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Artificial intelligence as self-learning capital

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  • Gersbach, Hans
  • Komarov, Evgenij
  • von Maydell, Richard

Abstract

We develop a tractable model of Artificial Intelligence (AI) as self-learning capital that improves through application. An AI sector and an applied research (AR) sector produce inputs for a final goods firm and compete for high-skilled labor, benefiting from mutual spillovers. The economy undergoes four tipping points, with initial AI growth driven by entrepreneurs and skilled workers, before reversing direction. In the steady state, AI advances autonomously via spillovers from AR. We show that well-designed subsidies and taxes — such as an AI tax once learning becomes self-sustaining — can guide labor allocation toward socially optimal outcomes.

Suggested Citation

  • Gersbach, Hans & Komarov, Evgenij & von Maydell, Richard, 2025. "Artificial intelligence as self-learning capital," Economic Modelling, Elsevier, vol. 153(C).
    • Handle: RePEc:eee:ecmode:v:153:y:2025:i:c:s0264999325002160
    DOI: 10.1016/j.econmod.2025.107221
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    JEL classification:

    • E13 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Neoclassical
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models

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