Inspired or entitled? The contingent effects of coworker AI-augmented performance through the lens of social comparison

Introduction Research on the interpersonal consequences of workplace AI has mainly examined how observers evaluate the act of AI use. As AI use becomes ordinary, however, use itself loses diagnostic value, and the observable performance produced by AI-assisted work becomes more consequential. Drawing on social comparison theory, we propose that coworker AI-augmented performance is a comparison-relevant cue that yields contingent interpersonal consequences for observers, depending on task interdependence. Methods We tested this dual-pathway model in an online between-subjects experiment with full-time employees ( N = 240) and a three-wave field study of employee–supervisor dyads ( N = 360). Results When task interdependence was high, coworker AI-augmented performance was positively associated with interpersonal knowledge seeking, which in turn increased employee work performance. When task interdependence was low, coworker AI-augmented performance was positively associated with psychological entitlement, which in turn decreased employee work performance. Findings were consistent across the experiment and the field study. Discussion Coworker AI-augmented performance can inspire knowledge seeking or invite entitlement, depending on task interdependence. These results highlight both the benefits and perils of AI-augmented performance cues and the need to examine relational work structure in coworker reactions to AI.