Artificial Intelligence in Human Resource Management: A Systematic Literature Review of Emerging Practices, Challenges, and Future Research Directions
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Abstract
Artificial Intelligence (AI) is transforming Human Resource Management (HRM) by enabling automation, predictive analytics, personalization, and data-driven decision-making across the employee lifecycle. However, the rapid expansion of AI-HRM research has produced fragmented evidence concerning emerging applications, employee and organizational outcomes, ethical challenges, and responsible governance. This study aims to systematically synthesize recent literature on AI in HRM, identify dominant applications and outcomes, examine implementation challenges, and develop a future research agenda. A Systematic Literature Review (SLR) was conducted using a structured search strategy based primarily on Scopus-indexed peer-reviewed journal articles published between 2021 and 2026. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 framework. Eligible studies were analyzed through descriptive mapping, thematic coding, comparative synthesis, and theoretical analysis. The findings indicate that AI applications are concentrated in recruitment and selection, performance management, talent management, workforce planning, HR analytics, learning and development, employee engagement, and retention. AI-HRM generates potential benefits through improved efficiency, decision support, personalization, productivity, and workforce optimization, but also creates challenges involving algorithmic bias, privacy, transparency, explainability, accountability, employee trust, job insecurity, and technostress. Generative AI and large language models represent an emerging frontier that further expands AI's role from automation toward human-AI collaboration. The study proposes an integrated AI-HRM framework emphasizing responsible AI governance and organizational readiness as critical conditions for sustainable value creation. The review contributes theoretically by integrating technological, organizational, human, and ethical perspectives and practically by providing guidance for responsible AI adoption in HRM.
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