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

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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)

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.

Suggested Citation

  • Davidescu Adriana Anamaria & Bîrlan Ioana & Manta Eduard Mihai & Geambaşu Cristina Maria, 2025. "Artificial Intelligence in ESG and Sustainable Finance: A Bibliometric Analysis of Research Trends," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 19(1), pages 1506-1517.
    • Handle: RePEc:vrs:poicbe:v:19:y:2025:i:1:p:1506-1517:n:1013
    DOI: 10.2478/picbe-2025-0117
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