As the relationship between the US and its European allies shows signs of strain, AI labs across the continent are searching for inventive ways to close the gap with American rivals that have so far dominated the field.
With rare exceptions, US-based firms outstrip European competitors across the AI production line—from processor design and manufacturing, to datacenter capacity, to model and application development. Likewise, the US has captured a massive proportion of the money pouring into AI, reflected in the performance last year of its homegrown stocks and the growth of its econonmy.
The belief in some quarters is that the US-based leaders—Nvidia, Google, Meta, OpenAI, Anthropic, and the like—are already so entrenched as to make it impossible for European nations to break their dependency on American AI, mirroring the pattern in cloud services. In early January, the head of Belgium’s national cybersecurity organization told the Financial Times that Europe had “lost the internet,” and should make peace with a degree of reliance on US infrastructure.
Yet the governments of the UK and EU do not appear ready to give up. Already, they have committed hundreds of millions of dollars to minimizing their reliance on foreign AI suppliers. Meanwhile, buoyed by the success of China-based AI lab DeepSeek, whose breakout last year shattered the dogma that control over the largest fleet of AI processors determines which firm wins out, Europe-based researchers are pursuing alternative methods for developing competitive products built around imaginative model design.
“We have been too gullible to the narrative that innovation is done in the US—that we lost the AI train and should not even think about it,” claims Rosaria Taddeo, a professor of digital ethics and defence technologies at the University of Oxford. “That’s a dangerous narrative.”
One possible advantage that European AI labs hold over the large American firms—closed shops that share very little about their training data or the intricacies of their model design—is a willingness to develop out in the open. By publishing models for anyone to use or modify, the theory goes, breakthroughs achieved by European labs will compound as they’re further refined by collaborators. “You are multiplying the power of these models,” claims Wolfgang Nejdl, professor of computer science at Germany’s Leibniz Universität Hannover and director of the L3S Research Center, part of a consortium developing a large language model for Europe.
In the face of the White House’s lukewarm stance toward European leadership—and a nakedly hostile attitude among some allies of US President Donald Trump—those efforts to innovate and become self-sufficient have taken on a new urgency.
“The geopolitical situation has changed the way we should interpret sovereignty…This technology is an infrastructure—and an infrastructure we do not produce,” claims Taddeo. “We have to start moving in that direction. It’s not possible to ignore it anymore.”
A Transatlantic Spat
In recent months, European leaders have found themselves at loggerheads with the Trump administration over a tangle of issues ranging from the sovereignty of Greenland, to tariff policy, to immigration, leading to speculation about a deterioration in the NATO alliance that has set the global order for more than 75 years. The two sides have clashed particularly openly over the approach to policing American tech firms—especially X, the social media platform owned by Elon Musk.
After the European Commission fined X the equivalent of $140 million over alleged regulatory violations in early December, US Secretary of State Marco Rubio condemned the penalty as “an attack on all American tech platforms and the American people by foreign governments.” Later, after a UK regulator opened an investigation into X over a torrent of AI-generated sexualized images of women distributed on the platform, a precursor to a possible countrywide ban, US State Department official Sarah Rogers threatened retaliation.
Against that backdrop, Europe’s reliance on American-made AI begins to look more and more like a liability. In a worst case scenario, though experts consider the possibility remote, the US could choose to withhold access to AI services and crucial digital infrastructure. More plausibly, the Trump administration could use Europe’s dependence as leverage as the two sides continue to iron out a trade deal. “That dependency is a liability in any negotiation—and we are going to be negotiating increasingly with the US,” says Taddeo.
The European Commission, White House, and UK Department for Science, Innovation and Technology did not respond to requests for comment.
To hedge against those risks, European nations have attempted to bring the production of AI onshore, through funding programs, targeted deregulation, and partnerships with academic institutions. Some efforts have focused on building competitive large language models for native European languages, like Apertus and GPT-NL.
For as long as ChatGPT or Claude continues to outperform Europe-made chatbots, though, America’s lead in AI will only grow. “These domains are very often winner-takes-all. When you have a very good platform, everybody goes there,” says Nejdl. “Not being able to produce state-of-the-art technology in this field means you will not catch up. You will always just feed the bigger players with your input, so they will get even better and you will be more behind.”
Mind the Gap
It is unclear precisely how far the UK or EU intends to take the push for “digital sovereignty,” lobbyists claim. Does sovereignty require total self-sufficiency across the sprawling AI supply chain, or only an improved capability in a narrow set of disciplines? Does it demand the exclusion of US-based providers, or only the availability of domestic alternatives? “It’s quite vague,” says Boniface de Champris, senior policy manager at the Computer & Communications Industry Association, a membership organization for technology companies. “It seems to be more of a narrative at this stage.”
Neither is there broad agreement as to which policy levers to pull to create the conditions for Europe to become self-sufficient. Some European suppliers advocate for a strategy whereby European businesses would be required, or at least incentivized, to buy from homegrown AI firms—similar to China’s reported approach to its domestic processor market. Unlike grants and subsidies, such an approach would help to seed demand, argues Ying Cao, CTO at Magics Technologies, a Belgium-based outfit developing AI-specific processors for use in space. “That’s more important than simply access to capital,” says Cao. “The most important thing is that you can sell your products.” But those who advocate for open markets and deregulation claim that trying to cut out US-based AI companies risks putting domestic businesses at a disadvantage to global peers, left to choose whichever AI products suit them best. “From our perspective, sovereignty means having choice,” says de Champris.
But for all the disagreement over policy minutiae, there is a broad belief that bridging the performance gap to the American leaders remains eminently possible for even budget- and resource-constrained labs, as DeepSeek illustrated. “If I would already think we will not catch up, I would not [try],” says Nejdl. SOOFI, the open source model development project in which Nejdl is involved, intends to put out a competitive general purpose language model with roughly 100 billion parameters within the next year.
“Progress in this field will not to the larger part depend anymore on the biggest GPU clusters,” claims Nejdl. “We will be the European DeepSeek.”
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