Algorithmic HR decisions as communication events: Fairness, trust, and employee–organization relations in AI-mediated workplaces

Abstract

This study examines how employees perceive the communication of algorithmic HR decisions in AI-mediated human systems and how these perceptions relate to fairness, trust, and employee–organization relational outcomes. Drawing on human systems management, organizational communication, organizational justice, and trust research, it tests a communication–fairness–trust pathway using survey data from 750 employees in Greece, Germany, and the Netherlands with workplace exposure to algorithmic HR systems. The findings show that communication quality is positively associated with perceived procedural and interactional fairness. Both fairness judgments are positively related to trust in the organization and management, while trust is the strongest predictor of relational outcomes. Indirect effects indicate that communication quality is linked to employee–organization outcomes through fairness and trust. Cross-national checks suggest that the pathway is broadly stable across the three countries, with limited differences in the fairness–trust links. The study contributes to human systems management by positioning algorithmic HR decisions as communication events. Through these events, employees interpret fairness, accountability, trust, and relational acceptability. Communication cannot correct a biased or substantively unfair system; perceived communication quality instead relates to employees’ evaluations of algorithmic decisions and their organizations.