Assessing the determinants of artificial intelligence (AI) adoption in learning among accounting students at Universiti Utara Malaysia (UUM)

The integration of Artificial Intelligence (AI) into the accounting profession highlights the need for future graduates to possess relevant technological competencies. This study investigates the key determinants influencing AI adoption in learning among accounting students at Universiti Utara Malaysia (UUM). Based on the Technology Acceptance Model (TAM) by Davis (1989), the study examines four independent variables such as Artificial Intelligence Literacy (AIL), Technology Readiness (TR), Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) in relation to the Adoption of AI Technology in Learning (AAITL). A quantitative research design was employed using a structured questionnaire. The questionnaire was distributed to all Semester 6 Bachelor of Accounting students, but only 137 responses were received and analysed. The data were analysed using Statistical Package for the Social Sciences (SPSS) through descriptive and multiple regression analyses. However, the finding indicated only PU and PEOU had a significant influence on Al adoption in learning, while AIL and TR were not significant. These results reinforce the applicability of TAM in academic contexts, showing that students are more likely to adopt AI when it is perceived as useful and easy to use. These findings provide partial support for the TAM, suggesting that students are more likely to adopt AI when they perceive it as useful and easy to use. This study contributes to a better understanding of behavioural factors influencing AI adoption in learning among accounting students at UUM and offers a basis for further research in similar academic contexts.