Article
Artificial Intelligence Literacy and Graduate Employability: A Cross-Disciplinary Study
Artificial intelligence (AI) is reshaping the skills that employers expect from university graduates, prompting renewed attention to AI literacy as a determinant of employability. This paper synthesizes recent theoretical and empirical literature to examine how AI literacy relates to graduate employability across disciplinary contexts, including business and management, STEM fields, and the humanities and social sciences. Drawing on established AI literacy frameworks and graduate employability models, the paper argues that AI literacy functions less as a standalone technical competency than as a meta-skill that interacts with self-efficacy, career adaptability, and discipline-specific practice to shape labour-market readiness. Evidence reviewed indicates that AI-literate students report greater career adaptability and confidence navigating AI-mediated work, but that the strength and nature of this relationship varies markedly by discipline, institutional support, and access to applied learning opportunities. The paper also identifies a persistent gap between employer expectations of AI-related competence and graduates' self-assessed readiness, alongside equity concerns tied to uneven access to AI education across fields of study. The paper concludes with recommendations for embedding cross-disciplinary AI literacy instruction, applied assessment, and employer-linked learning pathways into higher education curricula to strengthen graduate employability in an AI-mediated labour market.