Universities are moving from traditional, instructor-centred delivery towards AI-enhanced education in which adaptive platforms, intelligent tutors, and generative AI assistants form part of everyday study. This paper examines that shift through a consumer behaviour lens, treating students as users and evaluators of an educational service whose adoption decisions are shaped by perceived usefulness, effort, social influence, enjoyment, value, risk, and habit. Drawing on technology acceptance theory, the theory of planned behaviour, the unified theory of acceptance and use of technology, diffusion of innovations, expectation-confirmation theory, and research on consumer resistance to innovation, the paper compares traditional and AI-enhanced education from the student's viewpoint, reviews empirical evidence on student acceptance of generative AI, and proposes a conceptual model with ten testable hypotheses and a measurement plan. It also describes a student decision journey and an adopter segmentation, and discusses implications for university strategy, teaching, and policy. The paper is conceptual and literature-based: it reports no primary survey data, and its tables and figures are syntheses of the cited sources. It concludes that students adopt AI where it offers clear value at low effort and acceptable risk, and that universities should treat adoption as a service-design and trust-building challenge rather than a purely technical one.