This session introduces T3’s AI Adoption Rubric and Survey Suite, tools designed to help institutions assess their current stage of AI readiness using evidence rather than assumptions. Participants will learn how to use surveys for faculty, staff, students, and leadership, and how to translate results into actionable steps. The session covers five assessment dimensions: Adoption...
This session examines the current state of AI-related professional development across higher education, highlighting gaps in training access, strategy, and coordination. It introduces four emerging training roles; faculty/peer trainers, administrators, students, and external partners, and provides a framework institutions can use to build sustainable, institution‑wide AI capacity. This session is intended for senior leaders in...
This session examines the full range of costs associated with institutional AI adoption. It addresses both direct expenses such as licensing fees, and the less visible resource commitments required, including time, staffing, and organizational culture. The session also highlights challenges related to a rapidly evolving vendor landscape, where AI features are released faster than governance...
This capstone session synthesizes findings from T3 Advisory's study on institutional AI adoption. It focuses on the shift from isolated pilots to coordinated, campus‑wide strategy and examines how institutions that are moving beyond experimentation structure governance, align AI efforts with institutional priorities, and build shared capacity across campus. The session outlines the key practices that...
