AEA Papers and Proceedings
ISSN 2574-0768 (Print) | ISSN 2574-0776 (Online)
Aggregate Productivity Gains from Artificial Intelligence: A Sectoral Perspective
AEA Papers and Proceedings
(pp. 31–35)
Abstract
Artificial intelligence raises productivity in specific tasks, but its aggregate impact remains debated. We project productivity gains from AI for 65 US industries and aggregate them in a multisector general-equilibrium framework, showing that AI could contribute up to 0.9 percentage points to annual aggregate TFP growth over the next decade. Gains are largest in knowledge-intensive services and smallest in manual task-intensive activities. With uneven sectoral gains, a Baumol effect could limit aggregate growth, but this channel remains quantitatively small when the cross-sectoral elasticity of substitution in final demand is sufficiently large or when factors can freely reallocate across sectors.Citation
Filippucci, Francesco, Peter Gal, and Matthias Schief. 2026. "Aggregate Productivity Gains from Artificial Intelligence: A Sectoral Perspective." AEA Papers and Proceedings 116: 31–35. DOI: 10.1257/pandp.20261035Additional Materials
JEL Classification
- C45 Neural Networks and Related Topics
- D24 Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
- E23 Macroeconomics: Production
- L23 Organization of Production
- M15 IT Management
- O33 Technological Change: Choices and Consequences; Diffusion Processes