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AI washing: Strategic disclosure and backlash

Author

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  • Song, Xiapeng
  • Hou, Wenxuan
  • Ouyang, Zizhou
  • Hao, Fangmin

Abstract

As firms increasingly exaggerate artificial intelligence (AI) adoption in disclosures, we analyze market responses to unsubstantiated AI claims. Using BERT-based text classification and AI patent data for U.S. firms (2018–2023), we find that such narratives initially attract investors but ultimately yield negative market reactions and sustained underperformance. Results demonstrate market penalties for AI overclaiming through both short-term investor responses and long-term operational outcomes, extending narrative economics to emerging technologies. The study highlights that while narratives can mobilize attention, markets ultimately punish rhetoric that outpaces implementation.

Suggested Citation

  • Song, Xiapeng & Hou, Wenxuan & Ouyang, Zizhou & Hao, Fangmin, 2026. "AI washing: Strategic disclosure and backlash," Finance Research Letters, Elsevier, vol. 95(C).
    • Handle: RePEc:eee:finlet:v:95:y:2026:i:c:s1544612326002151
    DOI: 10.1016/j.frl.2026.109684
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    Cited by:

    1. Congluo Xu & Jiuyue Liu & Xiangsheng Zheng & Ziyang Li, 2026. "Dissipation of Debt Financing Privilege on Corporate AI Washing: Evidence from China," Papers 2605.16808, arXiv.org.

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    Keywords

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    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G30 - Financial Economics - - Corporate Finance and Governance - - - General

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