IDEAS home Printed from https://ideas.repec.org/a/wly/mgtdec/v46y2025i3p1856-1870.html
   My bibliography  Save this article

Firm Performance on Artificial Intelligence Implementation

Author

Listed:
  • Cheng‐Kui Huang
  • Jheng‐Siang Lin

Abstract

In recent years, artificial intelligence (AI) has become a focal point in academic and business research. With breakthroughs in learning algorithms, AI applications in business operations are increasingly practical and impactful. AI offers tools for market analysis, decision‐making support, and innovations in business models and processes, presenting a significant turning point for firms. Despite this, questions remain about whether AI implementation yields measurable business value or is merely a trend, challenging enterprises and managers. This study provides a significant contribution by empirically examining AI impact on firm‐level performance through three key indicators: financial performance, productivity, and market value. Drawing on internal financial perspectives, this research reveals that while AI adoption enhances financial performance and market value, the advantages for AI first movers and better performers are not uniformly positive across all indicators. This nuanced analysis offers managers and stakeholders a deeper understanding of the tangible value of AI, guiding more informed implementation strategies.

Suggested Citation

  • Cheng‐Kui Huang & Jheng‐Siang Lin, 2025. "Firm Performance on Artificial Intelligence Implementation," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 46(3), pages 1856-1870, April.
  • Handle: RePEc:wly:mgtdec:v:46:y:2025:i:3:p:1856-1870
    DOI: 10.1002/mde.4486
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/mde.4486
    Download Restriction: no

    File URL: https://libkey.io/10.1002/mde.4486?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:wly:mgtdec:v:46:y:2025:i:3:p:1856-1870. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www3.interscience.wiley.com/cgi-bin/jhome/7976 .

    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.