Artificial Intelligence in ESG and Sustainable Finance: A Bibliometric Analysis of Research Trends

Davidescu Adriana Anamaria (), Bîrlan Ioana (), Manta Eduard Mihai () and Geambaşu Cristina Maria ()
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Davidescu Adriana Anamaria: Bucharest University of Economic Studies, Bucharest, Romania
Bîrlan Ioana: Bucharest University of Economic Studies, Bucharest, Romania
Manta Eduard Mihai: Bucharest University of Economic Studies, Bucharest, Romania
Geambaşu Cristina Maria: Bucharest University of Economic Studies, Bucharest, Romania

Proceedings of the International Conference on Business Excellence, 2025, vol. 19, issue 1, 1506-1517

Abstract: The integration of Artificial Intelligence (AI), including Machine Learning (ML) and Natural Language Processing (NLP), into Environmental, Social, and Governance (ESG) frameworks and sustainable finance has gained significant academic and industry attention. This study presents a bibliometric analysis of research at the intersection of AI, ESG, and sustainable finance, using Web of Science data from 2004 to 2025. Our analysis maps the evolution of research trends, identifies key authors, influential publications, and collaboration networks, and explores the intellectual structure of the field. Using co-citation analysis, keyword co-occurrence mapping, and thematic clustering, we reveal how AI-driven methodologies have shaped ESG assessments, sustainable investment strategies, and financial decision-making. Findings highlight a sharp rise in AI applications in ESG post-2015, particularly in ESG risk modelling, climate analytics, and AI-driven reporting. This study provides a comprehensive overview of the evolving academic discourse, identifying emerging research directions and challenges related to data standardization, transparency, and ethical AI applications in sustainability.

Keywords: Bibliometric analysis; Artificial Intelligence; Machine Learning; NLP; ESG; Sustainable Finance (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:poicbe:v:19:y:2025:i:1:p:1506-1517:n:1013

DOI: 10.2478/picbe-2025-0117

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