Working Paper: NBER ID: w31161
Authors: Erik Brynjolfsson; Danielle Li; Lindsey R. Raymond
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.
Keywords: Generative AI; Productivity; Customer Support; Machine Learning
JEL Codes: D8; J24; M15; M51; O33
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Introduction of AI tool (C45) | Increased productivity (O49) |
| AI tool (C45) | Dissemination of best practices (O36) |
| Dissemination of best practices (O36) | Reduced experience gap (I24) |
| AI assistance (C45) | Improved customer sentiment (D12) |
| Improved customer sentiment (D12) | Enhanced employee retention (M51) |
| AI access (C45) | Enhanced performance for less skilled workers (J24) |
| AI tool (C45) | Convergence in communication patterns (L96) |
| AI assistance (C45) | Decrease in quality of interactions for highly skilled agents (L15) |