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View all search resultsWho controls the data, controls the future
AI now sits inside finance, defense, health care and public administration, and it runs on two things most governments do not actually control: the data that train it and the compute that processes it.
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The construction of Digital Edge Indonesia data center in Cikarang, West Java, is underway in this undated picture. State power producer PT PLN is set to supply 2x 725 megavolts of electricity to support the operation of the country’s largest data center. (Antara/PT PLN)
I
n March, Iranian drones targeted three Amazon Web Services (AWS) facilities in Bahrain and the United Arab Emirates, hitting two directly and nearly hitting the third. It was the first time a commercial data center had been a military target, yet almost nobody outside specialist circles noticed. They should have. The servers holding a country’s data, and the chips running the artificial intelligence models on which its economy increasingly leans, are no longer background infrastructure. They are as strategic as ports or power grids, and just as exposed.
For most of the last decade, data was something companies mined, and AI was something companies sold, both regulated at the margins through privacy law, if they were regulated at all. This framing no longer works. AI now sits inside finance, defense, health care and public administration, and it runs on two things most governments do not actually control: the data that train it and the compute that processes it. Countries that ignore this will find their futures being decided in boardrooms where they have no seat.
Many governments have taken note. Global spending on “sovereign AI” will reportedly surpass US$100 billion this year. Over the last several months, Canada, France, Saudi Arabia and the UAE have rolled out national compute funds and GPU allocations. The European Union has gone further, treating sovereign AI infrastructure almost as doctrine, which has meant backing Gaia-X to build out European data infrastructure and financing projects like Mistral AI’s new data center outside Paris.
On paper, this looks like sensible diversification away from a handful of United States and Chinese firms. In practice, it risks creating something more brittle: a patchwork of national fortresses, each self-sufficient and none capable of talking to the others. Part of the problem is that “AI sovereignty” encompasses at least three things, and most governments are only working on one.
Data residency, keeping citizens’ data within national borders, is the oldest of the three, the easiest to legislate and the one most policy actually addresses. Compute sovereignty, who owns the chips and data centers doing the processing, is more difficult: a country can wall off its data, but it loses control if those data are processed on infrastructure someone else owns. Governance sovereignty, the ability to set the rules AI systems have to follow, rather than importing whatever standard the country hosting the dominant developers happens to set, is the one almost nobody talks about.
A fragmented regulatory landscape does not help any of this. Roughly 90 countries now have some kind of national AI strategy; at least 33 have passed binding legislation. But the approaches often clash. The EU’s AI Act, whose main provisions became applicable last month, carries penalties of up to 35 million euros ($40.6 million) or 7 percent of the offender’s total global annual turnover. The US AI Action Plan takes the opposite approach, treating deregulation itself as a competitive edge. China’s Global AI Governance Action Plan offers cooperation on AI governance with developing economies, but on Chinese terms.
The Council of Europe’s Framework Convention on AI, the first binding international AI treaty, represents real progress, but its enforcement is modest next to the scale of what it is meant to govern. Coordination beyond that has barely started. The United Nations’ Independent International Scientific Panel on AI has warned of a “race to the bottom,” with jurisdictions competing to offer the most permissive rules rather than the safest ones. Companies running high-risk AI deployments are already shopping for the softest jurisdiction.
