Sustainable yet Ethical: Balancing Workforce Practices in AI-Integrated HRM Systems

Abstract

Purpose: This study examines how artificial intelligence can be strategically integrated into human resource management to support sustainable organizational practices aligned with environmental, social, and governance objectives. It focuses on the role of AI-enabled HRM in facilitating sustainable workforce planning, promoting fairness in talent acquisition, enabling energy-efficient work arrangements, and enhancing employee well-being, while addressing ethical concerns associated with AI adoption in HR functions.

Methods: The study adopts a conceptual and analytical research design grounded in an extensive review of academic literature and established theoretical frameworks related to AI, sustainable HRM, and ESG principles. Through a systematic synthesis of prior research and current organisational practices, the study develops an integrated perspective on AI-driven HRM and identifies key dimensions influencing its ethical and sustainable implementation.

Findings: The findings suggest that AI has strong potential to act as a catalyst for sustainable HRM practices. AI-driven workforce analytics improve planning efficiency and resource utilisation, while algorithm-based recruitment tools can reduce bias and support diversity and inclusion. However, the study also identifies critical challenges associated with AI adoption in HR functions.

Implications: The study highlights the need for ethically grounded AI adoption in HRM, emphasising fairness, accountability, transparency, and employee well-being. It offers practical insights for HR professionals, organisational leaders, and policymakers on aligning AI-enabled HR practices with ESG objectives to achieve long-term sustainability.

Originality: This study contributes by positioning AI as a strategic enabler of sustainable and ethical HRM. It proposes a novel conceptual framework based on green talent analytics, ethical AI governance, and sustainable workforce management, providing a holistic roadmap for responsible AI adoption.

  • Page Number : 130-142

  • Published Date : 2026-05-31

  • Keywords
    Artificial intelligence, Sustainable human resource management, Green HRM, Ethical AI governance

  • DOI Number
    10.15415/jtmge/2025.162010

  • Authors
    Shivani Pandey and Umme Ara

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