Do OpenAI's Activities Affect Big Tech?: Implications from Event Study Results

Shinichiro Terada

33rd European Regional ITS Conference, Edinburgh, 2025: Digital innovation and transformation in uncertain times from International Telecommunications Society (ITS)

Abstract: This paper investigates whether the activities of OpenAI—particularly those related to its generative AI product, ChatGPT—have affected major U.S. technology firms, Big Tech, collectively referred to as GAFAM (Alphabet/Google, Apple, Meta/Facebook, Amazon, and Microsoft). Using a short-term event study methodology, we analyze the abnormal stock returns of these firms in response to key OpenAI-related events, including product launches, corporate investments, and technological integrations. Our empirical analysis reveals three main findings. First, the release of ChatGPT had no statistically significant effect on the stock returns of each of GAFAM firms. Second, Microsoft's direct investments in OpenAI, including a $1 billion and a multi-billion-dollar deal, resulted in neutral market responses, suggesting a balance between cost and expected strategic benefit. Third, collaborations that integrated OpenAI's technology into Microsoft's Bing and Edge, and Apple's iOS ecosystem yielded statistically significant positive abnormal returns for the respective firms. These results imply that OpenAI's competitive impact on GAFAM is not direct rivalry but rather complementary enhancement. OpenAI's AI capabilities function as a core competence that strengthens the existing revenue-generating platforms of Big Tech. This suggests a business ecosystem in which AI technologies are not isolated strategic assets, but rather enablers of broader corporate competitiveness.

Date: 2025
New Economics Papers: this item is included in nep-com
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.econstor.eu/bitstream/10419/331311/1/ITS-E-2025-66.pdf (application/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:zbw:itse25:331311

Access Statistics for this paper

More papers in 33rd European Regional ITS Conference, Edinburgh, 2025: Digital innovation and transformation in uncertain times from International Telecommunications Society (ITS)
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics ().