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Generative AI and Firm Values
Open accessAbstract
What are the effects of recent advances in Generative AI on the value of firms?Our study offers a quantitative answer to this question for U.S. publicly traded companies based on the exposures of their workforce to Generative AI.Our novel firm-level measure of workforce exposure to Generative AI is validated by data from earnings calls, and has intuitive relationships with firm and industry-level characteristics.Using Artificial Minus Human portfolios that are long firms with higher exposures and short firms with lower exposures, we show that higher-exposure firms earned excess returns that are 0.4% higher on a daily basis than returns of firms with lower exposures following the release of ChatGPT.Although this release was generally received by investors as good news for more exposed firms, there is wide variation across and within industries, consistent with the substantive disruptive potential of Generative AI technologies.
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“Eisfeldt et al. (2023) create portfolios of companies that have high and low exposure to generative AI like ChatGPT and find that higher-exposure firms earned excess returns that are 0.4% higher on a daily basis (which equates to over 100% on an annualized basis) than lower-exposure firms-suggesting that, 'according to investors, ChatGPT represents an important shock to corporate valuations.'”
From Is it all hype? ChatGPT’s performance and disruptive potential in the accounting and auditing industries (2024) · cites this paper as Eisfeldt et al. (2023)
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
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“Because firms rarely disclose their AI-specific capital expenditures, the literature often measures firm-level AI adoption using labor market data.”
From The Growth and Performance of Artificial Intelligence in Asset Management (2026) · cites this paper as Eisfeldt, Schubert, Taska, and Zhang (2026)
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Cites
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Acemoglu, D., & Autor, D. (2011) · Handbook of Labor Economics · doi:10.1016/s0169-7218(11)02410-5 · Cited by 3,799
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Cited by
Sorted by citations
Can ChatGPT forecast stock price movements? Return predictability and large language models
Lopez-Lira, A., & Tang, Y. (2026) · Journal of Financial Economics · doi:10.1016/j.jfineco.2026.104335 · Cited by 425
Eulerich, M., Sanatizadeh, A., Vakilzadeh, H., & Wood, D. A. (2024) · Review of Accounting Studies · doi:10.1007/s11142-024-09833-9 · Cited by 195
“Finally, Eisfeldt et al. (2023) create portfolios of companies that have high and low exposure to generative AI like ChatGPT and find that higher-exposure firms earned excess returns that are 0.4% higher on a daily basis (which equates to over 100% on an annualized basis) than lower-exposure…”
InfluentialStill Waters, Rapid Currents: Early Labor Market Transformation under Generative AI
Humlum, A., & Vestergaard, E. (2025) · doi:10.3386/w33777 · Cited by 68
The Rapid Adoption of Generative AI
Bick, A., Blandin, A., & Deming, D. J. (2026) · Management Science · doi:10.1287/mnsc.2025.02523 · Cited by 48
Human + AI in accounting: Early evidence from the field
Choi, J. H., & Xie, C. L. (2026) · Journal of Accounting Research · doi:10.1111/1475-679x.70052 · Cited by 30
Large language models at work in China’s labor market
Chen, Q., Ge, J., Xie, H., Xu, X., & Yang, Y. (2025) · China Economic Review · doi:10.1016/j.chieco.2025.102413 · Cited by 17
Organizational Technology Ladders: Remote Work and Generative AI Adoption
Schubert, G. (2026) · Academy of Management Proceedings · doi:10.5465/amproc.2026.22251abstract · Cited by 5
Self-citationThe Growth and Performance of Artificial Intelligence in Asset Management
Chen, S., Sialm, C., & Xu, D. (2026) · National Bureau of Economic Research · doi:10.3386/w35273
Metadata
- Authors
- Eisfeldt, A., Schubert, G., Zhang, M. B., & Taska, B.
- Affiliations
- National Bureau of Economic Research (US)
- Venue
- National Bureau of Economic Research
- Publisher
- American Finance Association
- Published
- 2026-08-30
- OpenAlex
- W4375852308
- Cited by
- 173
- References
- 2
- Citations by year
- 2026: 63
- Type
- report
- Language
- en
- Open access
- green
- doi.org
- Locations
- National Bureau of Economic Research (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Finance › Financial Markets and Investment Strategies
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Firm Innovation and Growth
- Keywords
- generative AI, firm value, ChatGPT, abnormal returns, earnings conference calls, AI disruption, listed companies
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