The Dual-Path Mechanism of Artificial Intelligence Use on Employee Responsible Innovation: The Moderating Role of Perceived Corporate Digital Responsibility

• 1、Management School, Wuhan University of Science and Technology

Abstract：Focusing on the empowerment and burden that may arise after generative artificial intelligence enters workplace contexts, this study draws on conservation of resources theory and technostress theory to examine how artificial intelligence use affects employees\' responsible innovation. This study incorporates role breadth self-efficacy and technological complexity into a unified analytical framework and introduces perceived corporate digital responsibility as a contextual variable. Based on questionnaire data from 235 enterprise employees, the results show that artificial intelligence use is significantly and positively related to employees\' responsible innovation; role breadth self-efficacy serves as a positive transmission pathway in this relationship. Contrary to the original theoretical expectation, artificial intelligence use does not increase technological complexity but instead significantly reduces employees\' perceived complexity, thereby forming a "complexity alleviation" pathway that promotes responsible innovation. This finding suggests that, in the context of generative artificial intelligence, features such as natural language interaction, task assistance, and knowledge integration may weaken employees\' burden of technological adaptation. Further analysis shows that perceived corporate digital responsibility strengthens the positive effect of artificial intelligence use on role breadth self-efficacy, but presents a different boundary effect in the process through which artificial intelligence use influences technological complexity. Accordingly, this study supplements the mechanism through which generative artificial intelligence affects employees\' responsible innovation and provides empirical evidence for reinterpreting technological complexity in the context of artificial intelligence.

Keywords： Enterprise Management Artificial Intelligence Use Role Breadth Self-Efficacy Technological Complexity Perceived Corporate Digital Responsibility Employees\' Responsible Innovation