Copyright Fast Company
In artificial intelligence, compute and data matter, but people matter more. Behind every breakthrough model, every infrastructure leap, and every “revolutionary” chatbot lies a shrinking pool of scientists, engineers, and mathematicians capable of building them. The defining constraint on the next decade of AI isn’t just hardware: it’s human capital. Across the world, a quiet arms race is unfolding for that capital. The most advanced AI firms, like OpenAI, Anthropic, DeepMind, Meta, Google, and a few in China, are no longer competing just for customers or GPUs. They are competing for brains. The new concentration of intelligence In the past two years, the hiring and acquisition patterns of AI companies have begun to resemble a geopolitical map. Anthropic and OpenAI lure entire research teams from Google or Meta with compensation packages approaching nine figures. Apple and Amazon, late to the party, are buying startups not for products, but for the engineers behind them. And venture capital is no longer funding ideas so much as acqui-hiring: purchasing human potential before it matures elsewhere. Multiple analyses show that elite U.S. programs, especially Stanford, Berkeley, Carnegie Mellon, and MIT remain dominant feeders into frontier AI labs, reinforcing a tight concentration of expertise in a few firms and geographies. The result is intellectual concentration unprecedented in the history of technology. This clustering may accelerate progress in the short term. But it also increases fragility. When innovation lives inside a handful of firms, the industry becomes monocultural. The same assumptions, ethical frameworks, and commercial incentives repeat themselves. Alternative approaches, like symbolic reasoning, hybrid models, and decentralized architectures, struggle for attention or funding. The global scramble for minds Meanwhile, countries are treating AI researchers the way they once treated nuclear physicists or oil engineers. The United Kingdom launched its Frontier AI Taskforce with special visas for top scientists. Canada’s Global Talent Stream fast-tracks work permits for AI engineers in under two weeks. France offers tax incentives and research grants for companies that locate their labs in Paris or Grenoble. China, faced with export controls on chips, has doubled down on human intelligence as a strategic resource. Its leading universities are producing tens of thousands of AI graduates a year, many trained on open-weight models after Washington’s hardware restrictions. As one analyst at the Carnegie Endowment put it, “If you can’t import compute, you import talent.” In other words: brains are the new semiconductors. America’s self-inflicted wound And yet, the United States, still home to most of the world’s top AI firms, is busy tightening the spigot. Donald Trump’s renewed hostility toward immigration includes threats to limit, suspend, or impose heavy fees on H-1B and F-1 visas, the very programs through which thousands of AI researchers enter the country each year. The pattern is not new. In 2020, during his previous term, Trump signed an executive order suspending key visa categories, prompting MIT Technology Review to warn that the move “threatened to undercut America’s lead in artificial intelligence.” The logic hasn’t changed. The world’s best AI researchers are disproportionately international: roughly 60% of top AI scientists working in the U.S. were born abroad, according to the National Foundation for American Policy. Limiting their entry isn’t protectionism: it’s strategic sabotage. When your biggest competitive advantage is talent, closing the door to talent is a slow form of self-destruction. The corporate paradox Ironically, the companies that benefit from global talent the most are also the ones making that talent scarce. By offering astronomical salaries and exclusivity contracts, they create a gravitational field that pulls expertise out of universities and startups. Academia, long the seedbed of AI progress, is now bleeding researchers to industry at an unprecedented rate. The result is a research vacuum where public institutions can no longer afford to compete. Even national labs struggle to retain talent when private firms offer multiples of government pay. This corporate concentration of minds has another cost: intellectual homogeneity. When the same people cycle between the same companies under the same investors, the frontier of AI becomes narrower, more predictable, and less plural. The next big breakthroughs might never happen, and not because we lack compute, but because we’ve trained the global research community to think the same way. The geopolitical stakes For decades, the United States has dominated global innovation by acting as a magnet for talent. The H-1B and F-1 visa systems, for all their flaws, turned American universities and tech hubs into engines of discovery. That advantage is now at risk. advertisement If Washington continues down the path of visa restriction, and if the industry continues to hoard rather than nurture expertise, the gravitational center of AI could shift elsewhere. Canada, the European Union, and the UAE are already competing for displaced researchers. China, meanwhile, is developing homegrown alternatives with staggering speed. The irony is that America may lose the very thing that made its technology ecosystem unstoppable: openness. The more insular it becomes, the more it resembles the centralized systems it once out-innovated. The ethics of scarcity Talent concentration also raises moral questions. When a small number of corporations control the majority of global AI expertise, they effectively control which problems get solved and which are ignored. We are already seeing this bias in practice. Billions are being poured into models that optimize productivity, marketing, and financial forecasting, while underfunded projects in climate modeling, education, and healthcare languish. AI’s promise to “benefit humanity” is hollow if humanity doesn’t have a seat at the table. Diversity of thought, background, and geography is not a moral luxury; it’s a prerequisite for resilience. Homogeneous systems fail in homogeneous ways. A new social contract for intelligence The solution is neither regulation alone nor market freedom alone. It’s a new social contract for talent — one that treats human intelligence as a shared strategic resource, not a proprietary asset. That means: Immigration policies that attract, not repel, the world’s brightest minds. Funding mechanisms that keep public research competitive with corporate labs. Ethical frameworks that prevent non-competes and exclusivity contracts from turning scientists into captives. Global cooperation that recognizes AI as a common infrastructure challenge, not a zero-sum race. In the 20th century, nations competed for oil. In the 21st, they will compete for cognition. A warning and a choice The United States still holds the advantage: world-class universities, deep capital markets, and a culture of risk. But advantages erode when arrogance replaces openness. If America turns inward, it won’t just lose talent: it will lose the diversity that fuels creativity. And when the next generation of scientists chooses to work in Toronto, Paris, Madrid, or Shenzhen instead of Silicon Valley, the “American century” of innovation will quietly end. Not with a revolution, but with a resignation letter. Computing power, as I said in previous articles, is important, as it is access to cheap energy, or as Europe very well knows, regulation. But the race for AI supremacy will not be won by compute, nor by energy prices or by policy alone. It will be won by whoever attracts and empowers the minds that make intelligence itself. And right now, those minds are watching which countries still deserve them.
