New US report links artificial intelligence to renewed economic divergence
A January 2026 report by the US Council of Economic Advisers argues that artificial intelligence is likely to accelerate economic divergence between countries, with the United States positioned as the main beneficiary under current investment and policy trends.
The Council of Economic Advisers has published a report examining how artificial intelligence may reshape global economic growth patterns. Titled Artificial Intelligence and the Great Divergence, the paper compares the expected impact of AI to earlier technological shocks such as the Industrial Revolution, while stressing that outcomes remain uncertain and unevenly distributed Artificial-Intelligence-and-the….
The report argues that AI investment, performance, and adoption are advancing fastest in the United States. It highlights large differences in private and public spending on AI, computing infrastructure, and data centres, noting that US private AI investment substantially exceeds that of the European Union and China combined. According to the analysis, these gaps risk translating into divergent productivity and GDP growth trajectories over the coming decade.
Using existing economic literature, the advisers review estimates suggesting that AI could raise GDP levels by between low single digits and more than 40 percent over ten years, depending on assumptions about labour substitution and diffusion. The report emphasises that research and development spending and AI-related capital investment are leading indicators, while productivity gains are expected to materialise with a delay.
On labour markets, the document presents mixed evidence. It notes short-term job losses in some AI-exposed occupations, alongside stable overall unemployment rates. Drawing on historical examples, the report argues that efficiency gains may ultimately increase labour demand through expanded economic activity, though it acknowledges scenarios in which AI could reduce employment growth if substitution effects dominate.
The report also compares countries across AI investment, performance, and adoption metrics. It finds the United States leading in advanced model development and computing capacity, with China in second place and the EU trailing on most indicators. Adoption, however, is more geographically dispersed, with middle-income countries accounting for a large share of global AI usage despite lower domestic investment.
In its final section, the report links these trends to current US policy, outlining tax, trade, and regulatory measures intended to accelerate AI deployment and infrastructure build-out. It concludes that AI has the potential to reinforce existing economic hierarchies unless access to key inputs such as capital, energy, skills, and computing capacity becomes more evenly distributed.
