Will Employee–AI Collaboration Enhance Employees’ Proactive Behavior? A Study Based on the Conservation of Resources Theory
Chenxi Sun, Xinan Zhao, Baorong Guo, Ningning Chen
Abstract
This study explores how employee-AI collaboration can promote employees' proactive behavior by reducing their workload, and examines the mediating role of workload and the moderating effect of AI literacy. Based on a survey of employees across multiple industries, the study finds that employee-AI collaboration significantly reduces employees' workload, which in turn encourages more proactive behavior. In this process, workload serves as a central mediating mechanism, as it helps alleviate task pressure and frees up cognitive resources, enabling employees to take on additional responsibilities and put forward innovative suggestions. Furthermore, with increasing levels of employee-AI collaboration, employees with higher AI literacy tend to experience greater workload relief, while those with lower literacy demonstrate a stronger and more consistent proactive behavioral response. These findings offer theoretical insight into employee-AI interaction and practical implications for enhancing initiative and innovation through effective AI integration.