The rapid advancement of artificial intelligence (AI) has significantly transformed human resource management (HRM), enabling data-driven decision-making, automation, and predictive workforce analytics. Despite the growing volume of research, existing studies on AI-enabled HR practices remain fragmented across functions and contexts. This study conducts a systematic literature review of 86 peer-reviewed journal articles published between 2015 and 2025, following the PRISMA 2020 guidelines, to synthesize current knowledge on the application of AI in HR practices. Drawing on studies retrieved from Scopus and Emerald Insight databases, a thematic analysis identifies five dominant themes: AI in recruitment and selection, HR analytics and strategic decision-making, workforce planning and predictive HR, employee experience and well-being, and ethical, legal, and governance issues. The findings reveal a strong emphasis on recruitment and analytics-driven HR functions, alongside growing concerns regarding algorithmic bias, transparency, and employee trust. The review highlights critical research gaps, including the lack of longitudinal studies, limited employee-centric perspectives, and insufficient empirical examination of ethical AI governance. By integrating technological and behavioral insights, this study contributes to the HRM literature and offers actionable implications for managers seeking to adopt AI responsibly in HR practices