AI is increasingly embedded in academic work, yet faculty expertise remains difficult to surface and support. This session shares a project that uses a structured dataset of real faculty decision-making to train a local AI model as a cognitive apprentice, supporting reflection and professional judgment rather than automating decisions. Participants will see how capturing decision context, constraints, and reasoning reveals patterns in faculty work and informs more thoughtful AI integration. The session includes interactive moments that invite participants to reflect on real faculty decision scenarios and how judgment shifts across contexts.
