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Artificial intelligence and corporate ESG performance

Author

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  • Li, Junjun
  • Wu, Tong
  • Hu, Boqiang
  • Pan, Dongliang
  • Zhou, Yaqiong

Abstract

This study examined how artificial intelligence (AI) capabilities strengthen corporate environmental, social, and governance (ESG) performance while focusing on the mediating role of green resilience and the moderating effect of organizational resilience. AI has transformative potential for ESG performance; however, its role in emerging markets remains underexplored. While AI can optimize resource use, improve workplace safety, and enhance governance through transparency, challenges such as data limitations, infrastructure gaps, and ethical issues may hinder its impact. Bridging this gap requires focused research on how AI capabilities drive sustainable outcomes in these markets, identifying practical tools, and fostering supportive policies. We employed robust statistical techniques to establish reliable findings from a comprehensive dataset of Chinese-listed companies from 2011 to 2022. The findings indicate that AI capabilities significantly strengthen ESG performance. The relationship was facilitated through green innovation initiatives. Organizational resilience enhances AI's positive impact on ESG performance, especially in technology-intensive industries. However, the influence varies significantly by context, with stronger effects observed in nonhigh-polluting sectors and state-owned enterprises, highlighting the need for tailored approaches to maximize sustainable outcomes. Our findings augment the theoretical understanding of technology-driven sustainability by elucidating how AI capabilities strengthen ESG performance through innovation pathways. We identified key organizational factors, such as resilience and innovation capacity, as well as contextual factors, including industry type, regulatory frameworks, and ownership structures, that influence the relationship between AI and ESG performance. These findings provide valuable insights for organizations in emerging markets aiming to leverage AI for enhanced sustainability.

Suggested Citation

  • Li, Junjun & Wu, Tong & Hu, Boqiang & Pan, Dongliang & Zhou, Yaqiong, 2025. "Artificial intelligence and corporate ESG performance," International Review of Financial Analysis, Elsevier, vol. 102(C).
    • Handle: RePEc:eee:finana:v:102:y:2025:i:c:s1057521925001231
    DOI: 10.1016/j.irfa.2025.104036
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    JEL classification:

    • G34 - Financial Economics - - Corporate Finance and Governance - - - Mergers; Acquisitions; Restructuring; Corporate Governance
    • M14 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - Corporate Culture; Diversity; Social Responsibility
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth

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