How does AI-enabled HR analytics influence employee resilience: job crafting as a mediator and HRM system strength as a moderator

Purpose: Based on the JD-R model and process-focused HRM perspective, this research paper aims to investigate the processes underlying the relationship between AI-enabled HR analytics and employee well-being outcomes (resilience) that received less attention in the AI-driven HRM literature. Specifically, this study aims to examine the indirect effect between AI-enabled HR analytics and employee resilience via job crafting, moderated by HRM system strength to highlight the contextual stimulus of AI-enabled HR analytics. Design/methodology/approach: The authors adopted a time-lagged research design (one-month interval) to test the proposed hypotheses. The authors used two-wave surveys to collect data from 175 full-time hotel employees in China. Findings: The findings indicated that employees' perceptions of AI-enabled HR analytics enhance their resilience. This study also found the mediation role of job crafting in the mentioned relationship. Moreover, the positive effects of AI-enabled HR analytics on employee resilience amplify in the presence of a strong HRM system. Practical implications: Organizations that aim to utilize AI-enabled HR analytics to achieve organizational missions should also dedicate attention to its associated employee well-being outcomes. Originality/value: This study enriched the literature with regard to AI-driven HRM in that it identifies the mediating role of job crafting and the moderating role of HRM system strength in the relationship between AI-enabled HR analytics and employee resilience.