TRANSFORMING HUMAN RESOURCES OPERATIONS THROUGH ARTIFICIAL INTELLIGENCE: FOUNDATIONS, OPPORTUNITIES, AND CHALLENGES
Objective: This study examines how artificial intelligence (AI) can be strategically leveraged to enhance human resources (HR) operational practices while addressing ethical, governance, and workforce implications. The manuscript advances conceptual clarity by integrating existing evidence into a human-centered framework that guides responsible AI adoption in HR.Study Design: This study employs an integrative literature review to synthesize multidisciplinary scholarship on AI applications in HR, drawing on research in human resource management, organizational behavior, information systems, and AI.Method: Peer-reviewed journal articles and relevant gray literature published within the past five to ten years were systematically reviewed. A qualitative thematic synthesis was conducted to identify patterns in AI-enabled HR functions, implementation enablers, risks, and outcomes. Findings were organized into operational, strategic, ethical, and governance domains to inform framework development.Results: The review indicates that AI has the potential to transform HR operations beyond automation by enhancing decision-making, workforce analytics, and employee engagement. However, the realized benefits depend on organizational readiness, data quality, adherence to ethical AI principles, and robust governance structures. Without intentional oversight, AI adoption may exacerbate bias, undermine trust, and misalign with organizational values.Conclusion: This study contributes an original, integrative framework that positions AI as an augmentative tool supporting HR’s strategic evolution rather than a substitute for human judgment. The findings underscore the importance of intentional, ethical, and context-sensitive AI adoption and highlight directions for future empirical research to evaluate long-term organizational and workforce outcomes.
Paper
The full text of this publication is not hosted on 44B due to licensing.
Read it at OpenAlex