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Carnegie China: China passed the US as the top destination for elite AI talent in 2025, rising from 2022's 27.1% share to 40.6%; the US fell from 46.4% to 34.2%

The Information Claudia Chong

Context & Ripple Effects

A 2024 study found that China produced almost half of the world’s top AI researchers, making the country’s research-training base materially larger than the U.S. share in that analysis. A 2025 warning that U.S. AI-talent inflows had reached parity with outflows framed destination competitiveness as a developing constraint rather than a settled loss of attraction.

Carnegie China’s figures turn that underlying supply and mobility story into a location shift: the largest share of its elite-researcher sample is working in China rather than the U.S. Public discussion of the tracker also distinguishes destination share from net migration, arguing that the U.S. still posts a net gain in the sampled researchers.

First-order effects

  • China-based AI universities, labs and companies gain access to the largest work-location share of Carnegie China’s elite-talent sample, while the U.S. share contracts.
  • The result strengthens the link between China’s large domestic pipeline of top AI researchers and its own research employers rather than treating training and employment as separate advantages.

Second-order effects

  • U.S. universities and AI employers face greater pressure to retain and recruit researchers as the destination lead flagged in earlier talent-flow analysis gives way to a smaller share of the Carnegie sample.
  • China-based employers can draw more of their advanced-research hiring from researchers trained and working domestically, reducing the extent to which overseas placement is the primary route into elite AI work.

Third-order effects

  • If the shift persists, frontier AI research capacity will be distributed less around a single U.S.-centered destination and more around competing national research ecosystems.
  • Talent location becomes a more important component of AI sovereignty: training capacity, research institutions and employer opportunity increasingly reinforce one another within the same country.

The trend: AI competition is broadening from a contest to attract individual researchers into a contest to build self-reinforcing national talent ecosystems.

Discussion

  • @appendixzeroai @appendixzeroai on x
    This might be the most interesting number in the whole report: 3,619 researchers followed a China → China → China path: Chinese undergrad, Chinese grad school, now working in China. China → US → US: 1,071 US → US → US: 1,093 The domestic Chinese AI pipeline is now enormous.
  • @appendixzeroai @appendixzeroai on x
    But this isn't a story of the US suddenly losing its ability to attract talent. The US still has by far the largest net talent gain: +2,145 in Carnegie's sample. China is at -1,729. What changed is that China now produces so much AI talent, and retains much more of it, that both …
  • @hsu_steve Steve Hsu on x
    Carnegie report on NeurIPS 2025 authors and AI talent flow. US AI is heavily dependent on attracting talent from PRC. But PRC talent pool is larger than RoW combined. Largest pool of AI talent - capable of publishing at NeurIPS: PRC undergrad → grad school → Chinese company or pr…
  • @appendixzeroai @appendixzeroai on x
    Carnegie just dropped its new AI Talent Tracker and the shift since 2022 is pretty striking. Among the NeurIPS researchers in its sample, 57.4% did their undergrad in China, up from 46.3% in 2022. The US fell from 19.8% to 13.3%. But the more interesting change is where they now …
  • @appendixzeroai @appendixzeroai on x
    China has now overtaken the US as the main place these researchers work. 2022: 🇺🇸 46.4% 🇨🇳 27.1% 2025: 🇨🇳 40.6% 🇺🇸 34.2% That's a massive shift in just three years. The old picture of China producing talent that mostly ends up in the US is increasingly outdated.