AI-enabled HR analytics and work engagement: Work digital pressure and employee resilience as mediators and inclusive leadership as a moderator

Artificial intelligence (AI) is rapidly transforming human resource management, yet its implications for employee work engagement remain insufficiently understood. Drawing on the Job Demands–Resources (JD–R) model, this study examines the dual-path mechanisms through which AI-enabled HR analytics influences work engagement. Specifically, this study examines work digital pressure and employee resilience as mediators and inclusive leadership as a boundary condition. Using a two-wave, multi-source research design with matched data from 367 employees and 147 supervisors in Chinese enterprises, the results show that AI-enabled HR analytics has a positive indirect effect on work engagement through enhanced employee resilience and a negative indirect effect through increased work digital pressure. Further, inclusive leadership strengthens the positive relation between employee resilience and work engagement but does not mitigate the negative effect of work digital pressure. These findings indicate that AI-enabled HR analytics generates both motivational resources and digital demands, rather than exerting a purely beneficial or detrimental influence on work engagement. This study extends the JD–R model to AI-driven HR systems and provides a more balanced, process-oriented understanding of AI-enabled HR analytics, while offering actionable guidance for human-centered digital HR practices that sustain engagement and mitigate unintended strain.