IDEAS home Printed from https://ideas.repec.org/a/ora/jrojbe/v10y2025i1p108-120.html
   My bibliography  Save this article

Challenges Of Artificial Intelligence For Knowledge Management Systems: A Bibliometric Analysis Perspective

Author

Listed:
  • Constantin Bratianu

    (Bucharest University of Economic Studies, UNESCO Department for Business Administration, Bucharest, Romania; Academy of Romanian Scientists, Romania.)

  • Alexandru Ioan

    (National University of Political Studies and Public Administration, the Faculty of Management, Bucharest, Romania)

Abstract

This paper explores the opportunities and challenges associated with integrating artificial intelligence (AI) into knowledge management systems (KMS), by using a bibliometric analysis. The rapid advancement of AI technologies, particularly generative models, has opened new avenues for enhancing KMS theories and practices. The study examines publication trends, key contributors, predominant research themes, and the practical applications of AI in KMS, with a specific focus on how these technologies can transform knowledge creation, sharing, and dissemination. The study draws on data from the Scopus database, revealing the significant impact of AI on KMS practices, particularly its capacity to enhance knowledge transfer, support decision-making processes, and foster organizational learning. However, the study also identifies several challenges, including ethical concerns, the interpretability of AI-driven tools, and the scalability of AI methods. The analysis underscores the need for further research in addressing these challenges and exploring the full potential of AI to fill knowledge gaps and create new knowledge artefacts. This paper provides valuable insights for scholars, practitioners, and organizations looking to harness AI for improving KMS theories and practices, offering a systematic analysis for future research on the evolving intersection of AI and KMS.

Suggested Citation

  • Constantin Bratianu & Alexandru Ioan, 2025. "Challenges Of Artificial Intelligence For Knowledge Management Systems: A Bibliometric Analysis Perspective," Oradea Journal of Business and Economics, University of Oradea, Faculty of Economics, vol. 10(1), pages 108-120, March.
    • Handle: RePEc:ora:jrojbe:v:10:y:2025:i:1:p:108-120
    DOI: http://doi.org/10.47535/1991ojbe209
    as

    Download full text from publisher

    File URL: https://ojbe.steconomiceuoradea.ro/wp-content/uploads/2025/04/8-OJBE-paper-392-Bratianu.pdf
    Download Restriction: no
    File URL: https://libkey.io/http://doi.org/10.47535/1991ojbe209?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

    Keywords

    knowledge management systems; artificial intelligence; deep learning; large language models; bibliometric analysis;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

    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:ora:jrojbe:v:10:y:2025:i:1:p:108-120. 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: Tomina SAVEANU The email address of this maintainer does not seem to be valid anymore. Please ask Tomina SAVEANU to update the entry or send us the correct address (email available below). General contact details of provider: https://edirc.repec.org/data/feoraro.html .

    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.