AI productivity gains are often seen in sectors that cut entry-level jobs.

The US is no longer leading the AI model race, says the latest Stanford AI Index report, which finds that the performance gap between Chinese and American models has “effectively closed”.

The AI Index is an initiative at the Stanford University Institute for Human-Centered Artificial Intelligence. In its eighth edition last year, it found that even though Chinese AI models were fast catching up in performance, the US was still placed as the clear leader in the race. That, however, has changed.

Since early 2025, several Chinese models have challenged their American counterparts, with China’s DeepSeek-R1 marking the first large instance last February. Models from Chinese companies such as Alibaba, Zhipu and MiniMax have since continuously ranked high in leaderboards.

The US, however, continues to be AI’s biggest backer, still producing more “top-tier” AI models and high-impact patents, while China is leading the game in volume, industrial robot installations, citations and patent output.

Private AI investment in the US reached around $286bn in 2025, with nearly 2,000 newly-funded AI companies forming last year. The US also hosts the highest number of AI data centres – more than 10 times more than any other country.

Talent loss

AI has undoubtedly cemented its presence in society; Stanford reports that AI has reached mass adoption faster than the personal computer or the internet.

Generative AI has already been adopted by more than 50pc of the population, with numbers sitting at 61pc in Singapore, 54pc in United Arab Emirates and around 28pc in the US.

The technology is fast accelerating in capabilities, reaching more of the population than ever before.

Many of the notable AI models released last year can meet or exceed human baselines on PhD-level science questions, multimodal reasoning and competition mathematics, the report finds, creating challenging circumstances for jobseekers. AI models purpose-built for science can outperform human scientists in many cases, it adds.

On the flip-side, the report finds connections between a decline in entry-level employment and productivity gains.

The software development sector, which shows the clearest markers of productivity gains through AI, saw a 20pc decline in US-based employees aged 22 to 25 years old. Senior positions with older developers are growing in count, meanwhile.

Despite the massive investments, the US is struggling to attract global talent, with an 80pc drop since last year’s report in AI researchers and developers choosing to move to the country.

Responsibility takes a backseat

The report notes that responsible AI is not keeping up with AI capability, pointing to a lag in safety benchmarks and “spotty” reporting on benchmarks.

Documented AI incidents rose to 362, up from 233 in 2024. Meanwhile, a recent study found that improving AI safety can affect model accuracy, adding to the challenge of improving model safety.

The report also touches on AI sovereignty, calling it a “defining feature of national polic[ies]”.

The EU, for one, launched the AI Continent Action Plan last April, promising to enhance AI infrastructure and reduce dependence for its technological needs.

Meanwhile, newer open source developments – most notably, OpenClaw – are helping to redistribute who can participate in the AI race.

Technology firms are taking advantage of the widely accessible open source models by creating their own versions of OpenClaw with enhanced security.

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