Higher education leaders are increasingly treating AI readiness as an instructional design and governance problem, not just a technology rollout. New reporting highlights that colleges are pushing AI into coursework while also grappling with student mistrust and the risk that AI use crowds out deeper learning and judgment. In one new study-based discussion, researchers tied to the University of Pennsylvania reported evidence that AI teaching assistants can reduce student motivation and performance—especially for students whose teachers were already weaker—suggesting that reliance can function as a “crutch” rather than a learning support. The study’s findings raise immediate classroom-level questions about how AI tools are integrated into assessment and feedback loops. Meanwhile, separate guidance on AI in teaching argues universities must redesign learning experiences around the role of classrooms in fostering social engagement, discourse, and focused attention—areas that generative tools cannot replicate. The emphasis is shifting to classroom purpose, learning fundamentals, and deliberate use of AI to strengthen critical thinking rather than automate judgment.