The Growing Concern Over AI Sovereignty
Aidan Gomez, CEO of Canadian AI company Cohere, has long been concerned about the potential for foreign governments to cut off access to advanced AI models. This concern was validated earlier this month when the U.S. government moved to restrict foreign access to Anthropic’s Mythos. For Gomez, this event highlighted a critical risk: centralized dependence on a single entity is a structural vulnerability.
“Everyone has now realized that the reality is that centralized dependence on a single entity is a structural risk,” he said. “You can have access revoked and services shut down.”
The U.S. has historically led the global AI race, controlling vast computing power and hosting most of the leading frontier labs. China is its closest rival, with both nations accounting for 90% of the world’s computing power, according to data from AI research firm Epoch AI. Outside the U.S.-China axis, the field of frontier AI developers is more limited. Companies like Cohere, founded in Toronto in 2019, and Paris-based Mistral are among the few prominent players building large-scale models outside the U.S.-China dynamic.
As AI becomes increasingly integrated into critical systems—such as hospitals, financial markets, military logistics, and public services—the question of who controls this technology and who can switch it off is becoming a matter of national strategy.
The Case for Sovereign AI
Gomez argues that democracies need to stop relying on foreign providers for critical AI and instead build sovereign systems they can control end-to-end. In practice, this means owning or having control over the full chain of components an AI system depends on: data centers, the chips inside them, and the models themselves. Rather than paying another country’s company for access via an API, companies should run models on their own infrastructure.
“This sentiment of renting AI from someone rather than owning it is a national security risk,” Gomez said. “You need to fully control it.”
Cohere already offers its models in a way that allows governments and companies to run them entirely on their own infrastructure. Instead of sending data to Cohere’s servers, customers receive the model and the software needed to deploy it within their own data centers, including on systems that are physically disconnected from the internet and to which Cohere has no remote access or ability to revoke service.
Defining Sovereign AI
The term "sovereign AI" has become a catch-all phrase, often used to describe various levels of independence. Some use it to mean controlling the data an AI system processes, while others refer to the ability to build and train new frontier models from scratch. Others simply mean ensuring sensitive information never leaves a country’s borders. The lack of a settled definition has made it a part of political debate, allowing governments and companies to claim progress without necessarily committing to more demanding forms of sovereignty.
For Gomez, the central part of sovereignty starts with physical infrastructure. “Domestically controlled infrastructure is the first piece of the puzzle,” he said. “Each country needs an infrastructure champion.” Only when governments have a domestic player that controls the chips, power, and data centers their AI systems run on can they be sure that no foreign firm—or regulator—can unilaterally pull the plug.
Realistic Sovereignty Through Alliances
However, the dream of fully sovereign AI faces challenges around compute, capital, and energy. Building and running frontier-scale systems is extremely expensive and resource-intensive, and most countries will never be able to own every layer of the stack outright. Realistic sovereignty, Gomez argues, must be pursued through alliances.
Rather than every government trying to replicate the entire ecosystem at home, Gomez suggests democracies pool their resources around a small number of “champions” and share capacity through trusted partnerships. “It’s not the case that every country is going to have each layer of the AI stack inside their own country…instead they need to find multiple partners for those layers,” he said. “If we try to spread our resources, it just won’t work. We have to back champions and not spread our bets.”
Cohere's Strategic Moves
Cohere has been working to partner with other “middle power” nations and companies. In April, Cohere announced a deal to acquire Germany’s Aleph Alpha, aiming to create a transatlantic AI company anchored in both countries. Two months prior, Canada and Germany had signed a Joint Declaration of Intent on Artificial Intelligence and launched a sovereign technology alliance. The Cohere-Aleph Alpha deal was positioned as a way to put that political commitment into commercial practice.
The combined company, which would retain the Cohere name and be led by Gomez, is valued at around $20 billion, according to the Financial Times.
A Call for Global Coordination
At last week’s G7 discussions, Gomez noted that leaders and AI executives largely agreed on the need for democratic countries to coordinate on standards and regulation. Now, he wants them to go further and invest in shared capacity so their critical infrastructure isn’t dependent on a few U.S. or Chinese firms.
The politics around AI, he argues, are not that different from the technology itself. “Centralized dependence on a single entity is a structural risk; we need to avoid these single points of failure,” Gomez said. “I’m a computer scientist, and that’s one of the first things you learn: don’t build a system with a single point of failure.”
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