Drivers of Behavioral Intention Toward AI Integration in Accounting Education: A UTAUT2 Perspective from Bangladeshi Universities

Abstract

The incorporation of Artificial Intelligence (AI) in accounting education is altering approaches to learning and professional skills development significantly at the higher level of study. Based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), this study examines the determinants that drive accounting students’ behavioral intention towards AI adoption in Bangladeshi universities. Data was obtained from 692 accounting undergraduate, and MBA students enrolled in public and private universities using a structured questionnaire that contains 28 observed variables. Factor analysis (FA) with varimax rotation was used to explore the factor structure. The KMO estimate was 0.950, and the Bartlett’s Test of Sphericity demonstrated the appropriateness of conducting a factor analysis. The results indicate eight major factors – Performance Expectancy, Facilitating Conditions, Behavioral Intention, Social Influence, Price Value, Habit, Effort Expectancy, and Hedonic Motivation, with a total variance of 84.96%. The most powerful predictor was Performance Expectancy, which could account for 52.00% of the variation, followed by Facilitating Conditions and Behavioral Intention. The findings suggest that students’ use intentions regarding AI in accounting education are primarily influenced by perceived performance benefits, infrastructural support, career relevance, and cost–benefit rationales. The findings of the study provide good implications for policy makers, university authorities, and curriculum developers to identify the strategic way forward to working on AI integration effectively with accounting education in developing countries like Bangladesh.