Faculty and administrators face escalating legal and procedural risk as universities respond to suspected AI misuse, particularly when institutions rely on AI-detector output without clear standards. A set of cases—including the University of Minnesota’s 2024 expulsion tied to alleged ChatGPT similarities and litigation over Turnitin-flagged work—illustrates how courts scrutinize notice, evidence, and appeal structure. The dispute over Haishan Yang at Minnesota showed how due process, documented hearings, and record-building can limit judicial reversals. By contrast, a New York court annulled misconduct action involving an Adelphi University freshman, Orion Newby, ordering the university to expunge the violation record after finding the basis for the determination “devoid of reason.” The emerging compliance lesson for higher education is concrete: misconduct frameworks need explicit evidence handling, transparent procedures, and appeal mechanics that are meaningful enough to withstand legal challenges.