The Impact of AI Negative Feedback vs. Leader Negative Feedback on Employee Withdrawal Behavior: A Dual-Path Study of Emotion and Cognition

Abstract

In the workplace, the application of artificial intelligence (AI) is becoming increasingly widespread, including in employee performance management where AI feedback is gaining importance. Some companies are also using AI to provide negative feedback to employees. Our research compares the impact of AI negative feedback and leader negative feedback on employees. In order to explore the impact of AI negative feedback on employees, we investigated how AI negative feedback impacts employee psychology and behavior and compared these effects to those of human leader negative feedback, within the framework of the feedback process model. To explore these differences, we conducted three experimental studies (n = 772) from two different regions (i.e., China and the United States). The results reveal that leader negative feedback induces greater feelings of shame in employees, leading to work withdrawal behaviors, compared to AI negative feedback. Conversely, AI negative feedback has a more detrimental effect on employees’ self-efficacy, leading to work withdrawal behaviors, compared to leader negative feedback. Furthermore, employees’ AI knowledge moderates the relationship between negative feedback sources and employee withdrawal behavior. Specifically, employees who perceive themselves as having limited AI knowledge are more likely to feel ashamed when receiving leader negative feedback than when receiving AI negative feedback. Conversely, employees who believe they are knowledgeable about AI are more likely to have their self-efficacy undermined by AI negative feedback than leader negative feedback. Our research contributes significantly to the literature on AI versus human feedback and the role of feedback sources, providing practical insights for organizations on optimizing AI usage in delivering negative feedback.