Why the U.S. leads Europe in Artificial Intelligence adoption

Survey evidence shows U.S. workers and firms are adopting Artificial Intelligence faster than their European counterparts. The gap appears to be driven not only by workforce composition, but also by stronger managerial support and greater workplace encouragement to use the technology.

Artificial Intelligence adoption is advancing faster in the U.S. than in Europe, according to survey findings comparing workers and firms across both regions. Researchers describe Artificial Intelligence as a broad family of systems that learn from data rather than relying only on fixed if-then routines, with generative Artificial Intelligence standing out as the best-known recent wave. The central question is whether the current rollout of Artificial Intelligence will mirror the earlier information and communications technology era, when faster U.S. adoption helped widen productivity differences with Europe.

On the worker side, 43% of U.S. workers use gen AI for their job, and we measured that in, in early 2026, compared to only 32% across six European countries we looked at. Those countries were the UK, Germany, France, Italy, Sweden, and the Netherlands, with adoption ranging from about twenty-five percent in Italy to about thirty-six percent in the UK. The gap also widens when use intensity is considered, because U.S. workers report spending more time with generative Artificial Intelligence on the job. On the firm side, 7% of U.S. firms use it for producing goods and services, compared to about 4% on average in Europe. In broader business-use measures, the European survey showed 20% for the U.S., and the researchers project that number for the U.S. to be 34% because that question was not asked in 2025 when the EU survey was conducted for the U.S..

Part of the U.S.-Europe gap reflects differences in workforce and firm composition. Artificial Intelligence use is higher among more educated workers, workers under age 50, workers in certain occupations and industries, and workers in larger firms. These compositional factors explain somewhere between a third and a half of the adoption gap. Much of the rest appears linked to management practices. U.S. firms are more likely to provide workers with Artificial Intelligence tools, make them available in the workplace, and actively encourage experimentation and use. Countries and firms with stronger management scores also show higher adoption rates, suggesting that organizational choices matter as much as technical access.

Early evidence points to productivity gains without a broad employment decline. Sectors with high adoption rates do not appear to show unusual employment losses so far, although some groups, such as early career workers in highly exposed jobs, could still face disruptions. When it comes to productivity, we do see meaningful effects, like a 10% point high adoption rate is associated with about 2-5 percentage points higher cumulative productivity growth since 2022. Workers also report direct time savings: on average, Artificial Intelligence users spend a bit more than three hours using AI per work week, and that saves them almost two hours per week. Researchers argue that larger gains may depend on firms redesigning workflows and reorganizing work, not simply adding new tools to old processes.

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