Bridging minds and machines: the role of psychological readiness, experience, and digital competence in developing AI literacy

Purpose This study aims to investigate the key predictors of artificial intelligence literacy (AI literacy). It explores the mediating role of digital literacy (DL) in the relationship between psychological (interest, attitude and self-efficacy) and experiential (prior experience with AI tools) factors and AI literacy. Design/methodology/approach This study used a survey-based quantitative research methodology. Data were obtained from 754 students enrolled in various programs at the University of the Punjab. Structural equation modeling (SEM) was used to test direct and mediated relationships among constructs. Findings Interest, attitude, self-efficacy and prior experience significantly predicted AI literacy, both directly and indirectly through DL. Self-efficacy demonstrated the strongest total effect on AI literacy. Prior experience with AI tools significantly improved DL, which in turn enhanced AI literacy. The results highlight a dynamic interplay between psychological readiness and experiential learning, positioning DL as a crucial mediator in the development of AI literacy. Practical implications Educators and policymakers should design curricula that foster digital competence, encourage early exposure to AI tools and build learner self-efficacy. Structured, hands-on experience with AI technologies can support the development of confident and competent AI users. Originality/value This study presents a comprehensive model linking psychological and experiential variables to AI literacy through DL. It offers both theoretical advancement and practical guidance for educational stakeholders preparing learners for AI-integrated futures.