AI-Enabled Green HRM Research Surges, Bibliometric Study Finds

Artificial intelligence and green human resource management have rapidly converged into a distinct research field, according to a bibliometric review published in Discover Sustainability. The study, led by Lakshmi Shetty and colleagues including Ashish Dwivedi and Noor Ulain Rizvi, mapped the intellectual structure, thematic evolution and collaboration networks of the AI-enabled Green HRM literature using 94 publications indexed in Scopus between 2019 and 2026. The analysis, carried out with the Biblioshiny package in the R-Studio environment, revealed an annual growth rate of 57.46 percent in publications, with the literature almost quadrupling in 2024 and 2025.

Thematic clustering of the corpus identified key research streams linking AI, sustainable development and Green HRM practices. Within these clusters, the literature examines how machine learning, algorithmic management and digital transformation tools affect the recruitment, development, retention and motivation of environmentally responsible employees. The review also points to areas of synergy between AI capabilities and Green HRM outcomes, including improved measurement of environmental performance, prediction of employee green behaviours, and sustainability-oriented talent management.

Beyond mapping themes, the study posed two research questions: which thematic clusters and evolutionary trajectories dominate the field between 2019 and 2026, and which countries, institutions and authors form the core intellectual networks driving the research, along with the collaboration patterns in their work. By quantifying growth and visualizing collaboration networks, the review offers researchers a structured picture of where the literature has been and where the intellectual centre of gravity currently lies. The review also proposes a forward-looking research agenda.

Its most prominent recommendation concerns emerging economies, where the interface between digital transformation and green governance, the authors write, holds substantial potential that remains largely unexplored. They frame this as a priority for future studies, alongside the theoretical implications and management considerations drawn from the thematic analysis. As a bibliometric study, the work describes the state and structure of published research rather than testing any intervention in workplaces.

Its findings are limited to the 94 Scopus-indexed publications in its dataset and the 2019 to 2026 window, and the analysis was conducted on an early-access, peer-reviewed accepted version of the article. Even so, the reported growth figures and thematic map give researchers and practitioners a quantitative snapshot of how AI and green human resource management are being studied together, and a baseline against which the field's next phase of development can be measured.

Subject of Research: Bibliometric analysis of the AI-enabled green human resource management research field

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

Article References: Shetty, L., Dwivedi, A., Srivastava, S., Dubey, S., & Rizvi, N. U. (2026). A bibliometric analysis of intellectual structure and thematic evolution in artificial intelligence enabled green human resource management for environmental sustainability. Discover Sustainability. https://doi.org/10.1007/s43621-026-04611-w

Image Credits: AI Generated

DOI: 10.1007/s43621-026-04611-w

Keywords: artificial intelligence, green human resource management, bibliometrics, environmental sustainability, Scopus, thematic evolution, machine learning, digital transformation, talent management, emerging economies, Discover Sustainability, bibliometric