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A Systematic Literature Review on Transforming HR Practices for ESG Integration: The Role of Artificial Intelligence in Shaping Sustainable Business Strategies

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  • Nor Amira Syairah Zulkarnaini

    (School of Human Resource Development and Psychology, Faculty of Social Sciences and Humanities, Universiti Teknologi Malaysia)

  • Nurul Syazana Samsuden

    (Business Diploma and Financial Programmes, Sunway College Johor Bahru)

  • Sook-Fun Fong

    (Henley Business School, University of Reading Malaysia)

  • Valarmathi Sambath

    (Faculty of Business, Raffles University, Malaysia)

Abstract

Artificial Intelligence (AI) is transforming Human Resource Management (HRM) by facilitating the integration of Environmental, Social, and Governance (ESG) principles into organizational strategies. This systematic literature review explores how AI-driven HR practices contribute to enhancing ESG performance and fostering sustainable business environments. Specifically, AI supports green HRM initiatives by streamlining processes, improving decision-making, identifying environmentally conscious talent, and minimizing resource inefficiencies. Moreover, AI enables the development of sustainability-oriented workplace cultures through technologies such as energy management systems and smart building solutions. By synthesizing recent scholarly advancements, this review highlights the strategic role of AI in embedding ESG values within HR functions. The findings underscore AI’s potential to shape resilient, future-ready organizations and provide a foundation for further research on AI-enabled ESG integration in HRM.

Suggested Citation

  • Nor Amira Syairah Zulkarnaini & Nurul Syazana Samsuden & Sook-Fun Fong & Valarmathi Sambath, 2025. "A Systematic Literature Review on Transforming HR Practices for ESG Integration: The Role of Artificial Intelligence in Shaping Sustainable Business Strategies," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 9(7), pages 5092-5104, July.
    • Handle: RePEc:bcp:journl:v:9:y:2025:issue-7:p:5092-5104
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