Application Of Ai and Hr Analytics in Employee Life Cycle Management

Abstract

Artificial Intelligence and HR analytics are becoming important tools in modern Human Resource Management. Organizations are increasingly using digital technologies to manage employees and improve different HR activities. This review paper examines the application of Artificial Intelligence and HR analytics in Employee Life Cycle Management. The employee life cycle covers different stages such as workforce planning, talent attraction, recruitment, selection, onboarding, training and development, performance management, employee engagement, career development and employee retention. The paper reviews how AI and HR analytics can support these activities and help HR professionals make more informed decisions. The review shows that AI can reduce routine HR work, improve recruitment and candidate screening, support personalized employee training, provide continuous performance information and assist in identifying employee engagement and retention issues. HR analytics can help organizations understand employee data, identify skill gaps, study workforce trends and predict possible employee turnover. The combination of AI and HR analytics can therefore make employee life cycle management more systematic, faster and data-based. At the same time, the application of these technologies creates challenges related to data privacy, data quality, algorithmic bias, transparency, implementation cost and lack of technical skills. The paper also highlights the importance of human judgment in HR decision making. AI should support HR professionals rather than completely replace human involvement. The review concludes that responsible use of AI and HR analytics, together with proper human supervision, can improve employee experience and support effective Human Resource Management.