A Multidimensional Analysis of AI Literacy Determinants: External Resources, Digital Skills, and Psychological Profile Among University Students

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External resources, digital competence, and psychological characteristics have each been linked to Artificial Intelligence (AI) literacy, but almost always in isolation, so the unique contribution of any one domain remains unknown. Grounded in social cognitive theory, this study models all three domains jointly. Data were collected from 303 undergraduates at a liberal arts university in Hong Kong and analysed using hierarchical multiple regression. Perceived resources and perceived teacher support explained 29% of the variance in AI literacy; prior digital competence added a further 3%; and personal innovativeness, technology anxiety, and growth mindset in technology added a further 6%, with all three being significant in the final model (total R2 = 0.39). The external predictors remained significant throughout but attenuated substantially, indicating that institutional provision is necessary but not sufficient. Technology anxiety, which correlated negatively with AI literacy at the zero-order level, emerged as a positive predictor once other determinants were controlled. Analyses of the five AI literacy subdimensions localised this effect to critical evaluation and ethical competence and found no association with the three performance-oriented dimensions, suggesting that anxiety operates through heightened vigilance rather than enhanced operational skill. These findings, which no single-domain design could have produced, indicate that fostering AI literacy requires attention to students’ psychological readiness and foundational digital skills alongside the provision of infrastructure.