When do consumers trust AI? The moderating roles of service orientation and social class in human-AI service robot collaboration

Abstract

As artificial intelligence (AI) becomes increasingly autonomous, understanding how human–robot collaboration affects consumer trust has emerged as a critical challenge in human–AI interaction research. Drawing on service orientation theory and social class theory, this research investigates how different forms of human–robot collaboration affects consumer trust in AI service robots. With three scenario-based studies, we examine the contingent roles of service orientation and social class, as well as the mediating role of human-robot interaction anxiety. The results reveal that robot-assisting collaboration generates greater consumer trust than robot-leading collaboration under a relational service orientation, whereas this difference disappears under a transactional service orientation. Furthermore, consumers from lower social classes exhibit higher trust in robot-assisting than in robot-leading collaboration, while no significant difference is found among consumers from higher social classes. By integrating service orientation and social class into the human–AI collaboration literature, this study advances our understanding of the psychological mechanisms through which human–AI collaboration affects consumer trust and offers actionable insights for the effective deployment of AI service robots in organizations.