Determinants of chatbot usage intention in the banking sector in Morocco: contribution of an enriched UTAUT model

Abstract

The widespread adoption of artificial intelligence–based chatbots is progressively reshaping the modalities of customer interaction in the banking sector, while simultaneously raising critical challenges related to trust and the acceptance of automated technologies. This study examines the key determinants of banking chatbot usage intention in the Moroccan context, drawing on an enriched UTAUT model that incorporates functional, security-related, relational, and emotional dimensions.

The empirical analysis is based on a quantitative survey conducted among 384 users of digital banking services in Morocco. The collected data were analyzed using partial least squares structural equation modeling (PLS-SEM).

The findings highlight the central role of trust in the adoption process of banking chatbots. Trust is primarily built upon perceptions of integrity, security, confidentiality, and institutional reputation, whereas perceived risk acts as a major barrier. Functional attributes of chatbots, such as competence and reliability, contribute to establishing a baseline level of credibility but do not constitute strongly differentiating factors. Perceived usefulness emerges as the main driver of usage intention and plays a decisive mediating role between trust and actual adoption. Furthermore, technological discomfort reduces users’ willingness to adopt chatbots by undermining perceived usefulness, while anthropomorphism does not exert a significant influence in the banking context examined.

The adoption of banking chatbots relies on a multidimensional architecture combining technical, security-related, relational, cognitive, and emotional factors. These findings encourage banks to strengthen transparency, conversational consistency, and digital support in order to foster sustainable customer adoption.

JEL Classification : M41

Paper Type : Empirical Research