EXPLORING THE IMPACT OF AI-DRIVEN TALENT MANAGEMENT MODELS ON EMPLOYEE RETENTION IN INDIAN IT COMPANIES

Abstract

Job dissatisfaction, lack of career growth and talent pool are also a problem in employee retention in the Indian IT industry. Traditional talent management practices fail to address the dynamic employee needs, which disengages employees, resulting in an increase in turnover cases. The paper focuses on the influence of AI-based talent management models on employee retention in Indian IT companies. The study will evaluate the use of AI in recruitment, performance management, and career development in enhancing employee engagement, work satisfaction, and retention. The mix-methods method was applied consisting of a quantitative survey and qualitative interviews of 350 employees and HR professionals of different Indian IT firms. The Likert scale questions in the survey were on the use of AI in HR activities: recruitment, engagement and retention. Regression analysis, correlation tests, ANOVA, and T-Tests were applied as the data analysis tools to examine how AI tools correlate with employee retention. The outcome shows that there is a statistically significant positive correlation between AI-based talent management models and employee retention. The use of AI, specifically in performance management and predictive analytics, reduced turnover by 70% of those surveyed said AI-performance management made their work more fun, and 60% were convinced that predictive analytics enabled the HR team to preemptively deal with turnover. Moreover, 72 percent of the respondents believed that AI-enhanced recruitment enhanced job-role fit, which led to less dissatisfaction and turnover. As the research shows, AI-based talent management models can help the Indian IT companies to significantly increase their retention score as the HR functions are personalized, and the needs of every employee are addressed, yet the recommendations to incorporate AI and to conduct an ongoing assessment of these systems should be increased.