IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-05243494.html
   My bibliography  Save this paper

Framework of artificial intelligence on human resources management: Leveraging the transformation and performance in Moroccan companies
[Perspective de l'intelligence artificielle sur la gestion des ressources humaines : Un accélérateur de transformation et de performance dans les entreprises marocaines Framework of artificial intelligence on human resources management: Leveraging the transformation and performance in Moroccan companies]

Author

Listed:
  • Nabila El Boukhari

    (UH2C - Université Hassan II de Casablanca = University of Hassan II Casablanca = جامعة الحسن الثاني (ar))

  • Mounia Filali

    (UH2C - Université Hassan II de Casablanca = University of Hassan II Casablanca = جامعة الحسن الثاني (ar))

Abstract

Artificial intelligence represents a transformative force in Human Resource Management (HRM), capable of helping Moroccan companies reach a new frontier of operational efficiency, data-driven decision-making, and employee experience. However, its potential is currently constrained by limited investment resources and, potentially, by cultural realities. This integrative review aims to synthesize the state of the art by combining narrative and conceptual perspectives. The significance of our study lies in the need to mobilize theoretical frameworks such as the Technology Acceptance Model (TAM), the Diffusion of Innovations Theory, and the Resource-Based View (RBV) to describe the drivers and barriers to AI integration in HRM in Morocco. If achieved, this will pave the way for Moroccan organizations to fully leverage AI in HR functions, including recruitment, training, and performance management. The study provides a framework for companies considering the adoption of AI within their HR departments. It sheds light on the main enablers and obstacles of AI adoption, offering recommendations to mitigate challenges such as resistance to change and inadequate skills. For instance, the study advocates training initiatives to equip HR professionals with the necessary competencies, as well as the establishment of digital infrastructures to effectively support AI systems. Finally, the paper emphasizes that AI must be deployed responsibly, including the development of guidelines to prevent algorithmic bias and safeguard private data.

Suggested Citation

  • Nabila El Boukhari & Mounia Filali, 2025. "Framework of artificial intelligence on human resources management: Leveraging the transformation and performance in Moroccan companies [Perspective de l'intelligence artificielle sur la gestion de," Post-Print hal-05243494, HAL.
  • Handle: RePEc:hal:journl:hal-05243494
    Note: View the original document on HAL open archive server: https://hal.science/hal-05243494v1
    as

    Download full text from publisher

    File URL: https://hal.science/hal-05243494v1/document
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration

    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:hal:journl:hal-05243494. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.