Transformative AI and demand bottlenecks
Phurichai Rungcharoenkitkul
No 1381, BIS Working Papers from Bank for International Settlements
Abstract:
Transformative AI promises to accelerate growth through productivity enhancement and automation. Yet automation on such a scale would raise the share of investment in output, potentially starving AI innovation of returns from a shrinking consumer market. We propose an endogenous growth framework to study this interaction, featuring research and entry decisions that propel AI advances but whose costs must be paid for by consumer demand. We identify several scenarios, spanning transformative AI, a demand bottleneck outcome where thinning consumer demand stalls AI progress, and intermediate cases in between. When anchored to evidence, the calibrated model points to the demand bottleneck as a highly plausible scenario, and projects more moderate growth in the coming years relative to recent studies such as Korinek et al. (2026). We draw policy implications, including for the natural rate of interest.
Keywords: artificial intelligence; automation; natural rate of interest; demand-pull innovation; market size; endogenous growth; demand bottlenecks (search for similar items in EconPapers)
JEL-codes: E22 E43 E52 O31 O33 O41 (search for similar items in EconPapers)
Date: 2026-10
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Persistent link: https://EconPapers.repec.org/RePEc:bis:biswps:1381
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