Linking AI-Driven HRM Practices to Organizational Performance: Empirical Evidence from Delhi NCR’s IT Industry

Abstract

This study reveals the impact of AI-powered Human Resource Management (HRM) practices on organizational performance in Delhi NCR's information technology sector. With Artificial Intelligence revolutionizing fundamental HR activities recruitment, training, analytics, and performance management—its implementation is increasingly revolutionizing workforce strategy. The study, employing a quantitative approach and data collected from 430 Delhi, Haryana, and Uttar Pradesh respondents, applies Partial Least Squares Structural Equation Modeling (PLS-SEM) to investigate structural relationships between AI-enabled HRM constructs and performance indicators. Constructs such as Talent Management and Recruitment (TMR), AI-enabled HR Operations (HODS), Workforce Analytics and Planning (PWAP), and Talent Development and Performance Management (TDPM) were anticipated to possess high reliability, validity, and discriminant characteristics. Findings confirm the positive effect of AI-HRM on organizational performance and provide practical implications for IT firms to strategically implement AI in HR practices. This study bridges an essential empirical research gap and contributes to AI-HRM studies in the Indian context.