Sun Chenxi, Zhao Xinan, Guo Baorong, Chen Ningning
School of Business Administration, Northeastern University, Shenyang 110167, China.
Business School, Guilin University of Technology, Guilin 541006, China.
Behav Sci (Basel). 2025 May 9;15(5):648. doi: 10.3390/bs15050648.
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.
本研究探讨员工与人工智能的协作如何通过减轻员工工作量来促进其积极行为，并考察工作量的中介作用以及人工智能素养的调节作用。基于对多个行业员工的调查，研究发现员工与人工智能的协作显著减轻了员工的工作量，进而鼓励了更多的积极行为。在此过程中，工作量作为核心中介机制，有助于减轻任务压力并释放认知资源，使员工能够承担更多责任并提出创新建议。此外，随着员工与人工智能协作程度的提高，人工智能素养较高的员工往往工作量减轻得更多，而素养较低的员工则表现出更强且更一致的积极行为反应。这些发现为员工与人工智能的互动提供了理论见解，并对通过有效整合人工智能来增强主动性和创新能力具有实际意义。
