This is one outlet's own report from Fortune — the article as it was filed.
AIPROPX ReportFortune · 1h ago
Google DeepMind is losing its grip on elite AI talent, new data shows
Over the last few years, the AI talent market has looked more like a professional sports draft than a conventional hiring cycle. Cash-rich labs are offering salaries more commonly associated with pro athletes, plus equity packages that can turn early employees into billionaires. The allure of life-changing paychecks has resulted in elite researchers swapping between rival labs at dizzying speed.
Google DeepMind, which was once the leading destination for many of those researchers—especially in Europe—is now finding itself on the losing side of that contest, according to a new overview of the flow of engineering talent exclusively shared with Fortune . A new analysis from Zeki Data, UK-based data intelligence company, shows that where OpenAI and Anthropic are making gains in the AI talent market, Google DeepMind and, to some extent, Meta are stumbling.
Interviews with several current and former staff suggest DeepMind’s changing identity has weakened part of its historic appeal. As Google has pushed to close the gap with OpenAI and Anthropic, the lab has become more tightly organized around improving and commercializing Gemini—a shift that some researchers see as displacing the open-ended, long-horizon science that once made DeepMind such a desirable destination for academics.
Three current and two former DeepMind staffers told Fortune the recent string of departures come down to a mix of factors: rival labs like Meta and Microsoft aggressively poaching talent with cash-heavy offers, mounting frustration inside Google over where it stands in the AI race, sinking morale, and the pull of pre-IPO stock at competitors such as OpenAI and Anthropic.
This month alone, Google DeepMind lost Jeff Dean , the company’s long-time chief scientist and a 27-year veteran, alongside senior fellow Sanjay Ghemawat and researchers Oriol Vinyals and Quoc Le, who left to launch a startup called Discovery Loop. On the same afternoon, Demis Hassabis, DeepMind’s cofounder and chief executive, said he would step back from day-to-day control of the lab to become its chairman and Alphabet’s chief scientist, handing operational control to CTO Koray Kavukcuoglu.
The new data from Zeki suggests the public exits are part of a broader reversal. For example, DeepMind’s share of research and advanced-engineering hires across Europe, the Middle East and Africa fell from 49% in 2022–23 to 18.6% in 2025–26—the sharpest market-share drop that Zeki recorded for a major AI lab in any region.
“They had the crown in Europe forever, and then it started to erode from a very high base,” Tom Hurd, founder of Zeki Data, told Fortune . “The likes of Microsoft AI Superintelligence and Meta Superintelligence are eating into their market share, and then there’s OpenAI and Anthropic on the side.”
The stakes of recruiting and retaining elite talent are high in the current hypercompetitive AI market. A relatively small group of researchers and engineers have the experience to train and improve the frontier models driving the AI boom. Their work can determine how quickly a lab improves its models, whether it can turn research breakthroughs into products, and how credibly it can attract the next wave of talent. Hiring and retaining these top engineers has proved difficult over the last few years, even for the industry’s best-funded companies.
Globally, DeepMind is still bringing in more research and advanced-engineering staff than it is losing. But its arrivals-to-departures ratio—a measure of hires relative to exits—has fallen sharply, from about 12-to-1 in the second quarter of 2023 to roughly 2-to-1 in the third quarter of 2026, according to Zeki’s data. That means it is now adding about two people in these roles for every one who leaves, rather than roughly 12. Comparatively, Meta’s ratio in 2025 was 3 to 1, OpenAI’s was 5.7 to 1, and Anthropic’s was 22 to 1, per the report.
Anthropic has become the leading destination for departing DeepMind researchers and advanced engineers. Of the people who left DeepMind in the past 12 months, 25% went to Anthropic, 21% to Meta, and 14% to OpenAI, according to Zeki.
Representatives for Google DeepMind did not respond to a request for comment on Zeki’s findings.
The deterioration in DeepMind’s talent flows coincided with the lab tightening its publication rules, Hurd said, something that Zeki researchers say may have weakened one of the lab’s most important draws for research-minded staff. The Financial Times first reported in April of 2025 that DeepMind had introduced a tougher internal review process and a six-month embargo for some strategically sensitive generative-AI papers, as the company sought to prevent competitors from benefiting from its research.
The FT reported that the new approach made it harder for researchers to publish studies, particularly work that could expose product weaknesses or reveal commercially valuable techniques. DeepMind said at the time that it remained committed to research publication and was updating its policies to preserve its teams’ ability to contribute to the broader research ecosystem.
For a lab that built its reputation on public breakthroughs such as AlphaGo and AlphaFold, the shift created friction with researchers who had joined to pursue relatively unconstrained, blue-sky work.
“Most old timers who joined DeepMind before the ChatGPT moment, joined to be part of an AI research lab,” one former DeepMind engineer told Fortune . “Anyone who joined before 2023 thought they were joining an AI research lab, and suddenly they were asked to build products for Google.”
A string of high-profile exits
The firm found that research and engineering hiring across the sector has grown at a compound annual rate of 23% since 2022. But the growth is flowing disproportionately to newer frontier labs. OpenAI’s research and engineering headcount has grown at roughly 97% annually and Anthropic’s at 152%, compared with ...
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