A new analysis argues students are becoming “AI fluent” faster than universities, and that institutions over-focus on academic integrity while underbuilding enterprise-wide AI strategy. The piece says AI is already reshaping how universities teach, advise, recruit, admit, communicate, assess risk, and make decisions—yet governance often remains fragmented, with policies that treat AI primarily as misuse in student work. It highlights a core risk: relying on imperfect detection tools rather than defining what it means to “think” and demonstrate knowledge in an AI-embedded environment. For higher education leaders, the immediate strategic requirement is structural—senior leadership and governing boards need coherent AI architecture, technical support, and clear expectations that guide faculty practice and student learning outcomes.