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<p>Organizations are increasingly integrating artificial intelligence (AI) into their sustainability strategies to track environmental footprint, strengthen corporate responsibility and enhance governance processes (so called ESG issues). The present review aims to synthesize research contribution on AI in ESG research stream, thus adding to the evolving discussion on AI-driven sustainability. The study focuses on three key research questions: performance structure of AI and ESG research stream, the current state of the research stream, and directions for future research. To address these research questions, the review employed performance and thematic analyses methods to analyse data from Scopus and Web of Science (WOS) published during the last fifteen years (2009–2024). The performance analysis reveals key insights regarding the most impactful articles, authors, sources, and contexts in the domain. Keyword analysis explores the present state of AI in ESG research stream, classifying and synthesizing authors’ keywords to give an overview of the state of knowledge. Consequently, thematic analysis was used to pinpoint the direction for future research. Thus, this review presents a clear picture of AI usefulness for environment, society, and businesses which in turn, add to stakeholders understanding of AI and ESG interactions.</p>

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Research Progress on Artificial Intelligence in Environmental Social and Governance (ESG)

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年5月16日

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  • Muhammad Sani Khamisu,
  • Neha Khandelwal,
  • Ratna Achuta Paluri

摘要

Organizations are increasingly integrating artificial intelligence (AI) into their sustainability strategies to track environmental footprint, strengthen corporate responsibility and enhance governance processes (so called ESG issues). The present review aims to synthesize research contribution on AI in ESG research stream, thus adding to the evolving discussion on AI-driven sustainability. The study focuses on three key research questions: performance structure of AI and ESG research stream, the current state of the research stream, and directions for future research. To address these research questions, the review employed performance and thematic analyses methods to analyse data from Scopus and Web of Science (WOS) published during the last fifteen years (2009–2024). The performance analysis reveals key insights regarding the most impactful articles, authors, sources, and contexts in the domain. Keyword analysis explores the present state of AI in ESG research stream, classifying and synthesizing authors’ keywords to give an overview of the state of knowledge. Consequently, thematic analysis was used to pinpoint the direction for future research. Thus, this review presents a clear picture of AI usefulness for environment, society, and businesses which in turn, add to stakeholders understanding of AI and ESG interactions.