Green HRM, Green Leadership and Work Engagement in the Age of Artificial Intelligence: A Bibliometric–Systematic Review and Research Framework for Environmental Sustainability

Purpose Green human resource management (GHRM), green leadership and employee work engagement are each well established as levers of organisational environmental sustainability, and artificial intelligence (AI) is now entering the HR and leadership practices through which they operate. This review asks how these four literatures are structured, how far they have been connected, and what the available evidence implies about when AI strengthens or weakens the human pathway to environmental sustainability. Design/methodology/approach : A bibliometric–systematic review was conducted on 8,153 OpenAlex records (2010–2026). After PRISMA 2020-guided screening, 4,681 journal articles and reviews were mapped in VOSviewer 1.6.21 (term co-occurrence, overlay, density, reference co-citation and country co-authorship). A review set of 916 studies was coded for theory, design, sector and construct roles, and 87 intersection studies were critically appraised in depth. Findings The field has grown at 49.4% per year since 2015, yet its four streams remain weakly integrated: only 1.1% of documents examine GHRM, green leadership and engagement together, and only three also involve AI. Term mapping places AI in a firm-level capability cluster that is structurally distant from the leadership–engagement–behaviour cluster, and AI-linked studies rely on capability lenses (resource-based view, dynamic capabilities) rather than the employee-level theories that explain engagement. The few studies that test AI at the employee level report positive, null and negative effects, including AI awareness lowering green work engagement through job stress and AI substituting for green leadership. Originality/value The review provides the first quantitative evidence of the disconnection between AI research and the leadership–engagement mechanism of GHRM, and it develops a job demands–resources framework with seven propositions in which AI can act either as a green job resource or as a techno-demand. A theory–context–characteristics–methodology agenda and responsible-AI guidance for green people management are derived.