IDEAS home Printed from https://ideas.repec.org/a/spr/rvmgts/v19y2025i4d10.1007_s11846-024-00789-3.html
   My bibliography  Save this article

This (AI)n’t fair? Employee reactions to artificial intelligence (AI) in career development systems

Author

Listed:
  • Alina Köchling

    (Heinrich-Heine-Universität Düsseldorf)

  • Marius Claus Wehner

    (Heinrich-Heine-Universität Düsseldorf)

  • Sascha Alexander Ruhle

    (Tilburg University)

Abstract

Organizations increasingly implement AI for career development to enhance efficiency. However, there are concerns about employees’ acceptance of AI and the literature on employee acceptance of AI is still in its infancy. To address this research gap, integrating justice theory, we investigate the effects of the deciding entity (human, human and AI, and AI) and the impact of the data source (internal data, external data), on employees’ reactions. Using a scenario-based between-subject design, displaying a common situation in organizations (N = 280) and an additional causal-chain-approach (N = 157), we examined whether a decrease of human involvement in decision making diminishes employees’ perceived fairness and satisfaction with the career development process and increases their perceived privacy intrusion. Although we also considered other data sources to moderate the proposed relationships, we found no support for interaction effects. Finally, fairness and privacy intrusion mediated the influence of the deciding entity and data source on turnover intention and employer attractiveness, while satisfaction with the process did not. By addressing how the employees react to AI in career development–showing the negative reactions, our study holds considerable relevance for research and practice.

Suggested Citation

  • Alina Köchling & Marius Claus Wehner & Sascha Alexander Ruhle, 2025. "This (AI)n’t fair? Employee reactions to artificial intelligence (AI) in career development systems," Review of Managerial Science, Springer, vol. 19(4), pages 1195-1228, April.
  • Handle: RePEc:spr:rvmgts:v:19:y:2025:i:4:d:10.1007_s11846-024-00789-3
    DOI: 10.1007/s11846-024-00789-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11846-024-00789-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11846-024-00789-3?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; Employees’ reactions; Fairness; Organizational attractiveness; Privacy intrusion; Turnover intentions;
    All these keywords.

    JEL classification:

    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration
    • C99 - Mathematical and Quantitative Methods - - Design of Experiments - - - Other
    • M10 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - General

    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:spr:rvmgts:v:19:y:2025:i:4:d:10.1007_s11846-024-00789-3. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.