Beyond AI Champions: A Replicable Framework for Program-Wide AI Curricular Integration

Most higher education programs rely on artificial intelligence (AI) champions experimenting in isolated courses, leaving students with fragmented and inequitable AI learning experiences. This session presents a replicable, program-wide framework for AI curricular integration developed through a structured, multi-stakeholder task force of faculty, staff, and students at a large R1 College of Pharmacy. Grounded in Backward Design and anchored by the EDUCAUSE AI Literacy Framework, our two-phase model moved from competency exploration to full curricular mapping across 30-plus courses in five months. The process produced an AI literacy resource piloted in pharmacy and assessed with pre/post measures; in summer 2025, that resource was simultaneously adapted for a university-wide General Education (GE) Launch course and re-adapted for the pharmacy curriculum, resulting in parallel deployment across an estimated 4,000 to 5,000 GE students and approximately thirty Doctor of Pharmacy (PharmD), BS in Pharmaceutical Sciences, and graduate pharmacy courses beginning in fall 2025. Attendees will leave with a competency mapping process, a practitioner validation protocol, and faculty engagement strategies applicable across disciplines and scalable to any academic unit facing accreditation constraints or curricular overload.