Sep 2026· International Journal of Innovative Research in Engineering· 0 citations
TL;DR
Responsible AI governance should become a strategic component of modern HR management, enabling global organizations to balance technological innovation with employee rights, organizational accountability, and sustainable regulatory compliance.
Abstract
Artificial intelligence (AI) is increasingly transforming human resource management through applications in recruitment, employee evaluation, workforce analytics, talent management, and organizational decision-making. However, the growing use of AI in employment-related processes has also raised concerns regarding algorithmic bias, transparency, privacy, accountability, and regulatory compliance. This review aims to examine the future of HR governance by integrating AI ethics, risk management, and regulatory compliance within the context of global organizations. A structured literature review was conducted using relevant publications obtained from major academic databases, including Scopus, Web of Science, IEEE Xplore, ScienceDirect, and Google Scholar. The review focused on research addressing AI governance, responsible AI, HR risk management, algorithmic accountability, human oversight, and regulatory frameworks. The findings indicate that effective AI-driven HR governance requires an integrated approach combining ethical principles, lifecycle-based risk assessment, transparent decision-making, human oversight, data protection, and continuous compliance monitoring. The review also identifies fragmented governance practices and a lack of HR-specific frameworks as important research gaps. In conclusion, responsible AI governance should become a strategic component of modern HR management, enabling global organizations to balance technological innovation with employee rights, organizational accountability, and sustainable regulatory compliance.
The review indicates that effective AI-driven HR governance requires transparent algorithms, human oversight, ethical accountability, bias mitigation, data protection, continuous risk assessment, and alignment with evolving regulatory requirements.
Jaganathan Balaji· International Journal of Inn...· 0 citations
This case study examines the governance challenges associated with AI-enabled HR decision-making in an organizational context and highlights the importance of continuous AI auditing, meaningful human oversight, and clearly defined organizational responsibilities for responsible and sustainable AI governance frameworks...
Jaganathan Balaji· Indian Journal of Computer S...· 0 citations
A systematic literature review and comprehensive governance framework for responsible AI use in HRM is developed, indicating that AI adoption is prominent in recruitment, selection, and performance management, where algorithms shape evaluative decisions.
The findings demonstrate that the adoption of responsible AI cannot be achieved through technological means alone but also requires a commitment to comprehensive governance mechanisms, and the sequential interaction and interdependence of governance factors reduce operational and societal risks, increase transparency a...
Ghazwan Hani Hussein, Faiza Mohamed, A. Abuzreda· Journal of Technology and Sy...· 0 citations
Artificial Intelligence (AI) is increasingly becoming an important technology in Human Resource Management (HRM). AI-enabled systems can support recruitment, candidate screening, employee onboarding, learning and development, performance management, workforce planning, employee engagement, HR analytics and routine admi...
Sneka Aruchamy· International Journal of Res...· 0 citations
An AI-Enabled University Governance Framework is proposed that integrates AI capabilities, governance functions, ethical principles, moderating factors, governance outcomes, and institutional impacts and provides a conceptual foundation for understanding how universities can leverage AI while maintaining accountability...
Rinika Prakash· International Journal of Sci...· 0 citations
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