A debate over artificial intelligence in student work has moved from academic op-eds to policy rooms. Dr. Nafisa Baba‑Ahmed argued that AI has revealed longstanding flaws in assessment design, saying universities should stop romanticizing a pre‑AI past and instead redefine what skills they require students to demonstrate. The piece frames AI as an amplifier of existing shortcuts—essay mills, shared model essays and heavy tutor reliance—rather than a wholly new problem. Separately, national data and studies flagged broader learning declines tied to digital-first pedagogy and growing AI use among students. Researchers and educators warn that unrestricted AI access can erode critical thinking and basic literacy, and that K–12 trends—less screen restraint, fewer text‑based resources—are bleeding into higher education preparedness. University leaders are now weighing new assessment formats, proctoring policies, and curricular changes to guard academic standards while preserving legitimate AI uses like research assistance. Practical steps under discussion include redesigning assignments to emphasize in‑class demonstrations, oral defenses, and project‑based evaluation that require time‑bound cognitive work. Legal and equity questions remain: how to enforce policies without disadvantaging students who lack access to proctoring technology or alternative learning supports.