Adoption intentions the AI-powered apps in the personal finance sector

Abstract

This study aims to evaluate the factors affecting the adoption of AI applications in the financial sector of Generation Z with the combination of 3 theoretical models. This study measures the influence of the Technology Task Fit (TTF) on the Technology Acceptance Model (TAM) and the Information Success System (ISS). The quantitative methodology was used in this study and data collection was based on Google Forms while questionnaires were established by inheriting from previous related studies. According to the results, users perceive the ease of use and usefulness thanks to the relevance to their tasks that AI banking applications bring, thereby positively impacting their adoption. However, the application has not brought significant satisfaction to users. The study is expected to make a positive theoretical contribution to future research in banking technology. This study recommends that application developers integrate many features of AI technology to increase user satisfaction and adoption of AI banking applications. This study also suggests that future studies should evaluate and measure more hypothetical concepts to comprehensively assess user acceptance of AI applications in the finance sector for personal customers.