Adoption Monitor
How fast are individuals and firms adopting AI and related technologies?
Many contemporary AI tools are low- or no-cost and available digitally, allowing for rapid adoption. Capturing a rich picture of AI adoption requires drawing on a number of sources. Here, we track individual- and firm-level trends across surveys and countries.
While widespread adoption is neither necessary nor sufficient for broader economic impact, such adoption can indicate growing or shrinking importance of the technology in everyday and economic life.
We report individual-level, self-reported adoption rates from a variety of surveys. These surveys can differ in their sample size, the populations they represent, and elicitation strategy. This portfolio of surveys provides multiple signals on self-reported adoption.
Self-reported adoption captures specific forms of AI use that individuals are likely to consider generative AI. They might fail to capture embedded or ambient use, as well as integrated tools like spell checking and autocomplete.
We complement the individual results with surveys of firms across a number of high-income countries. These results capture the use of AI in production, as reported by company leadership. The use of AI in production and the cost incurred could provide a more reliable signal of the value of the technology for economically meaningful tasks. However, this signal is mitigated by adoption and diffusion frictions.
Generative AI Adoption by Individuals in the U.S.
Self-reported adoption of generative AI tools for work and personal use cases continues its steady upward trend, with 58% adoption at the beginning of 2026.
Generative AI tools are used often in personal or work life, but self-reported daily use remains low. Nearly 90% of generative AI users report using these tools every week, but only a quarter of users report using them every day.
Self-reported adoption rates of generative AI for work diverge in recent surveys: Hartley et al. report a decrease in adoption, while Gallup and Bick, Blandin, and Deming report continued increases towards 50% adoption.
Generative AI Adoption by Firms in Select Countries
Across all applications excluding text generation using LLMs, firms expect to increase adoption in the next three years. Robotics and autonomous vehicles see relatively large gaps between current and expected adoption.
Adoption trends for text generation using LLMs include forecasted decreases.
U.S. firms report slightly higher adoption at present, but level differences are ultimately modest. Respondents expect these between-country gaps to narrow slightly in coming years.
These data were reported by senior executives between November 2025 and January 2026.
Results are updated as new data are made available.
Summary of Recent Results
Individual adoption is growing but remains unevenly distributed
Two of three surveys show continued increases in individual adoption on the extensive margin. On the intensive margin, approximately one quarter of users report daily usage. Adoption patterns along the intensive and extensive margins are distinct.
Firms forecast modest increases in adoption
While firms have quickly adopted LLMs for text generation, they forecast modest extensive margin adoption over the next three years. On net, 6% of firms expect to move from not using any AI technology to using such tools.
Featured Affiliates
Nick Bloom’s research interests focus on measuring and explaining management practices across firms and countries.
His research includes collecting data from thousands of manufacturing firms, retailers, schools and hospitals across countries to develop a quantitative basis for management research. Recently, Nick has also been running management field experiments in India to identify clearly causal links between management and performance.
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