Driving Continuous Usage Intention of AI Banking Chatbots

AI-powered banking chatbots (AIBC) have revolutionized customer service operations, delivering personalized financial guidance at the click of a button. Research demonstrates that banks and customers highly benefit from chatbot adoption; yet it remains difficult for early users to stay engaged and continue using this service. This trend in customer long-term commitment to chatbots demonstrates the necessity of understanding the elements that shape the continuous usage intention (CUI) of AIBC. Drawing on the Technology Continuance Theory (TCT), the paper identifies and establishes the relationship between the key factors driving the CUI of AIBC. To examine the hypothesized relationship, analysis was performed on 319 survey responses, and Exploratory Factor Analysis (EFA), followed by Partial Least Squares Structural Equation Modeling (PLS-SEM) was conducted. The research shows how trust and anthropomorphism, along with traditional TCT constructs, i.e. expectation confirmation, perceived usefulness, and perceived ease of use, positively influence customer satisfaction and attitude toward AIBC use, leading to continuous usage intention. The study provides recommendations for banking institutions and chatbot developers to enhance customer satisfaction through usability optimization and trust-building strategies which spawn long-term commitment. The research expands the existing knowledge about AI financial services by identifying factors driving continuous usage intention and serves as a valuable guide for effective chatbot deployment in developing economies.