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This book offers a structural re-examination of language use and role in higher education, challenging the assumption that English monolingualism and English-Medium Instruction (EMI) are necessary conditions for academic internationalization. Drawing on interdisciplinary research, it shows that the current model is not a neutral medium, but introduces measurable cognitive, pedagogical, and institutional costs, affecting learning effectiveness, classroom interaction, epistemic diversity, and monetary costs. These effects arise from a structural feature of monolingual systems: the use of a single operational language for both knowledge production and accessibility. Learning in a non-native language inevitably introduces cognitive load that cannot be eliminated, even at high levels of proficiency. As a result, EMI functions as a persistent trade-off between global accessibility and educational quality.

Recent advances in AI-mediated language technology significantly change these constraints. Building on these developments, this book introduces the concept of the Artificial Intelligence-mediated Native Multilingual University (UMNIA), a model in which teaching and learning take place in the most cognitively efficient language (typically the native language), while global accessibility is ensured through real-time AI translation and mediation.

The book develops conceptual foundations, technical and economic feasibility, and institutional implications, proposing a shift from monolingual internationalization to a structurally redesigned multilingual system.

This volume is intended for researchers in higher education, science education and linguistics, as well as university leaders, policy makers, and practitioners involved in internationalization and academic system design.