Rethinking AI Readiness: Why Implementation Isn't Transformation

As institutions invest in AI tools, policies, and training, many are declaring themselves “AI ready.” Yet a disconnect remains. Implementation is often mistaken for progress. Platforms are deployed and guidelines established, but the day-to-day work of faculty and staff—and the student experience—remains largely unchanged. This session challenges prevailing definitions of institutional AI readiness, arguing that readiness is not a function of technology adoption alone, but of alignment with the human systems that determine how work actually happens. Many institutions are heavily invested in tools and infrastructure but far less in the conditions that enable meaningful use: shared understanding, trust, practice, and support. Drawing on cross-functional experience in AI integration, the session surfaces a common pattern: institutions measure activity—tools launched, trainings delivered, policies written—rather than meaningful shifts in behavior, workflow, and decision-making. Participants will be introduced to a reframed model of AI readiness that distinguishes between implementation and transformation. The session will examine where current approaches fall short and how traditional rollout strategies create the illusion of progress. Through practical examples, participants will learn how to assess readiness more accurately, identify stalled initiatives, and use real-world use and feedback to refine strategy and support sustained change.