Analyzing the Dissemination of Artificial Intelligence in Digital Banking: A Mixed-Methods Study of FinTech Adoption Behavior

This study purposefully addresses the FinTech and digital banking literature by examining the diffusion of artificial intelligence (AI) across technological, organisational, and consumer dimensions through a mixed-methods approach, with a particular focus on semi-urban and developing market contexts. The qualitative phase comprised semi-structured interviews with representatives from two nationalised and four private Indian banks, chosen for their strong reputations, extensive user bases, and early FinTech adoption in semi-urban areas, and subsequently tested through a cross-sectional quantitative survey of semi-urban consumers using a structured questionnaire. Quantitatively, 547 valid stratified-random responses were analysed using validated five-point Likert measures. The measurement model has a high level of reliability and validity, and a high level of internal consistency, convergent and discriminant validity, and lack of multicollinearity, which proves the applicability of the measurement model to structural analysis. The structural findings demonstrate that the digital literacy is the strongest contributor to trust, the satisfaction leads to loyalty, the organisational agility has a positive impact on satisfaction and trust, and the perceived usefulness has a relatively small impact. The findings of mediation and moderation indicate that trust and satisfaction are able to transfer the important effects on loyalty together but a greater perceived risk has the capability of eroding the trust-loyalty relationship. By offering practical insights, this research provides valuable guidance for policymakers and financial institutions seeking to balance innovation with consumer protection in the evolving AI-enabled digital banking ecosystem.