May 14, 2026

• Working Papers
• Publication
• Macroeconomy
• Workforce Development

Working Paper 2026-6

Abstract: We study how an automating technology affects career dynamics, human capital, and welfare in an economy where workers acquire skill through the tasks they perform. In a continuous-time general equilibrium model, learning-by-doing is determined jointly with the share of tasks automated, the frontier of tasks managers maintain, and the worker-to-manager career transition. Economies with high learning capacity admit pairs of stationary equilibria strictly ranked by the aggregate learning rate. Cheaper technology has opposite effects across the two: in the high-learning equilibrium, it raises welfare through the learning channel itself; in the low-learning equilibrium, it tips the economy into a human-capital trap. The planner's first-best combines a tax on automation profits with a subsidy on frontier maintenance expenditures at a common rate.

JEL classification: E23, E24, J24

Key words: human capital, learning-by-doing, automation, AI

https://doi.org/10.29338/wp2026-06

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Hassan Afrouzi is with Columbia University. Andrés Blanco is with the Federal Reserve Bank of Atlanta. Andres Drenik is with the University of Texas. Erik Hurst is with the University of Chicago Booth School of Business. The authors thank seminar participants at the University of Pennsylvania and the 2026 Pacific Macro Conference for useful comments. The views expressed herein are those of the authors and not necessarily those of the Board of Governors of the Federal Reserve System, the Federal Reserve Bank of Atlanta, or the Federal Reserve System.

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