Impact of data breaches on user intentions toward GenAI bots
Anu Rao · Journal of Computer Information Systems · 2026
Nowadays integration of Generative artificial intelligence (GenAI) bots in public transportation systems offers convenience and efficiency to commuters. However, data breaches pose privacy-security risks that impact commuters’ trust and intention to continue using. Studies have examined the factors that lead to data breach risks in AI bots, but the impact on the anthropomorphic GenAI bots is still unexplored. Drawing on the theory of planned behavior, we examine how data breaches on anthropomorphic GenAI can impact the commuter’s intention toward their usage. Mixed-methods approach combining partial square structural equation modeling (PLS-SEM) with Artificial neural network (ANN) and interviews in a data breach environment is employed. The findings revealed that data breaches significantly influence commuters’ usage intention, moderated by trust. This study has theoretical and practical implications, highlighting the need to prioritize robust security measures and trust-building strategies to ensure commuter retention and satisfaction under data breaches.