ARTIFICIAL INTELLIGENCE AND ESG: TRENDS, GAPS, AND OPPORTUNITIES IN BIBLIOMETRIC ANALYSIS

Abstract

This study presents a comprehensive bibliometric analysis of scholarly literature at the intersection of Artificial Intelligence (AI) and Environmental, Social, and Governance (ESG) practices. Using data from the Scopus database (2015–2025) and analyzed through VOSviewer 1.6.20, a total of 885 relevant documents were mapped to identify major trends, gaps, and opportunities within this emerging research field. The analysis reveals a significant growth in publications from 2022 onward, with a peak in 2024, reflecting the increasing relevance of AI-driven solutions for ESG implementation, reporting, and decision-making. Key findings highlight the dominance of themes such as technological innovation, machine learning in finance, and sustainability metrics. Three main thematic clusters were identified: digital infrastructure and ESG reporting systems; bibliometric and conceptual studies; and AI applications in investment and financial performance. Despite the promising integration of AI to enhance ESG outcomes, the study also uncovers gaps related to ethical concerns, regulatory frameworks, and underrepresentation in developing countries. This research contributes to a deeper understanding of the evolving knowledge landscape and offers strategic insights for academics, practitioners, and policymakers aiming to harness AI for sustainable and responsible governance.