AI Usage in Interpersonal Helping Comes at a Cost: Understanding Its Negative Effect on Gratitude and Reciprocation in the Workplace
Manna Zhang, Zheng Fan, Juan Du, Jiatong Wang · International Journal of Human-Computer Interaction · 2026
As the use of artificial intelligence (AI) in interpersonal helping among coworkers grows, its impact on recipients remains underexplored. This research examines how varying levels of AI usage in interpersonal helping (AUIH) impact recipients' reciprocation, alongside the underlying mechanisms and boundary conditions. Through a scenario-based experiment (Study 1, N = 300) and a critical incident technique (Study 2, N = 345), both studies demonstrate that higher levels of AUIH are associated with lower perceptions of the helper’s effort and benevolent intention. This, in turn, is related to diminished feelings of gratitude and reduced reciprocation. Additionally, the research identifies two key moderators: the recipient’s AI skill amplifies the negative relationship between AUIH and perceived effort, while the recipient’s AI trust mitigates the adverse effect of AUIH on perceived benevolent intention. These findings clarify the cognitive and affective effects of AUIH and offer practical insights for managing AI use among coworkers.