Abstract:
This research investigates the effects of the human resource (HR) practices within the organization on the efficiency of the HR process, with emphasis on the mediating role of the artificial intelligence (AI) applications in human resource management (HRM). In the context of rapid digital transformation, HR functions are increasingly experiencing a transformation from traditional administration functions to technology-driven systems that are strategically driven. Drawing on data collected from employees who are working in IT and technology driven organisations in Pakistan, the study examines the impact of core HR practices, namely recruitment and selection, performance appraisal and training and development, on the adoption of AI applications and in turn improve the efficiency of the HR process. A quantitative and explanatory research design was used, and data were analysed by Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings show that well-structured HR practices are a significant predictor of adoption of AI applications in HRM, and the adoption of AI has a strong positive effect on the efficiency of the HR processes in terms of speed, accuracy, and reduction in manual workload. Moreover, the results do confirm AI applications significantly mediate the relationship between HR practices and HR process efficiency, indicating that the efficiency gains from HR practices is substantially amplified by support from AI-enabled systems. This study adds to the growing number of studies in the literature on digital HRM by empirically integrating traditional HR practices with emerging AI technologies and offers valuable findings for managers who are interested in improving the HR efficiency by strategic alignment of HR systems and intelligent technologies.
