How leaders build employee trust in artificial intelligence: voice opportunities, humility, and trust transfer

Artificial intelligence is increasingly central to organizational work, yet employee trust in AI remains fragile. Although prior research has primarily explained trust in AI through technological characteristics such as transparency, reliability, and accuracy, we argue that trust in AI is also shaped by the social context in which employees encounter these systems. Drawing on affect-as-information theory and social information processing theory, we develop and test a model in which leader-provided voice opportunities reduce employees’ negative affect about AI-related work experiences, thereby enhancing perceptions of leader trustworthiness and, in turn, trust in AI. We further propose that this indirect effect depends on leader humility, because humility signals that employee concerns will be received in a respectful, open, and non-defensive manner. Results from a multi-wave field survey and an experiment support this model.