Artificial Intelligence, Human Capital Risk and Household Portfolio Choice

Kristoffer Berg, Jane Danyu-Zhang, Luigi Dante Gaviano and Constantine Yannelis

Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge

Abstract: For most households, human capital is the largest asset they own, and rapid advances in artificial intelligence (AI) may change its value. This paper studies whether workers whose occupations are more exposed to AI use financial and labor markets to hedge this risk, by investing in firms that gain from the new technology. We develop a portfolio-choice model with nontradable human capital in which AI-related equity pays off in states where exposed workers’ labor income falls through technological unemployment. The model predicts that more exposed workers should hold more equity, especially when human capital is large relative to financial wealth. We test these predictions using linked Norwegian administrative data on workers’ occupations, employers, income, wealth, and equity holdings. Workers in more AI-exposed occupations are more likely to participate in equity markets and, conditional on participation, hold more equity, especially from firms located in countries with firms more exposed to the AI boom. The exposure–equity relationship is stronger for younger workers, consistent with life-cycle hedging. Following the release of ChatGPT, workers with greater AI exposure also become more likely to move into lower-exposure industries and senior management roles. Our results highlight a channel through which financial markets may partially insure workers against technological unemployment.

Keywords: Artificial Intelligence; Portfolio Allocation; Income Risk; Stock Market Participation (search for similar items in EconPapers)
JEL-codes: G11 G51 J32 (search for similar items in EconPapers)
Date: 2026-07-27
New Economics Papers: this item is included in nep-ain, nep-fdg and nep-lma
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.econ.cam.ac.uk/sites/default/files/pub ... pe-pdfs/cwpe2660.pdf

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cam:camdae:2660

Access Statistics for this paper

More papers in Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge
Bibliographic data for series maintained by Jake Dyer ().