Generative AI at Work

Erik Brynjolfsson, Danielle Li and Lindsey Raymond

Papers from arXiv.org

Abstract: We study the staggered introduction of a generative AI-based conversational assistant using data from 5,172 customer support agents. Access to AI assistance increases worker productivity, as measured by issues resolved per hour, by 15\% on average, with substantial heterogeneity across workers. Less experienced and lower-skilled workers improve both the speed and quality of their output while the most experienced and highest-skilled workers see small gains in speed and small declines in quality. We also find evidence that AI assistance facilitates worker learning and improves English fluency, particularly among international agents. While AI systems improve with more training data, we find that the gains from AI adoption are largest for relatively rare problems, where human agents have less baseline training and experience. Finally, we provide evidence that AI assistance improves the experience of work along two key dimensions: customers are more polite and less likely to ask to speak to a manager.

Date: 2023-04, Revised 2024-11
New Economics Papers: this item is included in nep-big
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Citations: View citations in EconPapers (46)

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Working Paper: Generative AI at Work (2023)
Working Paper: Generative AI at Work (2023)
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