<![CDATA[This study examines the role of leadership in effective and efficient human resource management (HRM) decision-making. It analyzes leadership styles, including transformational, adaptive, ethical, and AI-driven leadership models; it explores how leadership strategies influence key HRM functions such as recruitment, talent retention, workforce planning, and performance management. Furthermore, the research addresses the integration of data-driven decision-making and AI technologies in optimizing HRM strategies while maintaining ethical and human-centered leadership principles. This study adopts a Systematic Literature Review (SLR) approach, synthesizing recent scholarly works from reputable sources to evaluate the effectiveness of leadership in HRM decision-making. A qualitative analysis of peer-reviewed journals, books, and empirical studies was conducted to identify patterns, challenges, and best practices in leadership-driven HRM. The study also examines the interplay between technological advancements and ethical governance in shaping leadership effectiveness within HRM frameworks. The findings reveal that leadership is crucial in shaping HRM policies, ensuring efficiency, strategic workforce planning, and organizational agility. AI-powered HR analytics and automation enhance efficiency but require ethical oversight to maintain fairness and transparency. The study also highlights challenges in leadership adaptation, including resistance to digital transformation, concerns over AI ethics, and the balance between efficiency and employee well-being. This research provides valuable insights for HR leaders, policymakers, and organizational managers, emphasizing the need for leadership development programs that integrate AI literacy, ethical governance, and strategic HR analytics. Future research should empirically validate leadership effectiveness and its contextual applications across different industries and workforce structures.]]>
