Research Snapshot: Examining AI’s rapid growth and economic impact
Adam Blandin, assistant professor of economics, typically analyzes how the amount of time worked affects a person’s earnings; how family structure affects wages, employment, and equality; and the economic implications of remote work. However, recently, Blandin looked at generative AI through an economic lens.
Blandin helped create the first nationally representative survey on how workers are using generative AI. Working with colleagues from the Harvard Kennedy School and the Federal Reserve Bank of St. Louis, with funding from the Harvard Skills Lab, Blandin revealed the potential economic implications of AI usage.
Q: What topic does your research address?
A: Generative Artificial Intelligence (AI) has emerged as a potentially transformative workplace technology, and several studies find sizeable productivity gains for workers who use generative AI. However, the overall impact of generative AI on the economic landscape also hinges on how many people adopt the new technology and how intensively they use it. We present results from the first nationally representative U.S. survey of generative AI adoption at work and at home. Our data comes from the Real-Time Population Survey (RPS), a nationwide survey that we designed that asks the same core questions and follows the same timing and structure of the Current Population Survey (CPS), the monthly labor force survey conducted by the U.S. Census Bureau for the Bureau of Labor Statistics.
Q: What were your findings?
A: We found that in August 2024, 39 percent of the U.S. population aged 18-64 used generative AI, and almost one in three respondents said they use it at least once during the week prior to the survey. Usage at home is somewhat more prevalent than at work (32 percent versus 28 percent), but daily usage is less frequent at home (6 percent versus 10 percent). On days workers used generative AI for their job, 23 percent used it for less than 15 minutes per day, 52 percent used it between 15 minutes and one hour per day, and 25 percent used it for more than an hour per day. Overall, we estimate that between 1 percent and 9 percent of all work hours in the previous week used generative AI. The most commonly used generative AI product is ChatGPT (28 percent), followed by Google Gemini (16 percent). Generative AI use is more common among individuals who are male, younger, more educated, and who work in computer, math, and management occupations.
The paper also compares the speed of adoption of generative AI to two other transformative technologies: personal computers (PCs) and the internet. Generative AI has been adopted at a faster pace than PCs or the internet. The faster adoption of generative AI is driven by higher usage outside of work. Three years after the mass introduction, PC adoption was only at 20 percent, which is about the same for the internet after two years. By contrast, the adoption rate for generative AI two years in is 39 percent. Interestingly, we show that at work, women initially adopted PCs at higher rates than men, but for generative AI the pattern is reversed. Use of PCs and the internet increased rapidly over the first decade or so after they were introduced. If a similar pattern holds for generative AI, it could become pervasive in the economy. This would likely help many of us by increasing productivity, which would lead to a higher standard of living, but it could hurt workers whose jobs become unnecessary.
Q: What do you hope will be the outcome of this research?
A: Improvements in technology are a key driver of economic growth. New technologies can also affect economic inequality if they make some skills less valuable and other skills more valuable. The potentially transformative effects of AI have led to both euphoric expectations for higher standards of living and fears of mass worker displacement. Understanding the spread of this new technology can help us understand its economic impact for the economy as a whole and for particular groups of workers. It can also help us design policies that encourage productivity gains or protect particular workers. We plan to continue running the survey every few months to track the trajectory of generative AI use over time. We also plan to conduct more studies to understand the impact of the technology on workers and the economy.