The silent exodus of the AI elite - How Europe is subsidizing America's tech future

Europe produces its own AI tech elites, hones them in strong universities and respected institutes, then watches them methodically depart for ecosystems that can offer them more money, more computing power, more speed, more growth capital and the sense that the "frontier” is being built elsewhere, according to an article published by Euronews. The source cited states that the exodus of AI experts from Europe is no longer a conference topic, but a strategic vulnerability that is visible in numbers and mobility maps: the continent has, according to a global mapping of AI professionals, about 30% more talent in this field per capita than the United States and almost three times more than China, but, paradoxically, it is recording a significant negative net outflow of senior professionals. This top-down drain is hitting where it matters most, in the capacity to transform research and education into global champions, frontier labs, rapidly expanding companies and economically exploitable intellectual property within the European Union, according to the cited source.

The 2024 Interface report puts it bluntly: European countries are "losing significant AI talent, both domestically and internationally, to the United States,” with Germany as a massive example of exporting AI specialists to the US and the UK. France is in the same negative register, as is Switzerland, the two countries functioning as transit zones to the US and the UK.

On closer inspection, Europe is not just losing people, it is losing precisely the most expensive investment: highly qualified and highly mobile specialists, trained in a system that still heavily subsidizes education, research and public infrastructure, but fails to sufficiently monetize the final result. According to the cited source, 57% of AI professionals working in Europe received their undergraduate degrees outside Europe, compared to 38% in the United States; Ireland is a near-didactic case, with about 28% of AI professionals holding undergraduate degrees from India, and in the United Kingdom the proportion is about 14%. Many of these people, once integrated into Europe, use their international mobility as an escalator to the American ecosystem, where compensation packages and research conditions are simply harder to refuse.

• Higher incomes in the US for AI specialists

The first reason for the exodus is remuneration. According to the cited source, salaries in the field of artificial intelligence in the United States are typically 30% to 70% higher than in most of Europe for similar jobs. For example, a mid-level or senior AI engineer in the US frequently earns base salaries between $140,000 and $210,000, and total compensation goes much higher through bonuses and stock options, while in Western and Northern Europe senior specialists typically earn between $90,000 and $150,000, and in Southern and Eastern Europe often under $100,000.

But the difference that decides the future is not just salary, but also equity participation, according to the cited source: in the US, stock options and potential earnings for early employees are a culture and a financial infrastructure; in Europe, they remain rarer and, when they exist, are often less generous, including in companies in the expansion phase, which makes staying on the continent for senior engineers and founders who demand real long-term potential, pragmatically seem like a ceiling. And even as Europe tries to attract back or bring in new researchers, the wage gap is becoming a barrier: Science Business magazine noted, citing a Brussels-based research policy specialist, that many American researchers would be willing to come to Europe, but a reduction of tens of percent in income is blocking their decision.

• Supporting scale-up for small companies, a problem in the EU

The second reason for the exodus relates to computing power and access to the "frontier”, Euronews reports. Researchers who want to work on the biggest models, the biggest data sets and the most expensive experiments tend to head to places where there are massive clusters, cutting-edge laboratories and frontier model projects at scale. The United States concentrates a large share of this infrastructure and these organizations, while Europe remains fragmented: it has excellent universities and strong public institutes, but fewer places that simultaneously combine global-level research, large-scale computing power and aggressive commercialization in a single integrated ecosystem. Horizon Europe and national programs exist, but, in the perception of industry and researchers, funding and access to computing power are often below what is offered by top US labs, and when the "frontier” moves quickly, resource differences turn into career differences.

The third reason for the exodus is the expansion or scaling gap: the point at which an AI or deep tech startup needs large, fast, risk-tolerant rounds that are large enough to sustain global growth. In Europe, Series B and subsequent rounds are often smaller, slower, and more cautious than in the United States, with stricter conditions; the result is predictable: some founders move their headquarters, leadership, or senior teams to the US, where growth capital is more abundant, decision-making is faster, and failure is less stigmatized.

Atomico's data from the "State of European Tech 2025” report shows a simple but painful indicator: net flows of tech talent to Europe have fallen from around 52,000 in 2022 to just 26,000 in 2024, while the top destinations remain the United States, Canada and Australia.

And on top of all that is the European architecture of rules, risk and fragmentation. The European Union has built a "trusted”, rights-based AI identity, crystallised in the AI Act; for some this is a competitive advantage and a sign of maturity, for others it generates operational uncertainty, compliance costs, unclear deadlines and a brake on innovation, especially when public procurement is slow and when the single market, in practice, still means differences between member states in terms of taxation, labour law and support schemes. This makes it often more complicated for a single AI company to expand within the European Union than it is for a single market like the US, and in an industry where speed is everything, administrative complexity becomes a competitive advantage.

• Intra-European mobility of AI specialists

Mobility is not just "out”, but also "in”, and this shows once again that Europe has talent and circulation, but does not have enough retention at the top. The cited source claims that in 2023, Switzerland and a few smaller countries attracted about 18% of intra-European relocations of AI professionals, mainly from France, Germany and Italy, driven by higher salaries, strong universities and proximity; historically, the Netherlands and the United Kingdom concentrated about 23% of such movements, describing a highly mobile brain exchange. But even these centers are constantly losing experienced professionals to the United States, and Germany remains the emblematic example of the paradox: it attracts, including flows from India, but continues to lose senior specialists to the US, the UK and Switzerland. In this context, the European Union is trying to reverse the trend, aware that without people there is no technological sovereignty, and without sovereignty there is no real economic power in artificial intelligence. Member States have agreed on a Council Recommendation for a European framework for attracting and retaining talent in research, innovation and entrepreneurship, in the logic of the "balanced circulation of talent" in the European Research Area, and the European Commission has launched initiatives such as the Talent Pool for workers from outside the European Union, legal access offices, Talent Partnerships and the Marie Sklodowska-Curie component "Choose Europe", aimed at co-financing the recruitment of top international researchers in artificial intelligence and linking grants to long-term career prospects. In the documents and communications on "Choose Europe for Science”, the scheme is explicitly presented as a response to the precariousness of research careers and the risk of brain drain, with a pilot call in 2025 and an indicative budget of euro22.5 million, precisely to make careers in European research more attractive and stable.

Europe's comfortable grand illusion has been that "we have good universities, so we will win”, but in artificial intelligence, the winner is not who trains, but who retains, who expands and who transforms talent into products, models, companies and economic power. Europe has more "raw material” than its rivals, by some measures even more than the United States per capita, but if the net outflow of senior specialists continues and if the gap in resources at the border remains, the EU risks becoming the elite supplier of others, a nursery that supplies minds to laboratories and companies that build their dominance elsewhere, while all that remains here, too often, are the diplomas, the pilot projects and the promise that "next time" it will be different.