AI, productivity, and economic growth
Ceyhun Elgin · Routledge eBooks · 20 Oct 2026
Where this sits in the debate
- Will AI actually boost productivity and growth? · its finding: it depends (why studies differ)
Direction of the finding as read from the abstract by an AI model (AI-written).
Key takeaway AI-written
A book chapter on AI, productivity and long-run growth that explains why task-level efficiency gains may not show up quickly in aggregate statistics, covering the productivity paradox, intangible investment and the J-curve. It contrasts singularity-style scenarios with Baumol-style bottlenecks and argues AI's growth impact depends more on diffusion, reorganisation, competition and institutions than on model capability.
Abstract
This chapter examines how artificial intelligence (AI) may affect productivity and long-term economic growth. It begins by clarifying what economists mean by productivity, total factor productivity (TFP), and growth accounting, then explains why AI can raise task-level efficiency without immediately producing a visible aggregate productivity boom. The chapter develops the productivity paradox, the role of intangible complementary investment, the AI productivity J-curve, and the distinction between genuine productivity-enhancing innovation and so-so automation. It then analyzes the main channels through which AI may increase growth: cheaper prediction, process innovation, better allocation, scientific discovery, organizational redesign, and new products. The chapter also considers the limits of growth optimism by contrasting singularity-style scenarios with Baumol-style sectoral bottlenecks. The central claim is that AI’s growth impact will depend less on raw model capability than on diffusion, reorganization, competition, institutions, and the distribution of complementary capital.
About this publication
Academic journal. Published in an academic journal — typically peer-reviewed before publication, though indexing alone doesn't guarantee review depth.
- Published
- 2026 (recently)
- Citations
- 0 (OpenAlex)
0 citations recorded by OpenAlex — too few 2026 papers in this collection for a fair comparison.
Related by theme, not necessarily by method or conclusion.
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