Artificial Intelligence-Driven Human Resource Management and Employee Satisfaction: The Mediating Role of Employee Engagement

Abstract

Organisations increasingly use artificial intelligence (AI) in recruitment, performance management, employee learning and workplace support. This study examines the relationship between AI-driven human resource management (AI-HRM) and employee satisfaction, with particular attention to the mediating role of employee engagement. Data were collected using a structured questionnaire comprising eight items on AI-HRM, nine items on work engagement and six items on employee satisfaction. The study analysed responses from 112 respondents. The reliability analysis indicated acceptable internal consistency, with Cronbach’s alpha values of 0.71 for AI-HRM, 0.77 for employee engagement and 0.77 for employee satisfaction. Regression-based mediation analysis using 5,000 bootstrap samples showed a positive association between AI-HRM and employee engagement (b = 0.331, p = .004). Employee engagement was also positively associated with employee satisfaction (b = 0.342, p < .001). However, the total effect of AI-HRM on employee satisfaction was not statistically significant (b = 0.195, p = .093). The indirect effect through employee engagement was 0.113, with a 95% confidence interval of [0.032, 0.220], whereas the direct effect was not statistically significant (b = 0.082, p = .472). These findings suggest that employee engagement may help explain the relationship between AI-HRM and employee satisfaction. Further research using appropriate research designs and diverse employee samples is needed to assess the generalisability of these findings.