Artificial Intelligence in Higher Education

Artificial intelligence is increasingly embedded in the everyday practices of higher education, shaping assessment, governance, labor, and institutional legitimacy. Rather than presenting a technical guide or policy checklist, this volume instead offers a reflective, multi-voiced examination of what AI means for higher education’s purpose, identity, and future. Its phenomenological grounding shifts the focus from operational questions of implementation to deeper inquiries into how AI reshapes institutions, knowledge, and the academic self.

Drawing on historical and critical perspectives, the book interrogates AI as both mirror and accelerant of long-standing challenges: inequity, market-driven logics, and the erosion of slow, critical learning. Spanning geopolitical contexts and institutional types, it embraces pluralism over consensus, showing that AI will not transform all universities in the same way. Narrative interludes humanize these themes, revealing the anxieties, ambiguities, and hopes of those living through this transition.

Building on the work of Richard Heller on the distributed university and knowledge equity, the book situates AI within broader structural issues such as corporatised knowledge economies, managerialism, and unequal access to educational and research opportunities. At the same time, it highlights emerging possibilities―from open educational resources and equitable research practices to decentralised digital infrastructures―that can contribute to more ethical and resilient institutional arrangements.

Neither prescriptive nor simplistic, this book is intended as a catalyst for leaders, policymakers, and reflective practitioners seeking to navigate AI with wisdom rather than haste. It argues that the future of higher education will be shaped less by technological sophistication than by the clarity with which institutions articulate their values, responsibilities, and commitments to the public good.