Unveiling the Dual Effects of AI Interaction on Newcomers’ Psychological Safety and Work Results
Liping Chen · Academy of Management Proceedings · 2025
With the widespread application of artificial intelligence (AI) in the workplace, how newcomers adapt to this change has become an important issue. Achieving psychological safety is crucial for newcomers to adapt to their roles and perform well, while AI introduction may complicate this process. Grounded in Uncertainty Management Theory (UMT), this study examines how interaction with AI impacts newcomers’ psychological safety and subsequent work results——in-role (task performance) and extra-role (proactivity)——through an experiment and a multi-time-lagged field survey. The results show that, on the one hand, AI interaction can enhance task-related knowledge acquisition (reducing uncertainty), thereby boosting psychological safety and improving task performance and proactivity. On the other hand, frequent AI interaction may reduce social interactions with colleagues, leading to social isolation, which negatively affects psychological safety and, in turn, work results. Notably, female newcomers experience a stronger sense of isolation due to AI interaction, resulting in lower psychological safety and weaker work results. This study contributes to the literature on human-AI interaction, psychological safety, and gender diversity in the workplace. It also provides practical guidance for organizations in managing the adaptation process of newcomers in the AI era.