Understanding artificial intelligence adoption among university students in South African higher education: a technology acceptance model approach

Artificial intelligence (AI) technologies are increasingly transforming higher education by supporting teaching, learning, and academic productivity. Despite the use of AI tools among students, limited evidence exists on factors associated with AI adoption within South African higher education institutions. This study investigated factors associated with AI adoption among university students at a selected South African university using an extended Technology Acceptance Model (TAM) framework. Specifically, the study examined the associations among perceived usefulness, perceived ease of use, subjective norms, attitudes towards AI, and actual AI use, as well as differences in AI adoption across demographic and academic characteristics. A quantitative cross-sectional study was conducted among students at a selected South African university. Data were collected using a structured self-administered questionnaire adapted from the TAM and existing AI adoption literature. Participants were recruited through convenience sampling approach, and 216 students participated in the study. Descriptive and inferential statistical analyses were performed, with statistical significance assessed at the 5% level. Students generally perceived AI technology as beneficial for improving academic performance, saving time, facilitating learning, and supporting academic tasks. All four hypothesised relationships were statistically significant: perceived ease of use was positively associated with perceived usefulness ( r s  = 0.728, p   r s  = 0.647, p   r s  = 0.548, p   r s  = 0.589, p  p  = 0.009] and faculties (H = 8.74, p  = 0.013), but not by gender, age, or race. University students demonstrated generally positive perceptions and moderate adoption of AI technologies. The findings suggest that perceived usefulness, perceived ease of use, subjective norms, and attitudes towards AI are significantly associated with AI adoption. Higher education institutions should strengthen AI literacy, provide guidance on responsible and ethical AI use, and develop targeted strategies that address differences across academic disciplines and levels of study.