AI-Based Performance Appraisal Systems and HR Analytics Adoption: Evidence from Kuwait’s Government Sector

Abstract

This study investigates the role of AI-based performance appraisal systems in enabling employee performance systems and realizing the benefits of Human Resource Analytics (HRA) within Kuwait’s government sector, with private organizations serving as a comparative benchmark. Using survey data from 332 employees and managers across public and private institutions, covariance-based structural equation modeling (CB-SEM) was employed to test the measurement and structural models. The results show that AI-enabled appraisal systems significantly enhance employee performance systems (β = 0.608, p < .001) and strongly predict the perceived benefits of HR analytics (β = 0.930, p < .001). These findings demonstrate that AI-based appraisal systems provide the critical data infrastructure required for analytics-driven HRM, improving objectivity, transparency, and strategic workforce planning. The study contributes to HR analytics scholarship by offering empirical evidence from a Gulf Cooperation Council (GCC) public-sector context, highlighting the enabling role of AI technologies in advancing digital HR transformation. Practically, the results provide actionable insights for policymakers and organizational leaders seeking to modernize performance management and strengthen human capital development in alignment with Kuwait Vision 2035.