Aggregate Productivity Gains from Artificial Intelligence: A Sectoral Perspective

Francesco Filippucci, Peter Gal and Matthias Schief

AEA Papers and Proceedings, 2026, vol. 116, 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.

JEL-codes: C45 D24 E23 L23 M15 O33 (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:aea:apandp:v:116:y:2026:p:31-35

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DOI: 10.1257/pandp.20261035

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