Researcher ORCID Identifier

0009-0006-0526-906X

Graduation Year

2026

Date of Submission

4-2026

Document Type

Campus Only Senior Thesis

Degree Name

Bachelor of Arts

Department

Economics

Reader 1

Darren Filson

Abstract

This paper examines whether AI keyword mentions in quarterly earnings reports (10-Qs) are associated with abnormal returns, and whether this effect differs across technology and non-technology firms (SIC codes 7370-7379) and pre- and post-ChatGPT release in November 2022. I examine 4,898 quarterly earnings announcements by S&P 500 firms from March 2022 - December 2024. Cumulative abnormal returns (CARs) are calculated using the Fama-French 5-factor model, controlling for earning surprise. AI mentions are associated with a mean CAR that is 0.76 percentage points higher, (CÂR = 0.0076, p < .01), suggesting a positive short-run market response to AI disclosure. However, once pre/post-ChatGPT period effects are controlled for, the AI mention effect weakens and loses statistical significance (CÂR = 0.0049, p > .10). The interaction between AI mentions and the post-ChatGPT period indicator is also insignificant (β = 0.0003, p > .10). Overall, there is no statistically significant evidence that ChatGPT’s release amplified the market’s response to AI mentions in either tech or non-tech firms. However, tech firms mentioning AI earn significantly higher CARs than non-tech firms mentioning AI, with a premium of approximately 3.3 percentage points (β = 0.0327, p < .05), providing support for industry heterogeneity. The main conclusion is that markets reward AI mentions more for technology firms, but do not systematically reward it more following ChatGPT’s release.

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