Reconfiguring global LIS education: AI integration, pedagogical roles and epistemic challenges

Purpose This study aims to investigate how artificial intelligence (AI) integration is transforming library and information science (LIS) education globally, focusing on its impact on curricula, pedagogical practices and professional roles. By examining both structural patterns and lived experiences, it aims to reveal how AI reshapes the epistemic, ethical and social dimensions of LIS education in the algorithmic age. Design/methodology/approach This study adopts a multi-method approach, combining cross-national curriculum mapping of 28 LIS programmes with 25 in-depth interviews to uncover both structural patterns and lived experiences of AI integration in LIS education. A six-dimensional analytical framework is developed to assess curriculum design, pedagogical diversity and faculty alignment. This study further applies Marxist theory, phenomenology and AI ethics perspectives to interpret role shifts among educators and students, offering a nuanced understanding of the epistemic, relational and affective dynamics emerging. Findings AI integration in LIS curricula is uneven globally: North American programmes lead in technical–ethical balance, while European and Asian counterparts focus on theory or lag in formal adoption. Interviews reveal instrumental AI use dominates, causing role alienation (students as “system operators”, faculty as “technical facilitators”) and eroding reflective learning. This study highlights risks of dehumanization and fragmented cognition in AI-mediated environments. Originality/value This research uniquely applies multi-theoretical lenses to expose AI’s dual impact on LIS education: technical opportunities vs existential-pedagogical challenges. It proposes redefining LIS as cultivating “information governors” capable of critiquing algorithmic systems, advocating holistic curricula merging technical fluency, ethical reflection and humanistic inquiry. The framework and recommendations offer actionable insights for global LIS programmes to navigate AI-driven transformation responsibly.