From Repository to Circulation: Rethinking the University in the AI Era
Artificial intelligence is no longer simply another technological wave. It is rapidly becoming a general-purpose cognitive infrastructure, collapsing the boundary between knowledge production and real-world deployment. Across sectors, AI is shortening the half-life of expertise: models evolve faster than textbooks, and applied knowledge shifts more quickly than curricula can traditionally accommodate. In such a landscape, the question facing universities is not whether AI should be taught. The deeper question is how universities must reorganize themselves when intelligence itself becomes computationally augmented. Adding AI electives or partnering with online platforms may signal responsiveness, but these remain surface-level adjustments. If AI is infrastructural, the response must be structural. Universities must move beyond offering AI as a specialized track and instead embed it within the epistemic core of each discipline. The challenge is not “AI education”. It is disciplinary...