Google DeepMind Is Losing Its Grip on Elite AI Talent

Lately, the AI talent market has looked more like a professional sports draft than a conventional hiring cycle.

Google DeepMind is facing growing competition for elite AI researchers as rival artificial-intelligence labs aggressively recruit top scientific talent. [Image: Google Facebook]

Cash-rich AI labs are offering researchers enormous salaries and equity packages that can turn early employees into billionaires.

The result is an increasingly fluid talent market, with elite researchers moving between rival labs at a rapid pace, Beatric Nolan reported for Fortune Tech.

Google DeepMind, once a leading destination for many of those researchers, is now finding itself on the losing side of that competition, according to data exclusively shared with Fortune.

Analysis from Zeki Data shows that while OpenAI and Anthropic are gaining ground in the AI talent market, Google DeepMind—and, to some extent, Meta—are losing talent.

Interviews with current and former employees suggest that DeepMind's changing identity has weakened some of the factors that historically made it attractive to researchers.

As Google has sought to close the gap with OpenAI and Anthropic, DeepMind has become more closely organized around improving and commercializing Gemini.

Some researchers view the shift as a departure from the open-ended, long-horizon scientific research that once made DeepMind particularly attractive to academics.

Three current and two former DeepMind employees told Fortune that the recent departures reflect a combination of factors, including aggressive recruiting by rivals such as Meta and Microsoft, frustration within Google over its position in the AI race, declining morale and the attraction of potentially lucrative pre-IPO equity at companies such as OpenAI and Anthropic.

The movement of researchers highlights the increasingly competitive nature of the AI labor market.

While compensation remains a major factor, researchers are also weighing access to computing resources, the freedom to pursue long-term research, leadership, organizational culture and the potential financial upside of joining private AI companies.