AI-Enabled Human Resource Management: Adoption, Impact, and Challenges

The integration of Artificial Intelligence (AI) into Human Resource Management (HRM) has emerged as a transformative force, reshaping traditional HR functions into data-driven and strategic processes. This study aims to examine the adoption, impact, and challenges of AI in HRM through a comprehensive analysis of secondary data derived from peer-reviewed journals and reports published by globally recognized organizations such as McKinsey & Company, Deloitte, and the World Economic Forum. The research employs a mixed analytical approach, incorporating trend analysis, comparative evaluation, and thematic synthesis to interpret data collected from the period 2015–2025. The findings indicate a significant increase in AI adoption across HR functions, particularly in recruitment, workforce planning, and employee engagement. AI-driven systems enhance operational efficiency, improve decision-making accuracy, and enable predictive workforce analytics, thereby contributing to organizational competitiveness. However, the study also identifies critical challenges, including algorithmic bias, data privacy concerns, employee resistance, and high implementation costs. These issues highlight the need for ethical governance frameworks and strategic alignment in AI adoption. The paper contributes to existing literature by providing a holistic secondary data-based perspective and offers practical implications for organizations seeking to integrate AI into HR practices. The study concludes that while AI serves as a powerful enabler of HR transformation, its successful implementation depends on balancing technological capabilities with ethical considerations and human-centric approaches.