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B. Bahar
Universitas Muslim Indonesia
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Library & Information Science Social Sciences

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AI-Enabled Sustainable Human Resource Management: Employee Well-Being, Ethical Governance, Organizational Resilience, and Sustainable Development B. Bahar; Baharuddin Semmaila; Baso Amang; Aryati Arfah; Muh. Arif; T. Tenriwaru
Golden Ratio of Mapping Idea and Literature Format Vol. 6 No. 4 (2026): August – October
Publisher : Manunggal Halim Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52970/grmilf.v6i4.2686

Abstract

Artificial intelligence has moved from the periphery of human resource management to its operational core, and its integration with sustainable HRM is now a strategically significant but contested field. This systematic literature review synthesises peer-reviewed, Scopus- and Web of Science–indexed research, with emphasis on 2020–2026 and retention of seminal theoretical sources, to examine how AI-enabled sustainable HRM shapes employee well-being, ethical governance, organizational resilience, and contributions to the Sustainable Development Goals (SDGs 3, 5, 8, 9, 10, and 16). Theoretically, the review appraises Job Demands–Resources, Conservation of Resources, Social Exchange, Dynamic Capabilities, Stakeholder, and Institutional perspectives, retaining only those warranted by the evidence. The synthesis identifies a consistent dual-process pattern: AI resources raise engagement, job satisfaction, and productivity, whereas AI demands generate technostress, exhaustion, work–family conflict, and job insecurity. Ethical governance emerges as a precondition rather than a compliance add-on, and organizational resilience depends on intellectual capital while being attenuated by environmental dynamism. The review also documents a fragmented theoretical base, heavy reliance on cross-sectional designs, inconsistent operationalisation of resilience, algorithmic management, and sustainable HRM, and thin organizational-level and SDG-outcome evidence. Its contribution is an explicitly exploratory integrated framework linking AI-enabled sustainable HRM to SDG contributions through the mutually conditioning pillars of well-being, governance, and resilience, with specified propositions, moderators, and boundary conditions.
Co-Authors Aryati Arfah Baharuddin Semmaila Baso Amang Muh. Arif Tenriwaru, T.