IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-05203151.html
   My bibliography  Save this paper

Advanced strategies in human resources management: AI serving the armed forces
[Stratégies avancées en gestion des ressources humaines : l’IA au service des armées]

Author

Listed:
  • Jérôme Baray

    (ARGUMans - Laboratoire de recherche en gestion Le Mans Université - UM - Le Mans Université)

  • David Legrand

    (ARGUMans - Laboratoire de recherche en gestion Le Mans Université - UM - Le Mans Université)

Abstract

In the military sector, where operational demands are high and competition for specialized talent is growing, human resource management (HRM) has become a key driver of effectiveness and resilience. This article examines the specific challenges of military HRM—including retention, mobility, recruitment, and skill management—while accounting for extreme environments and generational shifts. The integration of artificial intelligence (AI) and optimization models enables a predictive, personalized, and agile HRM system, grounded in the concept of a digital twin. This digital twin dynamically models personnel, hierarchical structures, and logistical constraints. Leveraging advanced algorithms (genetic, multi-objective) and geographic information systems (GIS), it optimizes HR planning, workforce allocation, training strategies, and external interactions. The article proposes a conceptual framework for enhanced military HRM, combining AI, simulation, and strategic optimization to meet the complex demands of modern defense organizations.

Suggested Citation

  • Jérôme Baray & David Legrand, 2025. "Advanced strategies in human resources management: AI serving the armed forces [Stratégies avancées en gestion des ressources humaines : l’IA au service des armées]," Post-Print hal-05203151, HAL.
  • Handle: RePEc:hal:journl:hal-05203151
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;

    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-05203151. 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.