Generative AI at Work
New AI tools have the potential to change the way workers perform and learn, but little is known about their impacts on the job. In this paper, we study the staggered introduction of a generative AI-based conversational assistant using data from 5,179 customer support agents. Access to the tool increases productivity, as measured by issues resolved per hour, by 14% on average, including a 34% improvement for novice and low-skilled workers but with minimal impact on experienced and highly skilled workers. We provide suggestive evidence that the AI model disseminates the best practices of more able workers and helps newer workers move down the experience curve. In addition, we find that AI assistance improves customer sentiment, increases employee retention, and may lead to worker learning. Our results suggest that access to generative AI can increase productivity, with large heterogeneity in effects across workers.
We are grateful to Daron Acemoglu, David Autor, Amittai Axelrod, Eleanor Dillon, Zayd Enam, Luis Garicano, Alex Frankel, Sam Manning, Sendhil Mullainathan, Emma Pierson, Scott Stern, Ashesh Rambachan, John Van Reenen, Raffaella Sadun, Kathryn Shaw, Christopher Stanton, Sebastian Thrun, and various seminar participants for helpful comments and suggestions. We thank Max Feng for providing excellent research assistance and the Stanford Digital Economy Lab for funding. The content is solely the responsibility of the authors and does not necessarily represent the official views of Stanford University, MIT, or the National Bureau of Economic Research.
Erik Brynjolfsson is the Director of the Stanford Digital Economy Lab and a compensated Committee Member at Luohan Academy.
- Customer support agents using an AI tool to guide their conversations saw a nearly 14 percent increase in productivity, with 35...