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 analyzes digitalization, artificial intelligence, accreditation, rankings, and internationalization through the lens of future accountability in higher education. Ten chapters bring together Pacific, African, Asian, European, and broader Global South perspectives on prestige, inclusion, governance, and institutional transformation. The volume examines ethical foundations of academic reputation, inclusive quality assurance, accreditation as governance and political practice, ranking actors and algorithms, India’s National Education Policy 2020, borderless accreditation, Ubuntu-informed approaches to quality, flexible internationalization during systemic instability, and the movement from digitalization toward institutional smartness. Across these themes, the contributors challenge accountability models that privilege visibility, mobility, and standardized metrics over relationships, context, and public purpose. Intended for researchers, institutional leaders, accreditation and quality assurance professionals, policymakers, faculty, and graduate students, the volume argues that responsible transformation requires transparent data practices, context-sensitive standards, inclusive participation, and a critical understanding of how prestige systems distribute power and opportunity.