Artificial intelligence is beginning to reshape global productivity patterns, with the United States pulling ahead of Europe in adoption and expected economic gains, according to recent analysis and early 2026 data. Emerging evidence suggests the technology could trigger a new phase of divergence in growth between leading economies.
Early data shows clear adoption gap
Surveys from early 2026 show 43% of workers in the United States report using generative AI in their jobs, compared with an average of 32% across major European economies. Usage intensity is also higher: U.S. workers spend about 5.2% of total work hours using AI, nearly double the rate in the United Kingdom.
This widening usage gap underpins concerns raised by the White House Council of Economic Advisers, which has warned of a potential new “Great Divergence” reminiscent of the Industrial Revolution, when some countries accelerated rapidly while others lagged.
High levels of private investment in AI infrastructure in the U.S. are seen as a leading indicator of this possible split in economic trajectories.
Growth forecasts highlight emerging divide
Economic projections for 2026 reflect this separation. Analysts now see U.S. real GDP growth potentially reaching around 3%, materially above many current consensus estimates.
In contrast, the euro area is forecast to grow by about 1%, while the United Kingdom is expected to slow to roughly 0.8% growth. These differences are increasingly being linked to how quickly each region can absorb and deploy AI technologies.
Education and skills at the core of divergence
UBS chief economist Paul Donovan has argued that AI’s ultimate impact on productivity will depend heavily on education systems and the distribution of skills in each economy. While the effects of AI on output are still largely theoretical, he maintains that most new technologies tend to raise efficiency over time.
Donovan points to academic research suggesting AI can lift the productivity of lower-skilled workers proportionately more than others. However, the outcome depends on where the largest gains materialize. If the strongest productivity improvements concentrate among those with mid-level education, the United States could find itself at a relative disadvantage compared with other advanced economies whose education systems produce different skill mixes.
Europe’s skills shortage slows AI rollout
For now, Europe’s challenge is not demand but implementation. Around 71% of European Union businesses that have considered but not yet adopted AI say the main barrier is a lack of internal skills and expertise.
This shortage is acting as a direct brake on deployment of technologies that could otherwise boost output, reinforcing Donovan’s earlier warnings that structural differences in workforce education and training will shape how effectively economies capture value from automation.
Productivity impact still developing
Donovan notes that the benefits of AI are not yet fully measurable in official data, but early signals are beginning to appear in economic statistics. The pace and scope of AI’s impact, he argues, will depend on how quickly workforces can integrate new tools and adapt existing processes.
Disparities in training programs and on-the-job learning are likely to either speed up or slow down the spread of AI-related productivity gains. Regions with more flexible labor markets and stronger upskilling frameworks may be better placed to translate adoption into durable economic performance.
What to watch in the data
Over the coming weeks and months, those tracking the economic impact of AI will focus on several indicators:
- national productivity statistics, to see whether higher AI usage in the U.S. is turning into measurable efficiency gains
- detailed labor market reports, for signs that workers using AI are seeing higher output or wage growth
- corporate capital expenditure data, especially in technology and data infrastructure, as a forward guide to where future growth is being built
Any clear acceleration in productivity, particularly in the United States, would lend weight to forecasts of stronger growth and confirm that early adoption advantages are beginning to harden into structural economic gains.
The original analysis by Donovan was prepared with the aid of an artificial intelligence tool and subsequently reviewed by an editor.
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