IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v73y2025ics1544612324017033.html
   My bibliography  Save this article

Impact of artificial intelligence on the labor income distribution: Labor substitution or production upgrading?

Author

Listed:
  • Wang, Changlin
  • Jiao, Du

Abstract

The extensive adoption of artificial intelligence (AI) technologies has sparked debates about their impact on labor markets. However, there is still limited empirical evidence on AI's impact on labor income distribution, particularly in emerging economies. While existing research focuses mainly on job displacement risks, few focus on how AI affects labor compensation in corporate settings. This study examines how AI adoption affects labor income share through a mediation analysis framework using a comprehensive dataset of 25,156 firm-year observations from Chinese listed companies (2010–2022). Our findings show that AI implementation positively influences labor income share through two key channels: improved innovation capacity and accelerated technology upgrading. These effects are more pronounced in nonstate-owned enterprises and nonheavy-polluting industries. These results challenge the conventional narrative of technology-driven labor displacement, suggesting that AI adoption, combined with investments in innovation and human capital, can promote a more equitable distribution of corporate income.

Suggested Citation

  • Wang, Changlin & Jiao, Du, 2025. "Impact of artificial intelligence on the labor income distribution: Labor substitution or production upgrading?," Finance Research Letters, Elsevier, vol. 73(C).
  • Handle: RePEc:eee:finlet:v:73:y:2025:i:c:s1544612324017033
    DOI: 10.1016/j.frl.2024.106674
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612324017033
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.frl.2024.106674?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    Artificial intelligence; Labor income share; Innovation capacity; Technology Upgrading;
    All these keywords.

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance
    • M54 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Labor Management

    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:eee:finlet:v:73:y:2025:i:c:s1544612324017033. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    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.