PREDICTIVE ANALYTICS IN HR: USING AI TO FORECAST EMPLOYEE TURNOVER AND IMPROVE SUCCESSION PLANNING

Abstract

The integration of predictive analytics and Artificial Intelligence (AI) in Human Resource Management (HRM) is transforming traditional workforce strategies, particularly in areas of employee turnover and succession planning. Predictive analytics enables HR professionals to identify patterns and trends in employee behavior, facilitating proactive decision-making to retain top talent and ensure continuity in key roles. By leveraging AI algorithms, organizations can analyze vast amounts of data to predict turnover risks and highlight factors that contribute to employee dissatisfaction, allowing for timely interventions. In succession planning, AI aids in identifying high-potential employees and forecasting future leadership needs, enabling a more strategic approach to talent pipeline management. This study explores the application of predictive analytics in forecasting employee turnover and optimizing succession planning, highlighting the benefits, challenges, and ethical considerations involved. Through a review of case studies and recent advancements, this research provides insights into how AI-driven predictive analytics can enhance workforce stability, improve employee satisfaction, and drive organizational success in the evolving workplace.