From Intention to Use: Examining Artificial Intelligence Adoption in Indonesian Accounting Education Using the UTAUT Model
TL;DR
The results of the study show that performance expectancy, effort expectancy, and social influence have a positive and significant effect on behavioral intention in using AI, which suggests that intent of use is a major factor driving the actual use of AI in accounting learning.
Abstract
This study aims to analyze the factors that affect the use of Artificial Intelligence (AI) in accounting learning using the Unified Theory of Acceptance and Use of Technology (UTAUT) model. The study used an explanatory quantitative approach with a survey method on 327 students of the Under Graduate of Accounting Program at Public Universities and Private Universities in Jakarta and Depok City. The data was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with the help of SmartPLS 4.0. The results of the study show that performance expectancy, effort expectancy, and social influence have a positive and significant effect on behavioral intention in using AI. In addition, facilitating conditions and behavioral intention have a positive and significant effect on use behavior. The greatest influence was found on the relationship of behavioral intention to use behavior, which suggests that intent of use is a major factor driving the actual use of AI in accounting learning. The research model also had good predictive ability with an R² value of 0.676 for behavioral intention and 0.758 for use behavior. These findings strengthen the relevance of the UTAUT model in explaining the adoption of AI in accounting education and provide implications for universities in optimizing the use of AI to improve the quality of learning.