Legal practices of AI-driven HRM practices and organizational Performance: The mediating role of employee adaptability in digital-era organizations

Abstract

This study focuses on human resource management issues in the digital age from a legal perspective, based on dual-core theory, and empirically examines the impact of AI-enabled HR practices on organizational performance. The core dimensions of AI-enabled HR in this study include AI-powered recruitment, training, and performance appraisal, with employee adaptability introduced as a mediating variable. The study employed a quantitative research design, collecting 247 validated questionnaires from employees in digital organizations using partial least squares structural equation modeling (PLS-SEM) for empirical testing. The reliability and validity of the measurement model exceeded 0.7, the average extracted variance value was greater than 0.5, and the model passed the discriminant validity test according to the Fornell-Larcker criterion. The path test results demonstrate that all types of AI-enabled HR practices that comply with laws and regulations, along with employee adaptability, have a significant positive impact on organizational performance. Furthermore, employee adaptability is a positive mediating factor in the relationship between AI-enabled recruitment and organizational performance. This study complements the empirical evidence in this field regarding the interactive impact of AI-assisted human resources systems and the adaptability of employees.