Who Gets to Own AI?eric

In the second post in this series I argued that whether AI ends in a surveillance state or a shared prosperity comes down to one lever above all: keeping ownership wide. If the gains from the machines are broadly held, the inequality that drives the whole repression calculus never reaches the danger zone. Nice theory. A fair reader replies with the obvious objection, and it is a good one.

How, exactly, is a small player supposed to own any of this, when frontier AI is one of the most capital, hardware and energy hungry things humans have ever built? When only a couple of companies, in only a couple of countries, can even make the stuff? "Keep ownership wide" sounds lovely right up until you look at the electricity bill.

So let us take the objection seriously, because it is half right.

The factory is concentrating, and not just into companies

Start with the money and the power, literally. The four biggest US hyperscalers spent around 413 billion dollars on capital expenditure in 2025, up roughly 84 percent in a year, and are on track for 600 to 700 billion in 2026. Anthropic has estimated that a single frontier training run will need something like five gigawatts of power by 2027. Several gigawatt-scale data centres come online this year, one per hyperscaler, and OpenAI's build-out alone is measured in the hundreds of billions. The binding limit is no longer chips or money. It is electricity.

Now widen the lens from companies to countries, because this is the part people miss. Genuinely frontier AI is, right now, a two-nation game. The United States leads; China trails by a matter of months and closed the model-quality gap to under three percent in early 2026, while already manufacturing roughly 85 percent of the world's humanoid robots. Europe wrote the world's first serious AI law and is backing a national champion, but sits well behind on both models and compute. Everyone else is downstream.

And underneath even that there is a narrower chokepoint still: the chips. The design and manufacturing chain, from Nvidia to TSMC to ASML's lithography machines, is controlled by the US and a small circle of allies. By one estimate China's Huawei will produce about four percent of Nvidia's compute this year. Whoever controls the machines that make the machines controls who gets to build at all.

Put those three layers together, companies, countries, chips, and you get the sharpest possible version of the worry from the last post. The most powerful capability in history is being built by perhaps five firms, in two states, on a hardware base a handful of companies gatekeep. That is not a widely owned technology. That is the most concentrated one imaginable.

The endgame worry, stated plainly

Follow that line to its end and you get the scenario worth naming out loud. If frontier capability, the chips beneath it, and the robots that give it hands all stay this concentrated, and if states then move to control them directly, through national champions, export bans and the kind of "AI Force" framing that treats the technology as an instrument of national power, then the most consequential tool humanity has built could end up effectively owned by a handful of actors. And the previous post already showed the incentive that concentrated capability creates: when watching and controlling a population becomes cheap, the powerful are tempted to choose control over care. A world where only a few can build the thing is a world where those few decide what it is for. That is the cyberpunk ending at global scale.

I am not going to pretend that is impossible. It is a live path. But it is not the only one, and the reason is almost funny.

The product diffuses, and rivalry is what pries it open

Here is the fact that breaks the clean pessimism. You do not need to own the factory to own the use of what it makes.

Open-weight models, the ones whose weights are published so anyone can download, run and fine-tune them, are now within striking distance of the closed frontier on most real work: coding, summarising, extraction, classification, ordinary reasoning. You can run them on your own hardware with no per-token rent, and hosted open-model inference already runs five to ten times cheaper than the frontier APIs. The closed labs keep an edge on the hardest reasoning and the longest agent chains, but for the overwhelming majority of what a person or a business actually needs, good enough arrived, and it arrived ownable.

And notice who is handing out that capability. The open models keeping everyone else in the game come largely from China, from DeepSeek and Qwen, alongside Meta's Llama in the US. That is not charity. It is strategy. China open-sources partly to undercut the American closed labs, win developer mindshare and set standards. Which produces a genuinely strange result: the same great-power rivalry that concentrates the frontier is, right now, the thing prying the technology open for the rest of us. Last year's two-hundred-million-dollar model is this year's free download you run on a box in the corner.

So the honest picture is two opposite motions at once. The factory concentrates. The product diffuses. The frontier pulls away at the very top while a fully capable version of last year's frontier falls into everyone's hands. Both are true, and the future belongs to whichever one wins.

So what can you actually own?

Not the factory. Not the chips. If you are not one of two states or five companies, that ship has sailed, and chasing it is a waste. What you can own is everything the factory is an input to:

• The weights, not just the tap. Running an open model you hold beats renting an API you can be cut off from or repriced on.
• Your compute, where it counts. Local and on-premises inference for the work that is sensitive, constant or core, cloud for the rest.
• Your data. This is the one that compounds. Your data trains your advantage or it trains the landlord's. Only one of those is ownership.
• The last mile. The workflow, the judgement, the customer relationship, the specific problem solved. A thin wrapper on someone else's model gets disintermediated. A real application built on your own data and expertise does not.

The old analogy still fits best. Generating electricity concentrated into a few enormous utilities, and it never handed all the power to the power companies. The value moved downstream, to everyone who owned an appliance, a workshop, a business that ran on the current. Nobody needed to own a power station to own a factory. AI can run the same way, the frontier as a commodity input and the value spread across everyone who builds on it, but only if we let it.

The catch is the same catch as before

That "only if we let it" is the whole game, because the diffusion is not guaranteed by physics. It survives only while three channels stay open: the gap between frontier and open stays a matter of months rather than years, open weights keep being released and stay legal to use, and compute and chips stay accessible enough that running a model is not itself a privilege. Every one of those is a political choice, not a law of nature.

And every one of them can be closed. Export controls can widen the gap on purpose. Foreign open models can be banned on security grounds. Chips can be rationed. National-champion policy can ring-fence the frontier behind the state. The rivalry that opened the channel can, with one turn of the security ratchet, slam it shut, and then the handful of actors who own the factory own everything, not because they out-competed you, but because the door was closed by decree.

That is the real fight over who owns AI. Not whether you can afford a graphics card. Whether the channels that let capability diffuse are kept open or allowed to close. You will never own the factory. Neither will your country, unless it happens to be one of two. But you can own the work, and for now the trend is on your side, and the only way to lose that is to be told it was never possible and to stop paying attention.

We built the brain. We are building the body. Owning the outcome was always going to be the hard part, and it was always going to be a choice.

Last in this series: everyone is braced for a superintelligence that turns on us, but the AI catastrophe that already almost happened this spring looked nothing like it. Skynet is the wrong thing to fear first.

Sources

• BCG: The Great Divide, how the US and China are splitting the AI world
• Chatham House: How middle powers can weather US and Chinese AI dominance
• Brookings: Global energy demands within the AI regulatory landscape
• DigitalApplied: Open-weight models H1 2026 recap (DeepSeek, Qwen, Llama)
• Earlier in this series: The End of AI Is a Political Choice, Not a Technical One