AI subsidies as a tool for redistribution

Subventions à l’IA comme outil de redistribution

Lucas Parmentier ()
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Lucas Parmentier: CEMOI - Centre d'Économie et de Management de l'Océan Indien - UR - Université de La Réunion

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Abstract: I study the optimal taxation of artificial intelligence (AI). My analysis highlights a wage-compression effect that provides a rationale for subsidizing AI, as AI adoption may reduce rather than increase wage inequality. When this effect outweighs AI's social costs, AI should be subsidized instead of taxed. I treat AI as a productive input distinct from robots, as the two technologies perform different ranges of tasks. Using numerical simulations, I demonstrate that the optimal policy for AI may differ sharply from that for robots. Under the benchmark calibration, AI is subsidized, whereas robots are taxed. Therefore, the case for taxing AI is weaker than is commonly assumed. When AI lowers the skill premium, fiscal policy may need to encourage, rather than slow, adoption.

Keywords: Artificial intelligence; Optimal taxation; Redistribution; Wage inequality; Technological change; Inégalités salariales; Progrès technique; Taxation optimale; Intelligence artificielle (search for similar items in EconPapers)
Date: 2026-11
Note: View the original document on HAL open archive server: https://hal.science/hal-05748060v1
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Published in Economic Modelling, 2026, 164, pp.107817. ⟨10.1016/j.econmod.2026.107817⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05748060

DOI: 10.1016/j.econmod.2026.107817

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