Evaluating AI-Enhanced Digital Payment Platform Adoption through an Extended UTAUT2 Model

Abstract

AI enabled digital payment is one of the more advanced forms of technology, with the unified theory of acceptance and use of technology (UTAUT) model adopted to perform cashless transactions instantly. The study focuses on how digitized banking might increase behavioral intention in adopting digital payment systems through an altered UTAUT2 model with factors such as performance expectancy, effort expectancy, social influence, facilitating conditions, trust & security, and regulatory support. Hence, a conceptual model and its structure equation modeling are proposed, which validates the model to demonstrate the adoption of the AI based digital payment platform and its effect on the behavioral intention of end users. A Purposive sampling method has been used for the study as the target respondents are the banking users. A sample size of 313 online banking customers of public and private sector banks is targeted in India. The study’s findings show that Cronbach’s alpha scores range from 0.72 to 0.78, while the scores of composite reliability range from 0.73 to 0.77, indicating favourable construct reliability and significant internal consistency for scale advancement, while SRMR and NFI are 0.058 and 0.89, indicating the achievement of a Good Model Fit. This suggests a promising potential for market share growth in the digital banking sector. Thus, the AI based digital payment system adopted by banking customers provides personalized and customized high- quality satisfaction and loyalty with effective and efficient services. Policymakers and stakeholders can capitalize on the measured model proposed by the current study to explore strategies to boost user engagement.