AI and feedback in organizations

Feedback directs employee behavior. It corrects poor performance, reinforces achievement, aligns organizational goals with employees’ output, and fosters motivation. Although essential for improvement, negative (versus positive) feedback often carries emotional costs, leading to decreased motivation and morale. Research shows that people are generally averse to providing and receiving negative feedback, which makes it difficult for organizations to deliver constructive criticisms effectively. To address these challenges, this project examines Artificial Intelligence (AI) as an innovative tool in delivering employee feedback. We investigate whether AI can provide feedback that is readily accepted by employees, such that it amplifies the performance benefits and relieves the emotional burden of negative feedback. Using an AI-driven game-based assessment platform, we examine how feedback valence (positive, neutral, negative) and feedback targets (self vs. others) influence employees’ perceptions of fairness, motivation to improve their performance, and willingness to accept feedback. Our goal is to enhance understanding of the link between AI use and human feedback processes, allowing us to generate practical applications for managers and employees to implement AI systems. Specifically, we develop insights into how AI can foster effective human-AI collaboration that drives sustainable high performance, aiming to boost employee productivity, skills, and overall job well-being. We also develop a framework to help leaders use AI systems for providing routine feedback. Thus, we enhance understanding of how AI adoption can reshape performance management in modern organizations.