Generative AI and Firm Values / Andrea L. Eisfeldt, Gregor Schubert, Miao Ben Zhang.

Format:

Book

Author/Creator:

Eisfeldt, Andrea L.

Contributor:

National Bureau of Economic Research.

Schubert, Gregor.

Zhang, Miao Ben.

Series:

Working Paper Series (National Bureau of Economic Research) no. w31222.

NBER working paper series no. w31222

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 2023.

Summary:

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.

Notes:

Print version record

May 2023.