IDEAS home Printed from https://ideas.repec.org/a/eee/finana/v102y2025ics1057521925001231.html
   My bibliography  Save this article

Artificial intelligence and corporate ESG performance

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1057521925001231
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.irfa.2025.104036?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    Artificial intelligence; ESG performance; Green innovation; Organizational resilience; Corporate sustainability;
    All these keywords.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:finana:v:102:y:2025:i:c:s1057521925001231. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620166 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.