Employees' Justice Perceptions and Trust in AI Systems for Performance Evaluation: Uncovering the Role of Gender and Culture

Organizations are increasingly using artificial intelligence (AI) to support employee performance evaluation, yet employees' perceptions of and responses to these systems within this high-stakes workplace context remain insufficiently understood. Drawing on social exchange, organizational justice, and trust theories, this study examines how employees' justice perceptions shape trust in AI-based performance evaluation systems and how trust in AI relates to broader employee–organization relationship factors, including trust in the organization, trust in managers, and affective commitment. It further investigates whether these relationships vary across gender and Eastern–Western regional contexts. Survey data from 291 employees across Eastern and Western countries were analyzed using partial least squares structural equation modeling and multigroup analysis. The findings show that distributive and procedural justice perceptions positively influence employee trust in AI across regional contexts, with distributive justice exerting the stronger effect. Trust in AI, in turn, positively influences affective commitment in both contexts. Gender differences were observed in the relationship between procedural justice perception and trust in AI within the Eastern sample but not within the Western sample. These findings contribute to research on organizational justice, trust, and AI in organizations, while also offering practical insights for fostering employee trust and supporting effective AI implementation in performance evaluation.