Generative Ai at Work

67 Pages Posted: 24 Apr 2023 Last revised: 22 Feb 2025

See all articles by Erik Brynjolfsson

Erik Brynjolfsson

National Bureau of Economic Research (NBER); Stanford

Danielle Li

Massachusetts Institute of Technology (MIT)

Lindsey Raymond

Massachusetts Institute of Technology (MIT)

Date Written: April 2023

Abstract

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.

Suggested Citation

Brynjolfsson, Erik and Li, Danielle and Raymond, Lindsey, Generative Ai at Work (April 2023). NBER Working Paper No. w31161, Available at SSRN: https://ssrn.com/abstract=4426942

Erik Brynjolfsson (Contact Author)

National Bureau of Economic Research (NBER) ( email )

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HOME PAGE: http://brynjolfsson.com

Danielle Li

Massachusetts Institute of Technology (MIT) ( email )

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Cambridge, MA 02139-4307
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Lindsey Raymond

Massachusetts Institute of Technology (MIT) ( email )

77 Massachusetts Avenue
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Cambridge, MA 02139-4307
United States

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