A new discussion of how business schools are approaching AI highlights a shift from debating whether AI belongs on campus to tightening the assessment and degree-purpose questions the technology now forces. The commentary points to students’ real-world use of AI tools, employer expectations for AI fluency, and the need to redesign learning models and evaluation methods. On the leadership side, S. Sriram of the University of Michigan Ross School of Business characterizes AI as an accelerant that surfaces structural weaknesses—such as assessments that over-reward task completion rather than judgment. Separately, coverage of which institutions are “doing the best at AI” frames the admissions and program-planning conversation around practical adoption capability—pushing MBA applicants to ask what is actually deployed, how outcomes are measured, and where institutional governance sits.