The Mediating Role of Algorithmic Trust in the Relationship between AI Service Personalization and User Continuance Intention

Abstract

In digital service platforms, user experiences and sustained engagement can no longer be achieved without personalization, a strategy driven by the use of artificial intelligence. The online banking industry is the focus of the present study, and the study intends to examine online banking’s unique characteristics, particularly in terms of algorithmic trust (AT) as a mediating variable between AI service personalization (ASP) and user continuance intention (UCI). A purposive sampling approach has been used to collect data from Jordan digital banking users. Measures of ASP, AT and UCI were adapted from existing literature for the research protocol. The data used were analyzed using SPSS 24 software and the method of structural equation modeling (SEM). The results show that there was a positive relationship between ASP and AT and between ASP and UCI. Additionally, AT was found to be positively associated with UCI. The regression analysis also showed that, for all digital banking users, AT is significantly predicted by ASP, while for digital banking users, AT is also significantly predicted by UCI. It was also determined that AT was a significant mediator between ASP and UCI. The results indicate that users’ trust in AI-powered banking systems increases with the use of AI personalization mechanisms, leading to a greater willingness to engage with digital banking services. The findings underscore the need for user-friendly and trustworthy AI systems that foster long-term customer interactions and trust on intelligent digital platforms.