From automation to augmentation: Human resource's journey with artificial intelligence

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Elsevier
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This article examines the strategic integration of artificial intelligence (AI) in human resource management (HRM), highlighting both its opportunities and its challenges. While AI can improve HRM functions such as recruitment, performance evaluation and employee development, it also raises concerns related to algorithmic bias, technostress and resistance to change. To navigate these complexities, we present a structured two-tiered model that balances algorithmic efficiency with human-centred workforce development. Unlike previous studies that explore AI-driven human resource management in isolation, this research provides a comprehensive strategy for AI adoption that improves employee engagement, optimises HR decision-making and fosters organisational resilience. In addition to outlining the role of AI in human resource management, we explore its practical implications, ethical considerations and associated risks, offering strategies to mitigate bias, promote transparency and foster organisational readiness for AI-driven transformation. We also emphasise the importance of pilot studies and empirical validation to assess the model's effectiveness in diverse organisational contexts. By providing a structured roadmap for AI integration, this study contributes to the ongoing discourse on how human resource management can lead, rather than simply adapt to, AI-driven workforce transformation.

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Bastida, M., García, A. V., Taín, M. Á. V., & Araujo, M. D. R. (2025). From automation to augmentation: Human Resource's journey with Artificial Intelligence. Journal of Industrial Information Integration, 100872.https://doi.org/10.1016/J.JII.2025.100872

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Funding for open access charge Universidade de Vigo/CISUG.

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© 2025 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Attribution 4.0 International