IDEAS home Printed from https://ideas.repec.org/a/nms/untern/10.5771-0042-059x-2023-2-134.html
   My bibliography  Save this article

Does AI bring value to firms? Value relevance of AI disclosures

Author

Listed:
  • Wang, Tawei
  • Yen, Ju-Chun

Abstract

This study examines the value relevance of a firm’s artificial intelligence (AI) implementation and its awareness of the related risks. We proxy a firm’s AI implementation by AI-related disclosures and risk factors in 10-K filings to the U.S. Securities and Exchange Commission. Our results show that AI implementation disclosures in 10-K filings are more value relevant than those without AI disclosures. We also find that the disclosed AI-related risk factors are value relevant, suggesting that investors positively value a firm’s AI risk awareness. By further classifying AI risk factors by a topical analysis of the latent Dirichlet allocation, we find that investors value AI-related risk factor disclosures more regarding security and data privacy. Finally, we find that when a firm has better board- or executive-level IT governance, investors place greater value on AI-related risk factor disclosures regarding business operations.

Suggested Citation

  • Wang, Tawei & Yen, Ju-Chun, 2023. "Does AI bring value to firms? Value relevance of AI disclosures," Die Unternehmung - Swiss Journal of Business Research and Practice, Nomos Verlagsgesellschaft mbH & Co. KG, vol. 77(2), pages 134-161.
    • Handle: RePEc:nms:untern:10.5771/0042-059x-2023-2-134
    DOI: 10.5771/0042-059X-2023-2-134
    as

    Download full text from publisher

    File URL: https://www.nomos-elibrary.de/10.5771/0042-059X-2023-2-134
    Download Restriction: no
    File URL: https://libkey.io/10.5771/0042-059X-2023-2-134?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nms:untern:10.5771/0042-059x-2023-2-134. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Nomos Verlagsgesellschaft mbH & Co. KG (email available below). General contact details of provider: http://www.nomos.de/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.