Determinants of AI Adoption in Banking: Evidence from Tunisia
TL;DR
The results suggest that functional benefits, ease of interaction, social influence, and confidence in AI systems are more decisive drivers of adoption than cognitive familiarity in an emerging market context.
Abstract
This study investigates the factors influencing customers’ intentions to adopt Artificial Intelligence (AI) banking services in Tunisa. Building on an integrated framework combining the Technology Acceptance Model, Unified Theory of Acceptance and Use of Technology, Theory of Planned Behavior, Perceived Risk Theory, and Diffusion of Innovation Theory, the study investigates how perceived usefulness, perceived ease of use (, awareness, knowledge, attitude, subjective norms, trust, and perceived risk influence AI adoption intentions. Using survey data from 400 Tunisian retail banking customers and applying regression analysis, the findings show that perceived usefulness, perceived ease of use, subjective norms, and trust positively and significantly affect customers’ intention to adopt AI banking services, whereas perceived risk exerts a negative effect. In contrast, awareness, attitude, and knowledge do not appear to significantly influence adoption intentions. The results suggest that functional benefits, ease of interaction, social influence, and confidence in AI systems are more decisive drivers of adoption than cognitive familiarity in an emerging market context. In addition, analysis of variance (ANOVA) results indicate that age and educational level significantly moderate AI adoption behavior, highlighting the importance of demographic heterogeneity in shaping AI acceptance. This study offers valuable insights for banks and policymakers seeking to accelerate digital financial innovation