AI in Video Games: Own the Loop - by Chirag Vadhia

AI in Video Games: Own the Loop

How AI is about to reshape what it costs to make a game, and why a studio keeps its value only if it owns the learning loop, not the model that runs it.

Chirag Vadhia

Jun 16, 2026

TL;DR

The question is the loop, not the AI model

On 15 June 2026, Satya Nadella set out a distinction that had nothing to do with games and everything to do with what is about to happen to them. Every company, he wrote, will have to build two kinds of capital: human capital, the judgment and pattern recognition of its people, and token capital, “ the firm’s AI capability it builds and owns.” The prize is not picking the best model but building a learning loop on top of one, where the two compound. As he put it: “ You can offload a task, or even a job, but you can never offload your learning.”

What he calls token capital is made of specific, ownable parts: the evaluations a company writes to encode its own standards, the reinforcement it runs on its own accumulated information, the queryable memory of everything it has done before. Build that, and the generalist model underneath becomes a swappable part; you can change it for a better one and lose nothing, because the expertise that matters has been captured in the loop rather than rented from the model. Fail to build it, and the reverse happens. The work flows through someone else’s model, the learning accrues to them, and your craft is slowly commoditised into it.

That was written about software companies and enterprises, but it is a precise description of what AI is about to do to a game studio. For what it’s worth, AI does not arrive at the deterministic core, the movement, the combat feel, the shared simulation every connected player must agree on; the engine is the safe part. It arrives in the content and tooling stacked around that core, the art, the levels, the dialogue, the testing, the Live Services treadmill that keeps a world fed for years. That layer is what a studio spends its budget on, and as it moves to models, the question Nadella puts to every other industry is the one that now decides a studio’s worth: does it own the loop, or rent the intelligence and let the value flow upward to a few models that, in his words, “ eat everything they see”?

Part 1. How a studio keeps its value: it owns the loop

An owned loop works at two levels, and GW3 shows both.

The content treadmill becomes a flywheel

A great example of a single function run as a loop is with Live Services: the seasons, events and updates a persistent world needs to keep players paying attention for years after launch. It is the clearest place to see what owning a loop means, because the same grind can be run two ways, and the two pull apart a little further with every cycle.

This is what a Live Services loop could look like for GW3:

Each cycle leaves the studio with more of its own production data than the last, with a more exact set of evaluations and models that are tuned a little more tightly to its world. This alters the way in which Live Services content can sharpen development over many years as the data from the asset compounds. Making extremely long-life content that spans over a decade can create a flywheel that becomes a moat.

In order to achieve this, none of this actually requires ArenaNet to train a model of its own. The generation and the learning run on commodity models rented from whichever lab leads the quarter.

So what the studio owns is the wrapper around them: the evaluations, the information, the models adapted on its own back catalogue and the memory of its own world.

The whole game feeds one owned core

Live Services are an example of just one loop, but a game the size of GW3 inherently runs dozens: concept art has a loop, encounter design has a loop, so do dialogue, localisation, the balance pass, and the bug triage, and so on.

If each of these parts of development aren’t communicating effectively, then each method for developing effective loops can be radically different (i.e. each loop could be running a different vendor’s tool that is learning a slice of the game and keeping what it learns). So a studio that decides to use external tools this way ends up renting its own craft back from a dozen suppliers, none of whom hold the whole picture and all of whom improve on its work.

What turns those scattered loops into something the studio owns is a single core beneath them, the thing Nadella called token capital, and for a game it has five parts:

A deep IP fails in a particular way under generic AI: the output is fluent and slightly wrong, a sword that is not quite a Guild Wars sword, a character speaking half out of voice, a quest that quietly breaks old lore.

The queryable canon and the taste evaluations are what catch that, and they only work if every loop draws on the same ones. The shared core is also what keeps the functions consistent with one another, the dialogue agent and the quest agent and the art pipeline all answering to a single record of what is true in the world. If you run a dozen rented tools instead and there is no shared record, the world drifts with each function plausibly off in its own direction.

Owned this way, the whole Live Services life of the game feeds one asset. Every season of content, every fixed bug, every million hours of play thickens the same core, and each function improves because the others did. That is the difference between AI making GW3 more itself across a decade and AI scattering the studio’s craft among the suppliers it rents from.

The loop costs before it pays, and few studios can build it

Set against renting, owning the loop looks worse before it looks better. The adapters, the evaluation suites, the information pipelines, the canon memory all have to be built and staffed before one iteration of the cycle can begin to compound, and the compounding only shows after several seasons of play have run through them.

A studio that rents the equivalent tools pays less in year one and ships at much the same quality; the gap opens later, if it opens at all. The financial model in the previous piece ( See: AI won’t make video games materially cheaper to develop) put the realised AI uplift at about three points of operating margin, well under the optimistic case once the offsets are counted, because a large part of the gross saving leaves again as tooling spend, paid straight to the vendors whose models do the work. The loop is an investment with a J-curve, not a discount that lands at launch.

Most studios also cannot build it. Studios do employ machine-learning engineers, for matchmaking, anti-cheat, animation and analytics, but building a generative loop is a newer and narrower discipline: evaluation design, reinforcement learning on a studio’s own information, and the data plumbing to feed them. That talent is scarce and expensive and competed for hardest by the labs themselves, and standing up the pipelines to turn raw play into usable information is its own programme of work. This, more than any argument about whether owning beats renting, is why most studios will rent: not because the loop is a bad idea, but because they have no way to staff one. The capability sorts the industry by size, and the lab deal is where that sorting is paid out.

And even a loop built and owned in full sits on ground the studio does not own. The commodity model at the base runs on someone else’s cloud and someone else’s chips, rented by the hour from the handful of firms that operate them. A studio can own every part of the wrapper, the taste, the information, the canon, and still depend on Azure or AWS, and on Nvidia beneath them, for the compute that makes any of it run. Owning the loop is sovereignty on one axis, what the studio knows and keeps. It says nothing about the other, whose platform it all runs on, and that second axis is where the lab deal does its work.

Part 2. The lab deal, and who ends up owning the loop

Every lab deal turns on one question: who keeps the core

A studio that cannot build the loop (which is most of them) gets one another way. It makes a deal with a firm that can, the frontier labs. There are four different ways in which a deal like this could occur, and the most important variable that matters is who owns the core when the deal is done, because that is the asset that compounds, and everything else is effectively terms around it.

The four methods are:

Where on that spectrum a studio lands is set by its leverage, and leverage here means whether it can say no.

What gives the studio leverage, and pulls the deal left:

What gives the lab leverage, and pulls the deal right:

A studio’s strongest card, a unique world full of players, is worth most to a lab exactly when the studio is healthy enough not to have to sell it. The two move together, which is the trap. Distress forces the sale, and distress also strips the card of its value, because a forced seller cannot hold out for the price the asset would otherwise command. So the deals that cede the most loop tend to be struck by the studios whose asset was worth the most, sold cheaply because they had to. Which model a studio can pursue is decided years before the lab ever calls, by whether it stays fundable enough to keep the choice open: a healthy studio with a world the labs want can choose to cede the loop at a price that reflects it; a distressed one does not choose at all.

EVE Online, a twenty-year world, becomes the lab’s training ground

EVE Online is the kind of environment a frontier lab cannot build for itself. For more than twenty years it has run as a single shared universe, one world rather than thousands of copies, where hundreds of thousands of real players run a real economy, fight wars that last months, and build, infiltrate and betray alliances. It is precisely what today’s AI handles worst: long horizons, a world that never resets, thousands of players pursuing their own goals at once, consequences that compound over years. Those are the problems DeepMind has named as the hardest in building capable agents, long-horizon planning, memory, and continual learning, and a world like this exercises all three. A lab can spin up a simulated economy. It cannot spin up twenty years of real people learning to outwit one another inside a single one.

On 6 May 2026, CCP Games, the Icelandic studio behind it, was bought out of its Korean parent, Pearl Abyss, by its own management and a group of long-term investors, for $120m, and rebranded Fenris Creations. Google DeepMind took an undisclosed minority stake in the deal, and with it the right to run an offline copy of EVE on its own servers.

The announcement framed it as a homecoming from a position of strength. The filed accounts describe a managed exit from a loss-making, indebted business. This is the condition from the previous section made concrete: a genuinely rare asset, a twenty-year player-driven world at record revenue, parting cheaply because the entity that held it could not hold out and its owner wanted out.

Access to that world is what changed hands, whether you describe it as an environment to train in or as the behavioural record of everyone who has played. By the spectrum’s equity test this was a minority stake: management kept the company, the IP and the production loop. But the equity is not the core of it and what CCP ceded is the right to learn from that world.

Owning the loop is only half the sovereignty

The spectrum measures one axis: who owns the loop. There is a second, and EVE only sharpens it. Even a studio that keeps its core in full does not own the ground it runs on. The models underneath are rented from a handful of labs, the compute from a handful of clouds, and the engine, in GW3’s case Unreal, is licensed from Epic. A studio can own everything it learns and still depend, at every layer beneath that, on companies it does not control. Sovereignty has two axes, what you own and whose platform you own it on, and almost no one in games holds both.

The owners of that second axis take their cut without owning any studio’s loop. Epic is the clearest case in games: it owns Unreal, the engine a large part of the industry builds on, and keeps extending it by rolling up the tools and middleware around it. GW3 runs on Unreal, so Epic earns from it whether or not ArenaNet ever owns its own loop. A large publisher can avoid that toll by building its own engine, as EA does with Frostbite, but owning an engine for your own use is not the same as owning a platform others build on, and it still leaves the cloud and the models rented. The platform-owner’s position is one no studio reaches by owning its loop.

Nadella’s framing is right about the first axis and quiet about the second. The durable asset is indeed the loop, the thing a studio builds and keeps. But he would also like to own the second axis, the model you rent, the cloud you run on, the platform you build the loop atop. Telling studios to own their loops costs him nothing if they build them on Azure, on the models he supplies, on the terms he sets.

For GW3 the choice is NCSoft’s, and it is the first axis that is still open. NCSoft can fund the game, which means it can keep the loop if it chooses to build one, rather than take the EVE shape because it has to. The second axis is already half decided: the game runs on Unreal, and on whatever cloud and models sit beneath it. The most a studio in its position can do is own what it learns. Whether ArenaNet does is the question the next two years will answer, and it is a choice, not a forecast.

Own the loop, or be commoditised into it

The choice was never whether a studio uses AI because the reality is that every studio will. It is whether it owns what the AI learns or hands that to whoever it rents the model from. Most studios cannot build that capability for themselves, which is why the lab deal exists, and why the deal’s structure, not its label, decides who ends up with the core.

For an investor, this reframes the question to ask of any game in an AI world. Not whether AI will cut its costs, which it will, modestly, but whether the studio is building an asset it owns or renting one it does not. NetEase has built its own AI capability and runs rented models like DeepSeek’s underneath it; CCP, out of money and out of options, did the opposite, and a twenty-year world became someone else’s training ground.

GW3 is a great example of where the choice is still open. NCSoft can fund the game, so it can keep the loop if it decides to build one, and whether it does would be an interesting event to see for GW3.