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The Quarterly Journal of Economics

Generative AI at Work

2025-02-04760 citationsDOI 10.1093/qje/qjae044

Erik Brynjolfsson · Danielle Li · Lindsey Raymond

Key Takeaway

A staggered rollout to 5,172 customer-support agents increased issues resolved per hour by 15% on average. Less experienced workers gained most, while the most experienced saw smaller gains and slight quality declines.

AI-generated HIE assessment

Study Design

field study

title and abstract

What the Study Found

This study examines a staggered rollout of a generative AI conversational assistant among 5,172 customer-support agents. Access to assistance increased issues resolved per hour by 15% on average. Less experienced and lower-skilled workers improved both speed and quality, while the most experienced workers saw smaller speed gains and slight quality declines. The evidence comes from one firm and occupation, so generalization requires caution.

Original paper record

Evidence Strength

Evidence strengths

  • 5,172 workers
  • Real-world deployment data
  • Measures productivity, quality, learning, and worker experience

Limitations

  • Single firm and occupation
  • Staggered rollout is less controlled than a randomized experiment

What This Does Not Prove

This record does not establish effects beyond the population, tasks, duration, and methods described by the paper. It should not be read as a universal causal claim.

HIE Interpretation

Large real-world study showing heterogeneous effects of generative AI on worker productivity, learning, and quality.

AI-generated HIE assessment · AI assessment confidence 91

Related Topics

  • Human-AI Interaction
  • Artificial Intelligence
  • Learning
  • Social Intelligence

Connected Claims

Original Source

DOI 10.1093/qje/qjae044 ↗