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

Nabila El Boukhari () and Mounia Filali
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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)

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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.

Keywords: Intelligence Artificielle; gestion des ressources humaines; IA; GRH; performance opérationnelle; Organisation marocaine. JEL Classification : O15 Type du papier : Recherche Théorique Artificial Intelligence; Human Resource Management; Operational Performance. Classification JEL: O15. Paper type: Theoretical Research; Intelligence Artificielle gestion des ressources humaines IA GRH performance opérationnelle Organisation marocaine. JEL Classification : O15 Type du papier : Recherche Théorique Artificial Intelligence Human Resource Management IA GRH Operational Performance. Classification JEL: O15. Paper type: Theoretical Research (search for similar items in EconPapers)
Date: 2025-09-06
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Published in International Journal of Accounting, Finance, Auditing, Management and Economics, 2025

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