AI Training Builds Confidence. It Doesn’t Erase the Fear.

Most districts treat AI professional development as the answer to teacher anxiety. Train people on the tools, write a clear policy, and the worry should fade. New survey data from Washington State suggests it doesn’t work that way.

Training built confidence. It did not touch the fear.

That’s not a reason to stop training. It’s a reason to stop expecting training to do work it was never designed to do.

What’s happening

On October 4, the Washington State Standard published a commentary from three Central Washington University faculty members — Josh Aubol, Steve Stein and Peter Klosterman — sharing results from a survey their College in the High School program ran in May 2026. They asked 222 high school math and English teachers about their attitudes toward AI, their institutions’ policies, their professional development, and how they and their students use AI.

The subject split is striking. Among English teachers, 57% said their attitude toward teaching had gotten worse since AI emerged, compared with 37.6% of math teachers. Concern about academic integrity followed the same pattern: 83.7% of English teachers versus 54.9% of math teachers. And yet English teachers were also more confident teaching responsible AI use — 45.5% compared with 24.4% of math teachers.

Then the finding that matters most for leaders. Clear institutional policies and quality professional development were associated with more confidence in using AI responsibly. But neither one significantly reduced teachers’ worries about academic dishonesty or their negative attitudes toward teaching. The authors call for discipline-specific professional development, clear policies for both teachers and students, and a considered approach that keeps student learning at the center of decisions.

A day later, on World Teachers’ Day, PTI coverage published by ThePrint reported on a new UNESCO report on teachers facing pressures from AI, climate change and migration. UNESCO estimates the world needs 50 million additional teachers by 2030, and fewer than 40% of teachers believe their profession is valued by society. The report also notes that teachers who feel valued are significantly less likely to consider leaving. The coverage points back to the joint statement education ministers adopted at UNESCO’s Digital Learning Week in September, which, in UNESCO’s summary, emphasizes that AI “must support and not replace their professional contribution and judgement” and commits to investing in teacher professional development and “ensuring that teachers take part in decisions about which systems enter their classrooms.”

Put the two together and you get one story. Teachers around the world are carrying more, feeling less valued, and absorbing a technology that touches the core of their work. Skills training helps. It isn’t the whole answer.

Why AI professional development alone won’t fix teacher morale

In Chapter 11 of Human Still Required, I write that fear is already in the room when leaders bring up AI. The question underneath it is about identity, not tools. If a machine can do parts of my job, what does that say about me?

Fear isn’t the problem. Silence is.

Human Still Required

Look at the English teacher numbers through that lens. Writing is the subject AI imitates most convincingly. The essay — for generations the proof of thinking in an English classroom — is exactly the kind of output a tool can now produce in seconds. Of course those teachers feel it more. Their professional identity is closer to the blast radius.

A workshop on prompting doesn’t answer that. A policy document doesn’t either. Those things answer the question “How do I use this?” The teacher is often asking a different question: “Does the thing I’ve spent my career getting good at still matter?”

Mourning what’s changing is not a failure of leadership. It’s a prerequisite for it.

Human Still Required

Leaders who skip this step usually mean well. They want to move people forward. But when the loss isn’t named, it doesn’t go away. It goes quiet, and quiet worry turns into distance.

Chapter 12 makes the other half of the argument. Most AI professional development is built on a training model, and training assumes the problem is knowledge. The Washington data shows knowledge was part of the problem — confidence went up. But the remaining problem is about thinking, judgment and meaning. That requires learning, not just training.

Professional learning that centers on tools produces trained technicians. Schools need adaptive professionals.

Human Still Required

The researchers’ call for discipline-specific professional development fits here. A math department and an English department are not facing the same AI. One-size sessions treat them as if they were. In my work with districts, the most useful conversations happen when a department sits down with its own assignments and asks, together, what still shows real thinking and what doesn’t.

UNESCO’s language points the same direction. Investing in teachers and giving them a part in decisions about which systems enter their classrooms is not a soft add-on to an AI strategy. It is the strategy. Teachers who help make the call tend to own it. Teachers who receive the call tend to manage it.

What leaders can do now

• Separate the two conversations. Run AI professional development for skill and confidence. Then hold a different conversation about what is changing in the work and what people are losing. Don’t let the first one stand in for the second.
• Go department by department. Ask English, math, science and other teams the same question: What part of your work feels most exposed by AI, and what do you most want to protect? Expect different answers. Plan different support.
• Bring teachers into tool decisions. Before your next AI purchase or pilot, put classroom teachers on the review team and give them real weight in the decision, not just a feedback form at the end.
• Name the value, out loud. Fewer than 40% of teachers worldwide believe society values their profession. Your staff won’t fix that number, but they will notice whether their own leaders say clearly why their judgment still matters in an AI-rich school.
• Measure more than confidence. If your post-PD survey only asks whether people feel ready to use the tools, add a question about how they feel about their work. The Washington findings suggest those can move in different directions.

If your leadership team wants to work through these questions together, the 5-Week Book Study walks through Chapters 11 and 12 with prompts built for exactly this kind of conversation.

Frequently asked questions

Does AI professional development reduce teacher anxiety about AI?

Not by itself. In the May 2026 Central Washington University survey of 222 high school teachers, clear policies and quality professional development raised confidence but did not significantly reduce concerns about cheating or negative attitudes toward teaching. Leaders need a separate, honest conversation about what is changing in the work.

Why are English teachers more worried about AI than math teachers?

The survey shows the gap but does not prove the cause. A reasonable reading is that writing is the work AI imitates most easily, so English teachers feel the change more directly — 83.7% reported academic integrity concerns, compared with 54.9% of math teachers. That’s a strong argument for subject-specific support.

How should teachers be involved in district AI decisions?

Early and with real influence. The ministerial statement adopted at UNESCO’s Digital Learning Week commits to ensuring teachers take part in decisions about which AI systems enter their classrooms. In practice, that means teachers on review and pilot teams before a purchase, not after.

The work training can’t do

Training is necessary. Confidence matters. But a confident teacher who no longer believes their work is valued is still a teacher on the way out.

The tools will keep improving. The leadership work stays the same: tell the truth about what’s changing, protect what matters, and make sure the people doing the work have a voice in how it changes.

When was the last time your staff heard you talk about AI without talking about a tool?

Sources

• Artificial intelligence in the classroom — Washington State Standard (commentary by Josh Aubol, Steve Stein and Peter Klosterman, Central Washington University), October 4, 2026
• Teachers navigating transformations driven by AI, climate change, migration: UNESCO report — ThePrint (PTI), October 5, 2026
• Education Ministers call for education to remain a common good in the age of AI at UNESCO’s Digital Learning Week — UNESCO, September 9, 2026 (background on the ministerial statement cited in the October 5 coverage)