Colleges and educators are shifting from bans to frameworks for generative AI, co‑creating agile academic integrity policies that center equity and faculty leadership. A higher‑education conference paper detailed a codesign process involving students, faculty and staff to craft flexible guidelines that can be updated rapidly as AI capabilities evolve. Practical classroom innovations are following: instructors are using AI to deliver differentiated instruction at scale—creating pretests, tailored learning paths and alternate assessments with generative systems. Proponents argue AI can enable personalized remediation and acceleration where previously impossible; skeptics warn about over‑reliance and integrity risks. Institutions are now tasked with two immediate priorities: creating inclusive, transparent policies that protect marginalized learners from policy side‑effects, and investing in faculty development so instructors can implement AI‑driven differentiation without compromising rigor or fairness. Provosts and academic technology teams should treat AI policy as iterative governance: pilot co‑created guides, monitor equity impacts, and align assessment design with learning outcomes and accreditation expectations.