ARTIFICIAL INTELLIGENCE IN HUMAN RESOURCE MANAGEMENT AND EMPLOYEE WELL-BEING: A SYSTEMATIC LITERATURE REVIEW
DOI:
https://doi.org/10.36085/jam-ekis.v9i3.11136Abstract
The development of artificial intelligence (AI) in human resource management (HRM) has transformed HR practices, yet its impact on employee well-being continues to yield mixed findings. Furthermore, there remains a limited body of research that integrates the relationship between AI, technostress, and Humanistic Human Resource Management (Humanistic HRM) within a single conceptual framework. This study aims to synthesize the literature on the effects of AI implementation in HRM on employee well-being and to develop a conceptual framework that explains these relationships. The study employed a Systematic Literature Review (SLR) method following the PRISMA 2020 guidelines, analyzing articles retrieved from the Scopus and Google Scholar databases for the period 2019–2026. The results of the synthesis indicate that AI plays a dual role: as a job resource that enhances efficiency and the quality of decision-making, and as a job demand that can induce technostress if its implementation is not supported by adequate organizational governance. This study proposes a Human-Centered AI HRM Well-being Framework that integrates Job Demands-Resources Theory and Humanistic HRM, demonstrating that technostress weakens the impact of AI on employee well-being, while Humanistic HRM strengthens it. These findings enrich the theoretical development of AI HRM and serve as a foundation for organizations to build a digital transformation focused on employee well-being
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