AI Employment and Political Risk Disclosures in Earnings Calls

Erdinc Akyildirim, Gamze Ozturk Danisman and Steven Ongena
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Erdinc Akyildirim: University of Nottingham
Gamze Ozturk Danisman: Istanbul Bilgi University
Steven Ongena: University of Zurich - Department Finance; Swiss Finance Institute; KU Leuven; NTNU Business School; Centre for Economic Policy Research (CEPR)

No 25-56, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

Abstract: Using a panel of 929 U.S. publicly listed firms, this paper investigates the impact of artificial intelligence (AI) employment on the disclosure of political risk in corporate earnings calls. We utilize the firm-level AI employment measure developed by Babina et al. (2024), based on resume and job posting records. Furthermore, we supplement it with our newly generated AI disclosure indices at the firm level, created through textual analysis of earnings call transcripts. Our findings indicate that firms with greater AI employment are significantly less likely to disclose information about political risk during earnings calls. We propose a dual mechanism that underpins this association. First, AI enables narrative management: firms use AI tools to strategically alter the tone and wording of disclosures, avoiding phrases that may elicit unfavorable sentiment, leading to a reduction in reputational risk. Second, AI improves firms’ internal performance and risk management, hence reducing the need for voluntary political risk disclosures. Our findings add to the literature on voluntary disclosure and the economic implications of AI by indicating that AI, as a general-purpose technology, has unintended consequences for corporate transparency.

Keywords: Artificial Intelligence (AI); political risk; voluntary disclosures; earnings calls; textual analysis; AI disclosure index (search for similar items in EconPapers)
Pages: 40 pages
Date: 2025-06
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Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp2556

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