The objective of this research is to identify and evaluate the determinants of AI technology acceptance and usage intention in higher education courses focused on data analytics in accounting and auditing. The research sample comprises 281 students from the Faculty of Economics & Business at the University of Zagreb in Croatia. To conduct the analysis, we employed the original Technology Acceptance Model and the Partial Least Square-Structural Equation Modelling analytical approach. A central finding of this study is the dominant role of Perceived Ease of Use. Perceived Ease of Use has a fundamental position in shaping students’ perceptions. Although modifications of Technology Acceptance Model-based models do not include attitude towards use, in our research, this factor serves as an important channel from perceived usefulness and perceived ease of use to behavioral intention to use AI. Furthermore, in our study, behavioral intention to use has the strongest predictive power for actual use of AI. An important contribution of this article concerns the specifics of applying AI in teaching, namely data analytics, which is increasingly significant across various professions, especially in accounting and auditing. Data analytics is an area strongly affected by the development of AI, leading to many new and improved tools and methodologies that leverage generative AI. For university programs to adequately respond to market needs, it is important to understand how students perceive the application of artificial intelligence in learning data analytics, and to what extent they are ready to adopt new technologies that will shape their future professional development.
Ana Ježovita (Thu,) studied this question.
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