasing four state-of-the-art open-source multimodal models spanning speech understanding, speech chat, text-to-speech, and vision encoding.

Krafton is also a founding partner for architecture and algorithms in SK Telecom’s government-backed Sovereign AI Foundation Model project, alongside institutions such as Seoul National University, KAIST, and chipmaker Rebellions.

Fundamentally, Krafton can benefit from the government paying for part of these initiatives. This can strengthen its core gaming business (such as deepening its edge as a gateway to the Korean gaming market), while nurturing a world-class AI lab that attracts and retains AI talent. That said, such projects extend quite far from Krafton’s purview, ultimately raising the question of focus. Is there actual business merit for Krafton, or is it a societal good but a business distraction?

Beyond Gaming Initiatives: Games as a Step to Larger Market Opportunities

Perhaps most surprising is Krafton’s use of AI to venture beyond its gaming roots, which it calls “Game for AI.” This approach harnesses Krafton’s deep gaming expertise, talent, and proprietary datasets to power expansion into new verticals, robotics in particular. It’s important to note that South Korea has the world’s highest density of industrial robots per employee.

Krafton’s move in robotics is centered around two complementary initiatives:

• Internally, Krafton has founded Ludo Robotics, a robotics company developing a “social humanoid brain” capable of powering broad physical AI applications.

• Externally, Krafton is joining forces with defense giant Hanwha Aerospace through a forthcoming joint venture. This combines Krafton’s software expertise with Hanwha’s industrial capabilities in robotics, space, and military domains. As stated by Krafton’s CEO, “We aim to grow the JV into a global defense technology company like Anduril.”

The vast troves of 3D environment data held by game companies provide an unmatched foundation for training world models that learn intuitive physics, object interaction, and cause-and-effect relationships from visual and action data. In robotics, these world models allow machines to simulate thousands of actions before transferring robust, real-world-ready policies to hardware. With the proper execution, Krafton can address market opportunities beyond gaming, though the initiative is likely to concentrate capital, talent, compute, and generally the company’s focus on other ventures.

Takeaways on Approaching AI Transformation Strategies

It’s still early, but Krafton’s approach shows what a serious AI transformation looks like in practice. Krafton’s strategy stands out for its ambition and its breadth, but it isn’t a universal template. The company is pursuing multiple initiatives at once — some capital-intensive, some highly competitive, and others with unclear near-term ROI. Parts of it will likely fail, but iteration over time is part of the process.

Just as importantly, much of Krafton’s approach is context-specific. The company operates under unique conditions as a founder-led, Korean company with large and steady cash flows, enabling moves like frontier AI research, robotics expansion, and alignment with national AI priorities. Krafton’s unique circumstances — enabling it to become an increasingly unique business — don’t transfer to everyone else.

And that’s OK. The real takeaway isn’t to copy Krafton’s strategy but to learn from and match its level of commitment to the future. That’s where most companies will fall short. We’ll return to Krafton’s results in time. For now, it sets a new pace for change — one others will have to match on their own terms.

Top News Items

Written by Devin Becker, Consultant at Naavik

Roblox releases agentic AI tools, promising the ability to “build a game with a single prompt.”

• Roblox shipped new agentic AI tools for Roblox Studio, headlined by an upgraded “Planning Mode” that turns a text prompt into a structured, multi-step game design document. The AI analyzes existing code and data models, asks clarifying questions, then executes across mesh generation, procedural model creation, and even autonomous playtesting. The AI now owns the full loop: analyzing existing code, generating meshes and models, asking important questions, and running autonomous playtesting that reads logs and self-corrects bugs. Already, 44% of top creators use AI tools, and Roblox is ensuring external systems like Claude and Cursor can plug into Studio via a built-in MCP server.

• The “single prompt game” headline is aspirational marketing; the real story is the practical shift from one-off prompts to a compressed plan-review-build-test loop, more closely mirroring how professional game development actually works. This continued democratization should catalyze further content volume growth, making quality discovery more important than ever. Despite enabling additional competition among developers, Roblox is already well-positioned here as it already manages recommendations across seemingly endless experiences.

Bring NPCs to life with AI-Powered conversations in Fortnite

• Epic Games launched “Conversations,” an experimental UEFN feature that lets Fortnite island creators build AI-powered NPCs capable of real-time, unscripted voice dialogue with players. Powered by Google’s Gemini 3.1 Flash-Lite and ElevenLabs’ voice synthesis, creators define a character’s personality using simple prompts, and the NPC handles the rest. This includes remembering player actions within a session, triggering in-game events, and even adjusting difficulty on the fly. This is the productization of the same tech behind Epic’s AI Darth Vader demo. It’s still experimental, so creators can’t publish these islands live yet, but clearly Epic wants conversational AI to be a native layer of the Fortnite ecosystem.

• One challenge is handling moderation at scale. Epic has already introduced guardrails such as banning romance bots, medical/mental health advice NPCs, and filter-bypassing personas. There’s also a significant cost factor as Epic is currently eating Gemini and ElevenLabs API bills during the experiment.

Latitude unveils Voyage, a platform for creating AI-powered RPGs

• Latitude, the studio behind the original AI Dungeon, one of the first consumer products to showcase generative AI as a gameplay mechanic, unveiled Voyage. This new platform lets players design and play AI-powered RPGs. Users describe settings, quests, mechanics, and villains; then the AI generates the world. NPCs are fully unscripted, remember player actions, and can be persuaded, manipulated, or befriended. The underlying “World Engine” took five years to develop and layers multiple AI systems for narration, gameplay management, character memory, and relationship tracking. During beta, players interacted with over 160,000 unique AI-generated characters and made nearly 3,000 gameplay choices on average.

• Moderation will be challenging, and the monetization approach of free-to-play with $15-$50/month subscriptions for unlimited actions and advanced AI features will be an important test case. If Latitude can prove players will pay meaningful subscriptions for AI-driven narrative experiences, it validates an entirely new business model. We’ll have to watch and see.

Is Brave New Wonders proof there’s a place for AI in indie games?

• Brave New Wonders, a factory-automation strategy game by City From Naught, uses AI as its central gameplay mechanic. Players command AI-powered automatons using plain-text natural language instructions, including instructions to explore, build, fight, transport materials, and automate production lines. The developer is emphatic that AI is used exclusively as a game mechanic, not in asset creation. Co-founder Shala Chen noted a frustrating irony: the game’s art looks so polished that players assume it must be AI-generated, when in fact the studio chose human artists precisely because AI output couldn’t match their quality standard.

• Brave New Wonders gives players new kinds of agency and expressiveness that were previously impossible in this genre. The natural language command system creates emergent complexity that traditional programming-based automation games (Factorio, Satisfactory) can’t replicate. Using AI to let players do things they couldn’t do before is a fundamentally different proposition from using AI to do things cheaper that humans already do well. Uses like this may come across as gimmicky at first, but it only takes 1-2 breakout successes to encourage more attempts.

Other News Items

• How Tencent is using AI to make fighting games more fluid

• Why Are Large Language Models So Terrible at Video Games?

• Character.AI’s new Books mode turns reading into roleplay

• Netflix plans to add a vertical video feed, use AI for recommendations

• How AI is powering Saudi Arabia’s video games industry

• Alibaba Moves Onto Tencent’s Turf With AI Model for 3D Video

• Panic won’t release Playdate titles that use certain forms of generative AI

• Tamatem acquires Playable Factory to expand into AI-enabled ad tech

• Firstpoint VC announces €50M fund to back AI-Driven gaming and entertainment startups

• AI Vector Vision says it can fix Nvidia’s DLSS 5 to look better with new vector tech

• Adobe embraces conversational AI editing, marking a ‘fundamental shift’ in creative work

• 43% of AI-generated code changes need debugging in production, survey finds

Content Worth Consuming

• Resurrecting a 1992 MUD with Agentic AI (Metavert Meditations)

• The Future of Agentic Game Creation Roblox Tech Talks (Tech Talks)

• One of the World’s Biggest Game Makers Reveals ‘the Uncomfortable Truth’ about AI (The Game Business)

• Why Google Cloud’s Jack Buser Thinks AI Can Save the Games Industry (GamesIndustry.biz)

• Video Game Lawyer Implores Devs to Understand Ownership and Swerve Generative AI (Game Developer)

• University of Bristol Study on Player Reactions to AI NPCs (University of Bristol)

For years, Naavik has been committed to open, rigorous thinking about the game industry. Today, we’re expanding that commitment with something new.

AI x Gaming is our dedicated coverage of artificial intelligence in the games industry. We’re launching it because, frankly, we think the conversation deserves better. Despite AI becoming one of the most consequential forces reshaping how games are made, there’s no single, reliable source tracking it with depth and consistency.

Every two weeks, you can expect an in-depth perspective on a meaningful AI topic in gaming, alongside a curated roundup of the key developments you need to know about from inside the industry and beyond. This is our editorial plan in plain terms:

• Balancing the short- and long-term view — understanding where AI tools stand today, not just where they might land in five years

• Business grounding — drawing actionable insights for studios and publishers navigating AI strategy and execution right now

• Continuous coverage — returning to topics as they evolve, aligning with the fast-changing nature of AI

• Data-driven approach — making sense of the sparse, often opaque information available on how AI is actually being used

Above all, we want this to be a conversation, not a broadcast. Let’s learn together. If there’s a topic you’d like us to dig into, a perspective we’ve missed, or a question you’re wrestling with, reach out — we mean it.

One housekeeping note: this newsletter is being sent to most Naavik Digest subscribers. If you’d prefer to stick with our core Digest, you can opt out of AI x Gaming at any time.

Let’s figure this out together!

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Navigating AI’s Execution Era in Gaming

Written by Francois Courset, Lead Consultant at Naavik

Charting the discourse around AI’s transformative role in gaming in 2026 means making sense of multiple contradictory market signals. Within a few weeks, Krafton announced a sweeping pivot to an “AI-first” organization while Take-Two quietly dissolved most of its AI division. AI now touches over 8% of all Steam titles, yet Tencent-owned Digital Extremes made the categorical promise that “nothing in our games will be AI-generated, ever.” Over $2 billion has been directed toward game AI startups to date, yet breakout AI stories all come from other industries, Emergent being the latest vibe-coding AI startup to cross the $100M ARR mark, walking in the footsteps of Cursor, Lovable, and Replit.

Three years after GPT-4’s commercial release unleashed the AI era, the gaming industry is torn between controversies around its use in creative processes, excitement about the future efficiency and gameplay innovation prospects, and the challenges that come with proper deployment and adoption. For this inaugural issue, let’s step back from the noise to map the terrain: understand the inevitable role of AI in gaming’s future, take an honest measure of where adoption stands today, and surface the execution and governance challenges the industry will need to embrace.

The inevitable role of AI in games

While AI for games is hardly new, Generative AI marks a shift in pace and nature shifting the technology from deterministic, scripted behaviors toward open-ended systems capable of producing fully realized worlds, characters, and systems on demand. Yet what makes this leap truly significant is that it comes precisely when the industry needs it most. AI offers a powerful framework to tackle gaming’s most pressing structural challenges:

• Slow industry growth: Following the post-COVID correction, gaming has settled into a below-inflation growth trajectory, forcing publishers to rationalize costs while urgently seeking new revenue levers. With live-service models now mature and past innovations like Battle Royale no longer driving market expansion, the industry is increasingly turning to Generative AI as a new frontier: one that could unlock fundamentally new gameplay propositions and reignite growth.

• Rising production costs and need for radical production efficiency: Game production, AAA in particular, faces ballooning costs for projects yielding ever-diminishing returns. Generative AI offers a framework for streamlining everything from asset creation and QA to localization, ultimately unlocking leaner, more sustainable production economics.

• Budget pressure is further compounded by competition from emerging cost-efficient markets. Emerging production hubs across Turkey, India, China, and Southeast Asia have local talent now capable of matching quality standards from mature gaming economies, leading to compelling cost arbitrage opportunities. AI-powered tools are empowering established hubs to dramatically amplify their output, narrowing the cost-benefit of moving production to more affordable markets.

To best map out AI’s potential — not to mention structure a strategy around it — it is essential to understand its different horizons, too often mixed:

• Short-term - Efficiency: Multiple AI-enabled tools are already mature enough to be deployed and provide significant production efficiency gains.

• Medium-term - Gameplay Innovations: Initiatives to leverage AI for the core gameplay experience are still at proof-of-concept stages. Yet as first consumer-facing attempts hit the market and find commercial validation, innovations and genres will be made possible through AI.

• Long-term - Industry Disruptions: AI provides a path toward significant industry shifts, by breaking down barriers to creation, radically altering the production process itself, or through the emergence of new AI-generated entertainment mediums.

Of course, AI won’t be the silver bullet single-handedly addressing all of the industry’s shortcomings, but its resonance with many of its core concerns, while providing a horizon for future disruptions, makes it impossible to ignore. AI adoption will happen despite the mob mentality pushback from gamers (85% of gamers have a negative opinion toward AI). It might not be a smooth journey for everyone (e.g., Crimson Desert or The Alters), but at some tipping point, the gains unlocked from AI likely outweigh the pushback. And any pushback isn’t likely to be permanent either; the world adjusts and moves on, as proven by previous technology adoption patterns.

Additionally, competitive pressures will eventually accelerate the need for AI adoption. Most teams not using best-in-class tech and operating less efficiently than others will lose relevance over time. Long-term survival depends on embracing the future.

The state of AI adoption in 2026

Generative AI’s penetration into the game industry over a three-year span has been unprecedented, though exact estimates vary across reports due to methodology and sample differences. According to the GDC 2026 State of the Game Industry report, 29% of game professionals are already using Generative AI tools as part of their day-to-day workflow, while 52% report their organizations have deployed AI tools somewhere across the business.

While impressive, a closer look reveals significant room for improvement:

• First, Generative AI is far less ubiquitous in gaming versus other industries. McKinsey’s 2025 State of AI survey reported that 79% of organizations used Generative AI in at least one business function.

• Second, the nature of adoption reveals that developers are overwhelmingly gravitating toward general-purpose tools (ChatGPT, Gemini, Copilot, etc.) rather than gaming-native solutions: only 5% of developers use specialized game development AI tools.

• Finally, AI penetration is already stalling, with GDC 2026 State of the Game Industry reporting a drop from 36% of game developers to 29% over the past year. This disengagement is likely tied to growing resentment toward AI with Omdia observing that close to half of game developers anticipate that AI will negatively impact the quality of games produced, up significantly from last year.

From a product standpoint, data tells a similar story. Generative AI has already achieved significant penetration, with 8% of all Steam titles and over a fifth of new releases publicly disclosing AI tool usage — figures that almost certainly understate reality, given the declarative nature of the tracking methodology and developers’ calculated silence to avoid player backlash.

Here again, some perspective is needed: While AI-disclosed games have collectively generated an estimated $660M in lifetime revenue, this is still a drop in the ocean compared to Steam’s $16B+ yearly revenues. Notably, the top performers in this cohort skew toward indie and AA titles, with the platform’s biggest franchises largely absent. Similarly, AI use for radical gameplay innovations is still pretty much at the proof of concept stage, with few games showing actual traction (e.g. Death by AI).

Unlike other industries where Generative AI has been embraced as a productivity tool, gaming’s identity as a creative-first medium creates unique frictions on the consumer side, as it reshapes the fundamentals of how the medium is being produced: 85% of players still have a negative bias toward AI-generated content.

Finally, from an organizational perspective, a clear acceleration can be observed, with a recent string of high-profile companies setting ambitious AI partnerships: Electronic Arts with Stability or Savvy with Humain, and others radically shifting toward so-called “AI-first” organizations such as Krafton or Appsflyer. It remains to be seen whether these announcements translate into meaningful organizational evolutions as companies tackle AI deployments and evolve isolated AI Labs R&D departments into company-wide AI adoption.

To further add context to these overall adoption trends, it’s worth noting that adoption is not uniform:

• Divergence by platforms: While console/PC are slow to adopt because they walk on eggshells with the mob of gamers, mobile and its A-B testing DNA is racing forward with AI experimentation much faster, with UGC as another fertile ground for AI deployment. Examples include Supercell’s dedicated AI strategy, King’s AI Labs, or Kwalee’s early Employee Program “KAI.”

• Divergence by regions: Asia (and China in particular) is moving way faster than the West, due to a deeper product-driven approach to game development, major tech conglomerates with game production arms allowing for significant R&D investment, and fewer consumer frictions around AI usage. Examples include NetEase’s “Foundational Competency” approach to AI, or Krafton’s “prioritizing AI as a central and primary means of problem-solving.”

• Divergence by use cases: There’s obviously a big difference between using Generative AI for localization versus deeper 3D assets or player-facing gameplay interactions, so the quality of AI usage is key to track. Noting here that AI use cases go beyond solely generative ones: automate processes, performing tasks, handling decision-making logic, etc.

Far from disproving the technology’s potential, looking at adoption patterns highlights the significant road ahead for meaningful AI deployment.

The roadblocks to executing on AI’s promises

Despite robust early adoption, the industry has been surprisingly slow to produce a defining AI breakthrough, contrasting with its pioneering role in previous technological waves like VR, 3D graphics, or online social connectivity. This can largely be attributed to unique challenges tied to the nature of game production:

• Games require complex production pipelines, hosting multiple disciplines under one roof, with each subdomain having different AI tooling, quality standards, and integration challenges.

• Games’ multi-year development timelines lead to natural inertia for adopting new technologies.

• While AI’s output is typically judged on correctness, game assets are evaluated aesthetically while also requiring lore-accuracy and consistency, both creating significant overheads and limitations.

• Games are fundamentally real-time and interactive, creating challenges with computing time and latency constraints to deploy live, player-facing AI tools.

• For AI usage in gameplay, the business model is still unproven, as studios may need to put the commercial burden of computing credits on the end customer.

• As a creative endeavor, game production comes with unique cultural barriers that aren’t found across other industries. This creates additional layers of friction from gamers hating on AI use, and reluctance for employees to adopt technologies altering the very process of making games.

On top of these foundational challenges, multiple ongoing trends further complicate execution in gaming:

• As mentioned before, the industry is in a low-growth phase, which makes it increasingly challenging for studios and publishers to meaningfully commit budget to R&D while their core businesses and teams are often contracting.

• Few companies have dedicated change management teams or organized technology and tooling oversight, making it challenging to deploy experiments, but also for startups developing new tools to properly access and engage with prospective clients.

• AI talent is scarce, and the tech sector’s faster pace and deeper pockets is more competitive at acquiring talent than the gaming industry. For example, Google recently acquired three startups to bolster its DeepMind world model team, including Common Sense Machine, previously a 3D asset creation tool for games.

Once again, these roadblocks aren’t as prevalent across categories and verticals. Fundamentally, AI could be approaching another phase of its hype cycle, and as such, the narrative should shift from understanding future potential to figuring out how to actually make some of the promises work today. The road ahead is one of execution, iteration, and trial and error – and future winners will be those ready to do their homework and fully embrace these challenges.

Unlocking the next phase in AI deployment

What is the next step to deepen AI adoption in gaming?

First, a lot of the change is already happening. Mobile studios are fully embracing AI tools, Roblox has also made significant strides toward AI, and Asian companies have already radically shifted their production processes. As such, it is less about unlocking the next phase at all and rather about it being unlocked more evenly.

Second, gaming needs to find its first “Aha!” moments acting as measurable proof for the technology’s potential. Steal a Brainrot, for example, was a strong signal that gamers were ready to embrace AI-native IPs in entertainment. The industry needs to find similar validations.

Third, the AI narrative within the industry must continue to evolve. Over the last six months, companies have signaled a shift in tone — from one of secrecy and expectation management to one of clear transformation strategies and measurable initiatives — through significant organizational changes and public communications about their AI plans. However, the industry still needs the courage to proactively address and reshape gamers’ perceptions of AI. Miscommunication and poor management continue to fuel unnecessary controversy.

Gaming companies will need to evolve from isolated experiments toward clearly outlined transformation strategies, and from change management initiatives to company-wide AI governance. The current transformative potential of AI lies in a multitude of small use cases across disciplines and divisions. This requires intentionality, clear measurement, and understanding of the state of the art to identify and deliver in places where AI brings the most benefits.

Small companies should be embracing it from the ground up so they can better punch above their weight and compete with larger companies, whereas larger companies are the ones who need to radically shift their thinking and initiate large-scale transformation strategies. Inertia and willingness to innovate will define market winners for the coming years. Ultimately, the era of AI should be an era for elite small teams to achieve more than ever before and innovate in new ways that haven’t been possible in years.

Centrally, execution starts with a plan, which is exactly why Naavik launched its AI consulting vertical. If you’d like to dive deeper into AI trends, want advice on what tools and companies to work with, or need a partner to support your company’s transformation, please reach out directly or through our contact form. Let us know if we can help!

Top News Items

Written by Devin Becker, Consultant at Naavik

Owlcat Games discusses its GenAI usage on The Expanse:

• Owlcat clarified its usage of GenAI in a recent interview, stating that it is not using any AI for its existing Warhammer or Pathfinder games (both based on tabletop game franchises) but is for future games. The stated uses are for prototyping, placeholder tests, quick iteration tests, creative search/inspiration, and vision coordination before starting conceptualization.

• While it emphasized that everything in the final product will “definitely be 100 percent human-made,” there’s a potential risk in simply forgetting to remove placeholders from the final product. The most recent game to fall into this trap was Crimson Desert, which resulted in a public apology and push to replace that content. Other popular games that saw similar incidents, like Clair Obscur: Expedition 33 and Anno 117: Pax Romana, show how easily this can happen.

• Using GenAI to improve game development is not inherently wrong, but risks arise from its appearance in the released product, especially on console/PC. The online mob mentality and aggressive media coverage greatly exaggerate the issue, especially since AI-generated placeholders are less obvious than typical ones, often slipping through QA.

• Developer transparency about GenAI use, while theoretically good, can backfire, as players often misidentify human-made assets as AI-generated. This is becoming a common problem, forcing developers to issue increasingly difficult-to-prove statements to counter player suspicions, escalating tensions.

• Why does this matter to AI x Gaming: The console and PC gaming sectors face friction as AI's benefits for game creation clash with core gamers' strong rejection. Developers are attempting transparency to bridge this gap, but a prolonged period of tension is expected. Whether studios like Owlcat will face a backlash is uncertain, but the hope is that gamers will eventually adopt more reasonable expectations for AI's role in development.

Take-Two Lays Off AI Lead and Team Members

• Several news outlets recently reported on the head of Take-Two Interactive‘s AI team being laid off, along with a number of other teammates. This was reported as a major deal, especially because Take-Two had been so publicly bullish on GenAI. What was overlooked by most of the reports was that the AI group (based on the lead’s LinkedIn post) was focused on other non-GenAI forms of AI, such as procedural generation and machine learning.

• No further details have emerged about the layoff and any related internal departmental changes, so further commentary is speculative. Was it purely budget-driven? Is Take-Two leadership less bullish on this form of AI usage? Or was this structure, as a centralized team, just the wrong one for Take-Two’s diverse, sprawling business? We suspect the latter, but it’s hard to say.

• Why does this matter to AI x Gaming: Large companies often struggle to manage technological change. Unlike small teams, which are easier to get everyone moving in the same direction, large companies aren’t as nimble and have to think through structure and process to a larger, more complex degree. Take-Two clearly isn’t giving up on AI at large, but these hiccups show that transformation could prove tough for other big, traditional publishers as well. Expect more leading companies to adjust their approaches to AI in the months and years to come.

InnoGames Gives AI Life Support to Sunrise Village

• Due to declining revenue and users, InnoGames was close to shutting down its mobile F2P farming cozy game, despite it still making $160-$190k a month. Now, thanks to GenAI, the team built a strong AI pipeline to keep the live-ops going with just a 2-4 person team, while the other 20+ team members moved to a new project.

• The pipeline is built around a Unity-integrated AI Stage Designer using multiple LLMs (notably the older, deprecated OpenAI GPT-4o) to generate storylines and quests, balance progression and rewards, search and tag assets, design layouts, place objects, and create basic cutscenes in six structured steps. AI also auto-labels around 10,000 visual assets in Sunrise Village, turning what used to be hours of manual browsing into seconds by enabling semantic search like “cozy fireplace” or “autumn tree.”

• In this model, the artists aren’t replaced; instead, they are the ones prompting, curating, and correcting the AI outputs — resulting in ownership that maintains quality, reduces the need for long production periods, and frees up more time for the art team. Creating this process took roughly two months of focused engineering work, and it’s now being improved and rolled out to other projects, including those that are still in growth phases.

• Why does this matter to AI x Gaming: Players’ aversion to GenAI in games is mostly around two things: replacing human artists and a drop in quality. InnoGames shows that not only can teams avoid both of those issues, but that it’s possible to keep live service games going far more efficiently. Since mobile is in a much stronger position to capitalize on these efficiency gains, more mobile companies will integrate similar processes.

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Other News Items

• Capcom says it will use Generative AI to speed up production

• Verse8 raises $5M for AI-driven game creation platform

• Sony to acquire AI and computer vision company Cinemersive Labs

• AI tech designed to end video game leaks for good uses watermarks hidden “in plain sight”

• Meta’s new model, Muse Spark, catches up on benchmarks and pivots away from open source

• The Gemini app can now generate interactive simulations and models

• Indie developer refuses to talk about the game for fear that AI will share his ideas with others

Content Worth Consuming

• “More time innovating; less time writing code:” Arc Raiders publisher Nexon believes AI will liberate its workforce (Game Developer): “Nexon CEO Junghun Lee offered more details on the company’s AI strategy, which revolves around an initiative dubbed ‘Mono Lake.’ Mono Lake is billed as an ‘end-to-end intelligence’ platform capable of weighing in on every single production decision. Nexon said the technology has been trained on billions of player sessions and decades of live game data, including engagement patterns, retention and monetisation habits, and live game telemetry. According to Lee, that vast dataset is what separates Mono Lake from other AI platforms.”

• The First AI Game Creator’s Brutal Truth About Game Dev (GameMakers): “The creator of Suck Up — the first commercially successful game using AI at runtime, with 100M+ YouTube views and $0 in marketing — breaks down what AI actually does and doesn't do for game development. Ran Mo (CEO of Proxima, ex-EA/YouTube/BCG) live demos AI-assisted coding in Unity, explains why vibe-coded games are architecturally unusable at scale, and shares his controversial take: AI in actual gameplay is probably overhyped, even by the guy who built the first AI game. We cover the trunk vs. leaves framework for deploying AI in your codebase, why the 80/100% gap in games is worth $100 million, the power law that's about to crush mid-tier studios, and why Ran hired a head of marketing with 1M TikTok followers instead of a brand marketer.”

• Project Glasswing: Securing critical software for the AI era (Anthropic): “We formed Project Glasswing because of capabilities we’ve observed in a new frontier model trained by Anthropic that we believe could reshape cybersecurity. Claude Mythos Preview is a general-purpose, unreleased frontier model that reveals a stark fact: AI models have reached a level of coding capability where they can surpass all but the most skilled humans at finding and exploiting software vulnerabilities. Mythos Preview has already found thousands of high-severity vulnerabilities, including some in every major operating system and web browser. Given the rate of AI progress, it will not be long before such capabilities proliferate, potentially beyond actors who are committed to deploying them safely. The fallout—for economies, public safety, and national security—could be severe. Project Glasswing is an urgent attempt to put these capabilities to work for defensive purposes.”

• Industrial Policy for the Intelligence Age: Ideas to Keep People First (OpenAI): “In just a few years, AI has progressed from systems capable of fast, narrow tasks to models that can perform general tasks people used to need hours to do. Now, we’re beginning a transition toward superintelligence: AI systems capable of outperforming the smartest humans even when they are assisted by AI. No one knows exactly how this transition will unfold. At OpenAI, we believe we should navigate it through a democratic process that gives people real power to shape the AI future they want, and prepare for a range of possible outcomes while building the capacity to adapt. That’s what this document is for—to start a conversation about governing advanced AI in ways that keep people first.”

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