Europe risks losing some of its fastest-growing artificial intelligence startups as regulation, funding shortages and skills gaps make it harder for companies to scale, a senior Amazon Web Services executive has warned.
AWS EMEA Managing Director Tanuja Randery said nearly four in 10 European startups surveyed would consider relocating outside the region to expand their businesses.
Among the fastest-growing companies, the figure rises to more than half.
The warning comes despite rapid growth in AI adoption across European businesses, suggesting that using AI and building globally competitive AI companies are becoming two very different challenges.
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Startups Say Europe Is Becoming Harder to Scale In
Randery said startups increasingly tell AWS they are reconsidering where to build their businesses because they cannot access enough capital or support in Europe.
Funding is only part of the problem.
European companies also face a complicated regulatory environment, shortages of workers with advanced AI skills and limits on computing and energy infrastructure.
Randery said some businesses report spending as much as 40 cents of every euro on regulatory compliance instead of technology investment.
That figure reflects feedback from companies rather than an official EU-wide measurement.
Still, it highlights the growing tension between Europe’s effort to regulate AI safely and its ambition to build globally competitive technology companies.
The European Union’s AI Act has created one of the world’s most comprehensive regulatory frameworks for artificial intelligence.
Supporters argue that clear rules around safety, transparency and high-risk systems can increase trust.
Critics worry that compliance costs may weigh more heavily on smaller companies than on technology giants able to maintain large legal and regulatory teams.
AI Adoption Is Rising, but Transformation Remains Limited
AWS research suggests Europe is not struggling to persuade companies to experiment with AI.
Around 54% of European businesses now use the technology, up from 33% two years earlier.
But only about one in five businesses has developed what AWS describes as a clear AI strategy, governance structure and investment plan capable of fundamentally changing operations.
That gap matters.
A business using a chatbot to summarise documents counts as an AI adopter.
But that is very different from redesigning production, customer service or internal workflows around AI systems.
Randery said Europe needs to focus more heavily on inference.
AI inference is the stage where a trained model is actually used to generate answers, analyse information or carry out tasks.
Training advanced models attracts much of the attention because it requires enormous computing resources.
But most of the practical economic value comes when those models are deployed at scale inside businesses.
Europe therefore does not necessarily need to build every frontier model itself to capture value from AI.
It does, however, need companies capable of turning available models into productive commercial systems.
Skills and Funding Could Widen US-Europe Gap
Europe already trails the United States in the scale of venture capital available to technology startups.
AI makes that financing gap more important because companies often need large amounts of capital for computing infrastructure, technical talent and rapid expansion.
A promising startup may therefore decide that operating from the US gives it better access to investors, customers and specialised workers.
Skills shortages add another constraint.
Building advanced AI systems requires machine-learning engineers, data specialists, cybersecurity professionals and people capable of redesigning business processes around automation.
AWS says the availability of those skills has not kept pace with demand.
The problem can become circular.
If successful startups relocate, Europe could lose both jobs and experienced employees who might otherwise help create another generation of technology companies.
Europe Also Faces Energy and Computing Constraints
Capital and regulation are not the only issues.
AI infrastructure requires large amounts of electricity and computing capacity.
Europe controls a relatively small share of global AI computing infrastructure compared with the United States.
Several countries are trying to expand domestic data centres, but electricity-grid capacity, permitting delays and environmental requirements can slow new projects.
That leaves European AI companies more dependent on large foreign cloud providers and technology companies.
The dependence has already become a policy concern.
UK government advisers recently warned that Britain could become a high-value AI customer rather than a creator if it fails to strengthen domestic computing, data and model-development capacity.
Similar concerns are emerging across continental Europe.
Randery said the answer should not be to choose between innovation and safety.
Instead, she argued that Europe needs both stronger safeguards and faster development.
The bigger question is whether policymakers can create rules that protect consumers without making it significantly more expensive for smaller companies to compete.
What this means for you:
Europe’s AI challenge is shifting from adoption to scale. If promising startups cannot find enough capital, computing capacity or skilled workers locally, more could move to markets where expansion is easier.
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