A bibliometric analysis of intellectual structure and thematic evolution in artificial intelligence enabled green human resource management for environmental sustainability

Abstract

Artificial Intelligence (AI) and Green Human Resource Management (HRM) are new frontiers in the field of organizational sustainability studies. This study aims to systematically capture the intellectual structure, thematic evolution and network collaboration in the AI-enabled Green HRM domain by using a bibliography data set of 94 publications listed in Scopus index (2019–2026). The articles were further analysed with the help of Biblioshiny package in the R-Studio environment. The data demonstrates an outstanding annual growth rate of 57.46%, and the literature in the field almost quadrupled in 2024/2025, highlighting the field's momentum. Thematic clusters, supported by key research papers relating to AI, sustainable development and Green HRM practices, highlight how AI tools such as machine learning, algorithmic management and digital transformation affect the recruitment, development, retention and motivation of employees who are environmentally responsible. The two research questions are: What are the dominant thematic clusters and evolutionary trajectories in the AI-enabled Green HRM literature 2019–2026? and Who are the countries, institutions and authors that form the core intellectual networks that energize this research field, and what patterns of collaboration are found in their work? The analysis reveals key areas of synergy between AI capabilities and outcomes of Green HRM, such as improved measurement of environmental performance, prediction of employee green behaviours, and sustainability-oriented talent management. In addition to theoretical implications and management considerations, there is a research agenda proposed that focuses on future research directions, especially in emerging economies where the digital transformation and green governance interface have great potential that has yet to be fully explored.