The Impact of AI-Enabled HRM Practices on Employee Work Engagement: The Moderating Role of Employee Digital Literacy

Abstract

Integrating artificial intelligence (AI) into human resource management (HRM) has revolutionized the way companies recruit, manage, and empower their staff. The current incorporation of AI into HRM has transformed the way organizations engage, manage, and recruit their employees. As AI becomes increasingly integral to HRM, there is a debate regarding its impact on employee work engagement. Based on the Job Demands-Resources (JD-R) model and Social Exchange Theory (SET), the current study creates and tests a moderated model explaining the relationship of AI-based HRM practices with employee work engagement in the presence of the moderating variable of employee digital literacy. Data were gathered using a quantitative cross-sectional design from 412 FTEs employed in organizations that used AI-enabled HR systems in the IT, banking, and telecom services sectors in Pakistan. Partial Least Squares Structural Equation Modelling (PLS-SEM) and hierarchical regression analysis were used to test the hypotheses. The results showed that AI-assisted HRM practices have a positive and significant impact on employees' work engagement (β = 0.412; p < 0.001). Additionally, employee digital literacy has a significant and positive moderation effect on the relationship between AI-enabled HRM and work engagement (interaction term β = 0.156, p < 0.01): the positive effect of AI-enabled HRM on work engagement is more pronounced for the more digitally literate employees. The model accounts for 38.7% of the variance in work engagement. By highlighting the role of AI in HRM as a job resource that positively influences employee engagement, when employees have the digital literacy to manage it, these findings support the JD-R model. Theoretical and practical implications, limitations, and suggestions for future research are presented.

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