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Through a combination of situational experiments and multi-wave data collection, we explored the mechanism of AI-induced knowledge redundancy on knowledge sharing. This study combined the mediating roles of responsibility dispersion and knowledge self-efficacy to reveal the psychological paths of individual knowledge-sharing behaviors under the AI intervention situation, and further introduced the moderating roles of AI trust and coworker relationships. The results of the study provide empirical basis for understanding how AI reshapes individual responsibility attribution, thus revealing the intrinsic mechanism of AI reshaping the motivation of knowledge sharing, and providing theoretical basis and practical inspiration for constructing a more motivational human-machine collaborative knowledge management system.This study has received ethical approval by Yangzhou University (YXYLL-2025-85).