“Not All Bad News Feels the Same”: How AI vs. Human Negative Feedback Shapes Employee Reactions

Negative performance feedback is a core managerial practice, yet it often triggers adverse emotional and behavioral reactions. With the growing integration of artificial intelligence (AI) in organizational, performance feedback is increasingly delivered by AI systems alongside human managers. Drawing on Affective Events Theory (AET), this study investigates how employees respond differently to negative feedback from AI versus human sources. Experimental results show that AI-delivered feedback elicits more learning behaviors and less psychological withdrawal than human-delivered feedback, primarily because it generates higher level of calm while human feedback induces higher level of anxiety. These effects, however, are attenuated when AI systems are designed with low anthropomorphism or when human managers display high trait empathy. By extending AET to the context of human-AI interactions in performance management, this research enriches the feedback literature and broadens the theoretical and practical application of AET.