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.
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