Customer behavior and adoption · Quasi-experimental staggered introduction using workplace operational data.
Generative AI at Work
Brynjolfsson, E., Li, D., & Raymond, L. R. (2025). Generative AI at Work. The Quarterly Journal of Economics.
Plain-English take
In this study, Less-experienced and lower-skilled workers improved speed and quality more than experienced/high-skilled workers; AI assistance also improved customer sentiment and reduced requests to speak with a manager. The publisher search abstract reports a 15% average productivity increase. Founder use: Prioritize AI copilot deployment where onboarding and experience gaps are largest; track quality, customer sentiment, escalation, and retention together.
How much weight to give this
4.5/5 Strong experimental or quasi-experimental evidence for its stated setting
The 1–5 evidence-check score is a practical reading aid, not a formal peer review or a probability that a conclusion is true. It combines design strength (2 points), sample reporting (1), comparison/control clarity (1), and how much of the paper could be checked (1). Access affects how confidently this directory can assess a study, not the study's underlying quality. Blinding is reported separately because it is not relevant to every design.
Design description was checked against the directly fetched article source; conclusions remain specific to the studied setting.
Sample size or the source's lack of a reported count is stated explicitly.
The comparison or identification strategy is described from the article record.
A directly retrieved full paper is available.
Double-blind? Blinding is not stated in the source reviewed; that does not establish whether blinding was or was not used.
Research question
What the authors investigated
What happens when a generative-AI conversational assistant is introduced into real customer-support work, and who benefits most?
Design
Quasi-experimental staggered introduction using workplace operational data.
Sample and setting
5,172 customer-support agents using a conversational assistant in their work.
Reported result
What the study found
Less-experienced and lower-skilled workers improved speed and quality more than experienced/high-skilled workers; AI assistance also improved customer sentiment and reduced requests to speak with a manager. The publisher search abstract reports a 15% average productivity increase.
This is a paraphrase of the source. Check the original paper for definitions, estimates, statistical uncertainty and analysis details.
Scope and transfer
Limitations to keep in view
One employer and support workflow; staggered adoption is not a pure randomized trial, and agent, customer, and tool effects may be context-specific.
Possible founder application
Prioritize AI copilot deployment where onboarding and experience gaps are largest; track quality, customer sentiment, escalation, and retention together.
Evidence access
Open working paper PDF captured from arXiv
Publisher page directly retrieved with Firecrawl; scrape reference 01a1227f-0fec-77ae-b61b-74f5f6c2b64c. Claims are limited to the reported article record. Correction notices were not separately checked.
If only an abstract or metadata was available, the profile is limited to claims supported there. A paper's paywall does not change its evidentiary status, but it limits what we can substantiate from accessible text.