As organizations increasingly adopt generative artificial intelligence (GAI) to enhance productivity, growing worker distrust may hinder this progress. While there is emerging literature from a technology acceptance perspective, the factors driving distrust from a socio-psychological perspective and the impact of distrust on adoption intentions require deeper exploration. We developed and validated a comprehensive framework to examine GAI distrust within organizations by integrating social cognitive theory and nudge theory. The framework identified pro-social nudges, outcome expectations, security concerns and privacy self-efficacy as key antecedents of distrust and assessed how distrust affects adoption intentions.
A survey of 1,005 active workers was conducted in China. The data were analyzed using partial least squares structural equation modeling and the PROCESS macro for SPSS (Model 4).
While pro-social nudges and security concerns increased distrust, they did not directly affect adoption intentions. In contrast, positive outcome expectations and privacy self-efficacy reduced distrust and enhanced adoption intentions. The mediating and suppression effects of distrust were also discussed.
This study offers a novel framework for understanding the antecedents and impact of GAI distrust, providing practical insights for organizations and GAI developers to mitigate distrust within a broader social-psychological context.
