Generative AI

/ Adoption Tracker

Explore the trajectory of genAI adoption
The impact of generative artificial intelligence (genAI) on the economy depends on the speed and intensity of its adoption. This tracker reports results from a series of nationally representative U.S. surveys of genAI use at work and at home.
The figure shows the share of respondents who use gen AI for work, outside of work, and overall (either for work or outside of work). Intensity of use is broken down into every day last week, at least one day but not every day last week, and used but not last week.

View by

Overall

Usage frequency

Adoption rate (%)

No data available

Gen AI Usage
57.9%
of the U.S. population aged 18-64 uses generative AI
February 2026
Gen AI Adoption by Workers
43.4%
of the employed respondents used generative AI for work
February 2026
Work hours time saving
2.2%
time saved out of total work hours due to the genAI adoption
February 2026
Computer, Internet and genAI
16
years
for personal computers to reach a similar adoption level as GenAI
February 2026
Media, Reports & Policy

St. Louis Fed

Why Does AI Adoption Differ So Much across Countries?

2026-04-14
Read

White House

The Revolution of Artificial Intelligence (Economic Report of the President, Ch. 5)

2026-04-13
Read

VoxEU / CEPR

Differences in AI adoption in Europe and the US: Explanations and implications for productivity growth

2026-04-09
Read

Silicon Continent

What explains heterogeneity in AI adoption?

2026-04-09
Read
Our funders
Walmart Logo
The research included in this tracker was made possible through funding from Walmart. The findings presented in this tracker are those of the authors alone and do not necessarily reflect the opinions of Walmart.
About us
Alex Bick
Alex Bick
Senior Economic Policy Advisor, Federal Reserve Bank of St. Louis
Disclaimer: The findings in this tracker are those of the authors and do not necessarily reflect the views of the Federal Reserve Bank of St. Louis, the Federal Reserve System, or the Board of Governors.
Adam Blandin
Adam Blandin
Assistant Professor of Economics, Vanderbilt University
David Deming
David Deming
Danoff Dean of Harvard College and Isabelle and Scott Black Professor of Political Economy at Harvard Kennedy School
Nathalie Gazzaneo
Nathalie Gazzaneo
Co-Director, Harvard Project on Workforce, Harvard University
Methodology Background
We visualized the combination of 7 surveys and 35,000 respondents.
This tracker visualizes data from the first nationally representative U.S. surveys of genAI usage at work and at home. Our data come from the Real-Time Population Survey (RPS), a national online labor market survey of working-age adults aged 18-64 that has run since 2020.

RPS is designed and weighted to be nationally representative and to complement existing government surveys, such as the Current Population Survey or the American Community Survey, by carefully replicating core sections of those surveys while still leaving room for novel questions.

Read more about the methodology and see additional insights from the survey data at https://doi.org/10.1287/mnsc.2025.02523 (Alexander Bick, Adam Blandin, David J. Deming (2026) The Rapid Adoption of Generative AI. Management Science).

Disclaimer: The findings in this tracker are those of the authors and do not necessarily reflect the views of the Federal Reserve Bank of St. Louis, the Federal Reserve System, or the Board of Governors.
Cite the GenAI Adoption Tracker
GenAI Adoption Tracker: Harvard Project on Workforce, Alex Bick, Adam Blandin. (2026, May). Generative AI Adoption Tracker. https://www.genaiadoptiontracker.com/
@misc{genaiadoptiontracker,
    author = {{Harvard Project on Workforce} and Bick, Alex and Blandin, Adam},
    title = {Generative AI Adoption Tracker},
    year = {2026},
    urldate = {2026-05-01},
    url = {https://www.genaiadoptiontracker.com/}
}