Higher‑education classrooms are seeing a collision of student adoption, pedagogical experimentation, and institutional lag. A survey of roughly 1,000 college students by Honorlock found that while about half view AI proficiency as career‑important, only 31% are aware of AI courses at their institutions and fewer than 20% have taken one—students mainly use AI for low‑level tasks. Concurrently, instructors report using AI to personalize learning: faculty are assigning student‑generated case studies and using AI tools to create tailored scenarios that boost engagement. The gap between student use and formal instruction suggests campuses are trailing students’ self-directed AI adoption; institutions risk ceding curriculum control if they do not build structured coursework and ethical guidelines for AI use. Faculty development, curricular design teams, and academic integrity offices must coordinate to craft course offerings that move students from basic tool use to workplace‑relevant AI competencies. Leaders should prioritize creating coherent AI learning pathways, aligning pedagogy with workforce outcomes and building clear ethical frameworks for assessment and proctoring.