Artificial Intelligence in Green Human Resource Management: Examining the Mediating Role of Employee Engagement in Attaining Organizational Sustainability

Purpose: Artificial intelligence (AI) is entering green human resource management (GHRM), yet the employee-level mechanism through which AI-enabled green HR practices produce organizational sustainability remains unclear. This study maps the field and examines whether employee engagement has been theorized as that mechanism. Design/methodology/approach: A VOSviewer-based bibliometric analysis was combined with a critical literature analysis. OpenAlex records (2010–2026) were screened using a PRISMA-informed protocol, yielding a core corpus of 206 studies on AI/digital-enabled green or sustainable HRM and a comparison corpus of 579 studies on GHRM and engagement. Performance, co-citation, term co-occurrence, overlay and co-authorship analyses were performed. Findings: The field is nascent: 77.7% of the core studies appeared in 2025–2026. Of four co-citation clusters, AI and sustainable-HRM scholarship is the least connected to research on how GHRM shapes employee behaviour. Only five core studies (2.4%) model engagement as a mediator, and only 8.3% of GHRM engagement studies mention AI. Capability theories and cross-sectional designs dominate, and emerging evidence shows that AI can also weaken green outcomes. Originality/value: Integrating job demands–resources theory with ability–motivation–opportunity, social exchange and socio-technical perspectives, the study proposes a dual-pathway framework in which AI-enabled GHRM can build or erode engagement, and derives seven propositions, boundary conditions and a research agenda. Practical implications: AI should be deployed in GHRM as an engagement-building job resource rather than as a monitoring tool, and the environmental footprint of AI systems should be counted against claimed sustainability gains. Article classification: Literature review (bibliometric and critical review with conceptual framework)