Enhancing Employee Performance through AI-Enabled HR Analytics: Exploring the Roles of Job Crafting, Perceived Risk, and Employee Engagement

Abstract

This study investigates the significant impact of AI-enabled HR analytics on employee and sustainable performance, highlighting the mediating role of job crafting and the moderating effects of perceived risk and employee engagement in manufacturing organisations in Bandung, Indonesia. Drawing on cross-sectional data from 349 employees in manufacturing firms in Bandung, Indonesia, this study provides empirical evidence of the positive influence of AI-enabled HR analytics on long-term employee performance. The research utilises JD-R theory to validate the mediating role of job crafting in this relationship. Partial Least Square (PLS) analysis, conducted using SMART PLS 3.0 software, was applied to test the model. The results demonstrate that AI-enabled HR analytics significantly impacts job crafting. Additionally, job crafting mediates the relationship between AI-enabled HR analytics and both sustainable performance and employee performance. Perceived risk moderates the relationship between job crafting and both performance outcomes. Similarly, employee engagement moderates the relationship between job crafting and both sustainable and employee performance. This study is among the first to empirically examine the use of AI-enabled HR analytics in the context of job crafting and its effects on sustainable and employee performance. It provides valuable insights for managers and business leaders seeking to leverage AI to enhance employee sustainability and performance in diverse organizational settings.