Authors - Aiswarya Rajan K K, K Nattar Kannan Abstract - This study presents a systematic literature review on the emergence, adoption, and challenges of AI-driven Human Resource Management (AI-HRM). Thematic synthesis and bibliometric insights were used to analyze eighteen Scopus-indexed studies published between 2019 and 2024 using the PRISMA framework. Using the Technology Acceptance Model (TAM/UTAUT), Socio-Technical Systems (STS) Theory, and Responsible AI principles, the review shows how AI improves HRM by automating repetitive tasks, facilitating data-driven decision-making, and allowing for individualized employee development. However, ethical risks like algorithmic bias, lack of transparency, privacy issues, and employee resistance continue to be major obstacles. The results imply that only when technological capabilities are in line with human judgment, organizational culture, and ethical governance can AI pro-vide long-term value in HRM.
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