Advanced strategies in human resources management: AI serving the armed forces

Stratégies avancées en gestion des ressources humaines: l’IA au service des armées

Jérôme Baray () and David Legrand ()
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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

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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.

Keywords: human resource management; military; artificial intelligence; digital twin; optimization; mobility; skills; HR prediction; optimisation; gestion des ressources humaines; armées; intelligence artificielle; double numérique; prédiction RH; compétences; mobilité (search for similar items in EconPapers)
Date: 2025-07-30
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Published in Revue Défense Nationale, 2025, T 1734

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05203151

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