I ran AI training for six department chairs, walking them through how to redesign assignments for a world where students have these tools too. Going in, I assumed the hard part would be the tools. It was not. The tools are easy. The hard part was fear.
Fear of getting it wrong in front of students. Fear that AI just means cheating. Fear, quietly, of being made redundant. I think most AI adoption stalls right there, and no feature solves it.
Name the fear before the feature
So I started every session by naming the worry out loud instead of pretending it was not in the room. Yes, students will use these tools. No, that does not make your expertise worthless, it makes it more important, because now the job is teaching judgment, not just facts. Once people felt that their value was not under threat, they got curious instead of defensive.
You cannot teach someone a tool while they are afraid of it. You have to address the fear first, then the features almost teach themselves.
Make the first win small and real
Nobody adopts anything from a slide. So instead of a grand demo, we took one assignment each chair actually used and redesigned it together, right there. A small, concrete win they could see working beat any amount of me describing the possibilities. We also kept ethics in the room the whole time - responsible use, being honest with students about it, not pretending the tools do not exist.
What I would tell anyone rolling out AI to a hesitant team:
- Start with the fear, not the feature. People cannot learn while defensive.
- Reframe their expertise as more valuable, not less, in an AI world.
- Redesign one real thing together, so the first win is concrete and theirs.
- Keep ethics in the conversation from minute one, not as a disclaimer at the end.
By the end, the chairs were not asking whether to use AI, they were asking how to use it well with their students. That shift, from fear to curiosity, was the whole job.