Generative AI is a groundbreaking technology, but its economic impact depends on the speed and intensity of its adoption. The paper The Rapid Adoption of Generative AI by Alexander Bick, Adam Blandin, and David Deming presents findings from the first nationally representative survey in the U.S. on generative AI use at work and home. The data are sourced from the Real-Time Population Survey (RPS), designed and weighted to be nationally representative and modeled after the CPS, a widely recognized national data source. The researchers found that in August 2024, 39.4 percent of the U.S. population aged 18-64 reported using generative AI, with 28 percent of employed respondents using it at work and nearly one in nine workers using it daily.
The study compares the adoption rate of generative AI with two transformative technologies—PCs and the internet—and found that generative AI has been adopted more quickly than both. The researchers also found that workers across a wide range of occupations and tasks use generative AI. Nearly half of those in computer, mathematical, and management roles use it, as do one in five blue-collar workers. Respondents indicated that generative AI was useful for a variety of job tasks, such as writing, administrative support, interpreting and summarizing text or data, and coding, with over 25 percent using it for each of the tasks listed.
The researchers estimate that between 0.5 and 3.5 percent of all work hours in the U.S. are currently supported by generative AI. Based on productivity improvements from experimental studies, they suggest that generative AI could potentially boost labor productivity by 0.125 to 0.875 percentage points at current usage levels, though they caution that this estimate is speculative given the assumptions involved.
The findings point to many future research directions, particularly the need to track the technology's adoption as it evolves and to observe whether its use becomes more widespread across different workers, occupations, and tasks. Future waves of this survey will include more detailed questions about the frequency and intensity of generative AI adoption to monitor its ongoing economic impact.
Read the full paper The Rapid Adoption of Generative AI.
Read the Federal Reserve Bank of St Louis On the Economy Blog.
Read an analysis of the results from David Deming's Forked Lightning Blog
David Deming Explains the Results
Authors
Alexander Bick, Federal Reserve Bank of St. Louis & CEPR; Adam Blandin, Vanderbilt University; and David J. Deming, Harvard Kennedy School & NBER.
About the project
The Project on Workforce is an interdisciplinary, collaborative project between the Harvard Kennedy School's Malcolm Wiener Center for Social Policy, the Harvard Business School’s Managing the Future of Work Project, and the Harvard Graduate School of Education. The Project produces basic and applied research at the intersection of the education and labor markets for leaders in business, education, and policy. Our mission is to chart the course for a postsecondary system of the future that creates better pathways to economic mobility.
Acknowledgments
The research included in this report was made possible through funding by Walmart. The findings, conclusions, and recommendations presented in this report are those of
authors alone, and do not necessarily reflect the opinions of Walmart.