This volume examines how artificial intelligence, automation, blockchain, and data-informed governance are changing decision-making in higher education. Ten chapters move from academic credentials and learning records to educator roles in open and distance learning, university digital transformation strategies, faculty capability development, smart teaching governance, AI-supported teaching tools, disability inclusion, and digital-age policy. Contributions from multiple national and institutional contexts combine conceptual analysis, case comparison, technical architectures, and practical institutional recommendations. A central concern is how universities can use intelligent systems to improve efficiency, trust, access, and responsiveness while preserving professional judgment, transparency, privacy, and human responsibility. The volume treats faculty development and inclusion as essential parts of technological transformation rather than secondary implementation issues. Intended for researchers, university leaders, faculty developers, quality assurance professionals, policymakers, IT teams, and graduate students, it argues that decision intelligence becomes educationally valuable only when automation is governed ethically, interpreted critically, and aligned with institutional learning.

This volume examines the transformation of higher education through smart university models, digital learning, artificial intelligence, and administrative innovation. Twelve chapters connect global collaboration, adaptive learning in sports education, responsible AI feedback, decentralized and hybrid pedagogy, institutional digital transformation, faculty role change, student online experiences, academic quality, teaching capital, and AI-driven university administration. The contributors combine conceptual reviews, empirical cases, governance analysis, and practice-oriented frameworks from diverse geographic and institutional contexts. Rather than treating smartness as a collection of technologies, the volume asks how universities can integrate data, automation, learning platforms, and intelligent systems while protecting equity, trust, privacy, and professional judgment. It highlights student experience and faculty capability as critical tests of whether digital transformation creates genuine educational value. Intended for researchers, university leaders, faculty, quality assurance professionals, policymakers, administrators, IT teams, and graduate students, the volume argues that smart universities must be designed as humane, accountable, and continuously learning institutions.