Growth in AI Knowledge

Joshua Gans

No 33907, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: How does artificial intelligence affect the creation of new knowledge and long-run economic growth? This paper develops a general equilibrium model where AI enhances decision-making by interpolating between existing knowledge points, reducing uncertainty within the boundaries of what is already known. This capability creates competing incentives for knowledge creation: AI makes dense knowledge clusters more valuable by enabling interpolation, but also reduces the penalty for knowledge gaps. We show that AI’s impact on growth depends on a critical threshold in its capabilities. When AI has a modest interpolation range, it encourages incremental research that increases knowledge density, raising growth when ideas are getting harder to find. When AI has an extensive range, it promotes exploratory research that reduces knowledge density, paradoxically slowing growth despite direct productivity gains. The welfare effects depend on both AI capabilities and market structure— monopolistic AI provision can improve welfare by restricting adoption and preventing excessive exploration, while competitive provision amplifies research distortions. These results suggest that policies limiting AI capabilities or promoting market power in AI provision may have unexpected benefits for innovation and growth when research productivity depends on knowledge density.

JEL-codes: O30 O31 O40 (search for similar items in EconPapers)
Date: 2025-06
New Economics Papers: this item is included in nep-ain, nep-cse, nep-gro, nep-ino, nep-reg and nep-tid
Note: PR
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