AI Professional Development

Your Teachers Are in Different Places With AI. Coach Them That Way.

Every staff has enthusiasts, skeptics and an overwhelmed middle when it comes to AI. The coaching research shows why one all-staff session can’t reach them all, and what school leaders can do instead.

By Jeff Utecht · · 8 min read

Teachers with mixed reactions discussing AI in a library staff circle while a school leader listens

Walk into any staff meeting this fall and you’ll find the whole AI spectrum in one room. One teacher has rebuilt half her unit with AI. Another tried it once, got a weird answer and quit. A third won’t touch it on principle. And a fourth is quietly using it every night but would never say so out loud.

Now picture the PD plan for that room: one session, one slide deck, one pace. It’s built for a teacher who doesn’t exist.

That’s why I think AI coaching for teachers, not another all-staff workshop, is the piece most schools are missing. There’s no single headline driving this post this week. It’s a pattern I keep seeing, and the research on coaching has been telling us how to handle it for years.

Key takeaways

The spread is the real story

We already know adoption is uneven, and not just between people. RAND’s survey panels found that 53% of English language arts, math and science teachers reported using AI for school in 2025, and the share rose at each level from elementary to middle to high school. At the same time, only 45% of principals reported having school or district policies or guidance on AI use.

Put those together and you get exactly the room I described. Some teachers are well down the road, mostly on their own. Others are waiting for permission, or clarity, or a reason. Very few are getting support that meets them where they are.

I’ll admit something here: early adopters are a gift. But schools often make them the plan. They become the unofficial help desk, the go-to demo, the person everyone emails at 9 p.m. That’s not a strategy. It’s a burnout pipeline, and it does nothing for the colleague who is anxious and quietly opting out.

What the research says about AI coaching for teachers

School leaders don’t need convincing that coaching works. But it’s worth remembering how strong the evidence is, and what the fine print says.

Kraft, Blazar and Hogan’s meta-analysis in the Review of Educational Research combined 60 causal studies of teacher coaching. They found a pooled effect of 0.49 standard deviations on teachers’ instructional practice and 0.18 on student achievement. That’s a lot for professional learning.

Here’s the fine print that matters for AI: effects were smaller in larger programs. The authors note that average effects from trials of larger programs are only a fraction of those from smaller ones. Scaling coaching while keeping it effective is hard.

So the lesson isn’t “hire coaches and you’re done.” It’s that coaching works when it stays close to the teacher: their classroom, their content, their worries. Just as AI tools and expectations keep shifting, coaching has to keep adjusting with them.

I’ve seen this before. I’ve been doing long-term partnerships with schools since 2009, starting with 1:1 laptop rollouts. Back then, too, every staff split into enthusiasts, skeptics and the overwhelmed middle. The devices didn’t change learning. Sustained support for teachers did, and it had to look different for each of those groups.

Where schools usually go wrong

What school leaders can do this month

  1. Map your staff, honestly. Use a short, anonymous pulse: “Where are you with AI right now?” with four or five options from “not using it and don’t plan to” to “using it daily.” Add one open question: “What would help?” You’re looking for the shape of the room, not names.
  2. Offer different on-ramps. Instead of one session, offer three: a low-stakes “what is this, really?” conversation, a hands-on build session around a real task, and an advanced group that tests and critiques outputs. Let teachers choose.
  3. Give your coaches an AI focus, not an AI job. Ask instructional coaches to fold AI into the coaching cycles they already run (planning, feedback, differentiation) rather than launching a separate AI program.
  4. Protect your early adopters. Give them a defined role, like hosting one open lab a month, and a limit. Thank them publicly. Don’t make them the help desk.
  5. Talk about the worries out loud. Put one agenda item on your next staff meeting: “What concerns you most about AI in our school?” Then actually answer. The BAKE mindset framework (balance, adaptability, knowledge-sharing, empathy) is a useful lens for leadership teams running that conversation.
  6. Check in at 30 days. Whatever you launch, schedule the follow-up now. Ask what teachers tried, what failed and what they need next.

Why this is partnership work

Differentiated AI coaching sounds simple on a slide. In practice, it means someone has to design the pathways, support your coaches, keep pace with the tools and keep the conversation honest across a whole year. Internal teams can and should own this eventually. Most just don’t have the bandwidth to build it from scratch while running a school.

That’s where an embedded partner helps. Across a year, that might look like a leadership team session to agree on purpose and guardrails, ongoing work with your instructional coaches so they can carry AI into their cycles, differentiated sessions for teachers at different starting points, and a parent night or board briefing so the community understands what’s changing. Face-to-face, virtual or a combination, depending on the outcomes you’re after. Every contract is unique, which is why it’s a partnership. Our K-12 AI implementation guide shows how those pieces fit together.

I bring 25 years in education, an international lens from working with US districts and international schools, and no vendor agenda. Just as important, I bring continuity: someone who knows where your staff were last spring and can meet them where they are this fall.

One PYP coordinator captured the heart of this after a workshop:

“Working with many early adopters at our school, I was eager to just keep charging ahead. However, after listening to different participants, I was reminded that there is a spectrum of responses and attitudes among educators, ranging from fear and skepticism to enthusiastic embrace.”

Tricia Friedman and I dug into this on the Shifting Schools podcast in What to Do When Teachers Are at Very Different Places With AI, including why low-stakes experimentation and treating AI learning as ongoing matter so much.

FAQ

What is AI coaching for teachers?

AI coaching for teachers is ongoing, one-on-one or small-group support that helps teachers use AI in their own planning, feedback and instruction. It builds on existing coaching cycles rather than a one-time training, and adjusts to where each teacher is.

How do you train teachers who are at different levels with AI?

Start by mapping where staff are, then offer several entry points instead of one session: a conceptual on-ramp, hands-on work around real tasks, and an advanced group that evaluates outputs. Follow up within a month.

Does instructional coaching actually work?

A meta-analysis of 60 causal studies by Kraft, Blazar and Hogan found coaching had large effects on instruction and positive effects on student achievement, though effects were smaller in larger programs.

Meet them where they are

Your staff will never be in one place with AI. That’s not a problem to fix. It’s the design brief.

So here’s my question for you: who on your staff is quietly being left behind by your current AI plan, and who is quietly carrying it?

If you want to build AI coaching that reaches every teacher, book a 30-minute call with me. Every partnership is tailored, so reach out and we’ll talk through pricing and what a partnership could look like for your school. You can also email me at jeff@jeffutecht.com.

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