How to enhance employee engagement in the AI era: An fsQCA-based study.

BackgroundThe ongoing fourth industrial revolution, characterized by the integration of intelligent machines, presents a transformative shift in the nature of work. Unlike past industrial revolutions that reshaped job dynamics, the current reliance on intelligent machines introduces new complexities. It is challenging to determine whether the adoption of intelligent machines fosters active engagement or diminishes motivation of employees.ObjectiveThis paper explores how the adoption of intelligent machines affects employee work engagement. We aim to identify the key combinations of factors influencing work engagement amidst technological integration by utilizing a supportive ecosystem perspective.MethodsWe employed fuzzy-set qualitative comparative analysis (fsQCA) to examine the interplay of seven factors: challenge stressors, leadership empowerment behavior, technology dependence, relationship dependence, emotional dependence, benefit dependence, and growth need strength. This approach addresses the limitations of previous research by considering the interdependencies and non-linear relationships among these factors.ResultsOur study reveals diverse configurations that influence work engagement. The fsQCA analysis uncovers multiple pathways through which the identified factors interact to impact work engagement, providing a nuanced understanding of the conditions that foster employee engagement in the era of AI.ConclusionsTheoretically, this study contributes to the literature by elucidating multiple configurations that influence work engagement, highlighting the importance of a supportive ecosystem perspective in understanding employee behavior in technologically advanced workplaces. The findings also offer empirical insights to guide managerial interventions aimed at fostering employee engagement in the AI era.