ART OF MANAGING HUMAN RESOURCE THROUGH DESIGNATED ML BASED KNN ALGORITHM FOR EFFECTIVE EFFICIENCY ENHANCEMENT

The incorporation of Artificial Intelligence (AI) and Machine Learning (ML) technologies within Human Resources Management (HRM) practices has attracted considerable scholarly interest in recent years, owing to its capacity to fundamentally alter conventional HR processes. This review manuscript delivers an extensive examination of the contemporary landscape of AI and ML transformation in HRM, investigating its theoretical underpinnings, practical implementations, advantages, obstacles, and prospective trajectories. Utilizing a systematic literature review methodology, this study integrates existing scholarly works to delineate pivotal trends, challenges, and opportunities associated with the utilization of AI and ML across diverse HRM functions. In particular, it scrutinizes the applications of AI and ML in the domains of recruitment and selection, employee engagement and retention, performance management, as well as diversity and inclusion initiatives. Through the application of theoretical frameworks and empirical case studies, this manuscript clarifies the manner in which AI and ML technologies are reconfiguring HRM practices, empowering organizations to engage in data-informed decision-making, enhance operational efficiency, and cultivate a more inclusive and diverse organizational culture. Furthermore, this paper underscores the advantages of the adoption of AI and ML within HRM, including heightened precision in candidate screening, tailored learning and development programs, and instantaneous performance feed back mechanisms, while concurrently addressing the challenges linked to algorithmic bias, data privacy issues, and organizational preparedness.