Meeting Faculty Where They Are: A Multi-Scalar Approach to Change Management for AI in Teaching

The adoption of generative AI in teaching is not primarily a technical challenge. It is a change management problem rooted in trust, professional identity, and academic values. This poster presents a multi-scalar faculty development strategy that prioritized relationship-building and pedagogical autonomy over speed, resulting in widespread faculty participation without mandating AI use. Rather than position faculty resistance as a barrier, this approach met faculty where they were through department visits, peer-led conversations, task force partnerships, and development opportunities ranging from theoretical framing to hands-on experimentation. Faculty were explicitly affirmed in their right to feel uncertain or critical about AI, while also challenged not to ignore it and to help students understand the implications of their choices. The result was a shift from fewer than ten faculty engaging with AI across campus to more than one third of faculty participating in AI-related events. Session attendees will leave with a replicable, values-aligned framework for building sustainable faculty buy-in for AI and other emerging technologies.