Generative AI at Work

Erik Brynjolfsson, Danielle Li, Lindsey Raymond · The Quarterly Journal of Economics · 4 Feb 2025

Where this sits in the debate

Will AI actually boost productivity and growth? · its finding: it depends (why studies differ)
Will AI widen inequality?

Direction of the finding as read from the abstract by an AI model (AI-written).

Key takeaway AI-written

Studying the staggered rollout of a generative AI assistant to 5,172 customer-support agents, finds it raised productivity (issues resolved per hour) by 15% on average, with the biggest gains for less experienced and lower-skilled workers, who saw both faster and higher-quality output; the most experienced agents saw little speed gain and slightly lower quality. Because the assistant appears to transfer top performers' know-how to novices, the paper is widely cited as evidence that generative AI can compress skill gaps within an occupation rather than simply replacing workers.

The paper in three steps AI-written

Written by an AI agent from the paper's abstract, which is the primary source and is quoted below.

The question

Does giving customer-support agents a generative AI assistant change their productivity, and for whom?

The approach

The authors study the staggered introduction of a generative AI conversational assistant across 5,172 customer-support agents, measuring issues resolved per hour, quality, learning, and customer behaviour.

The findings

Access to the assistant raises issues resolved per hour by 15% on average. Less experienced and lower-skilled agents gain in both speed and quality, while the most experienced see small speed gains and small quality declines. Gains are largest on moderately rare problems, and customers become more polite and less likely to ask for a manager.

How to read it: observational. Analysis of real-world firm, worker, or market data — realistic settings; causal claims depend on the identification strategy.

Limitations and counterpoints AI-written

The evidence comes from one setting, customer support, with one AI tool, so results may not carry over to other occupations or tools. Effects vary substantially across workers.

Abstract

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. The effects vary significantly across different agents. 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 moderately rare problems, where human agents have less baseline experience but the system still has adequate training data. Finally, we provide evidence that AI assistance improves the experience of work along several dimensions: customers are more polite and less likely to ask to speak to a manager.

About this publication

Academic journal. Published in an academic journal — typically peer-reviewed before publication, though indexing alone doesn't guarantee review depth.

Published: 2025 (21 months ago)
Citations: 591 (OpenAlex)

591 citations recorded by OpenAlex — too few 2025 papers in this collection for a fair comparison.

□ added to this collection in 2026.

Danielle Li, Erik Brynjolfsson, Lindsey Raymond signed the wemustactnow.ai letter · author affiliation matches seed institutions massachusetts institute of technology, stanford, stanford university — part of why this paper is in the collection.

Cited elsewhere in this guide

State of the debate: Will AI actually boost productivity and growth?