I Read 25 Studies on AI in Education. Here’s What Teachers Are Actually Doing.

Findings from the first artifact in Ed3's Portrait of a Teacher in the Age of AI

Over the last few months, I systematically analyzed 25 major research studies on generative AI in K-12 education — national surveys, state-level data, behavioral platform analytics, qualitative research — published between early 2023 and late 2025. The goal was simple: align them into a single picture of what teachers are actually doing with AI right now.

The synthesis was published this month by Ed3 as the first artifact in their Portrait of a Teacher in the Age of AI project.

The full report is here: Between Promise & Practice.

What follows are the findings I think matter most — and what they tell us about where the conversation is headed.

---

Teachers are using AI. A lot.

Depending on how you ask the question, somewhere between 25% and 87% of K-12 teachers have used AI for school-related purposes. That range is wide because the studies measure different things. Microsoft’s 87% includes anyone who used AI “once or twice.” RAND’s 53% asks specifically about instructional planning. The most conservative numbers still show majority adoption within three years of ChatGPT’s launch.

That debate is over. Teachers are using AI. The question now is how.

Almost all of it is lesson prep.

This is the finding that should reframe the conversation. Across every study that reports use cases, the pattern is the same: teachers use AI to plan lessons, create assessments, edit content, and draft communications. Back-end work. Preparatory tasks.

Student-facing use is minimal. In Utah’s statewide data — the largest dataset in the set at 7,595 teachers — only 17.3% use AI for student personalization. Only 9.5% have created chatbots for student use.

Stanford’s behavioral study (not self-reported — they tracked what 9,081 teachers actually did on the SchoolAI platform) found something even more revealing: the more experience teachers gained, the less they used student-facing tools. Power users shifted toward teacher productivity features. New users tried the chatbots, but experienced users stopped using them.

Teachers are not handing AI to students. They’re using it to do their own work faster.

No one has measured whether any of this helps students learn.

Zero studies in this set measure whether teacher AI use improves student learning outcomes. The benefits are perceived, not demonstrated. Teachers believe AI saves them 5-6 hours a week. They believe it improves their teaching methods. They may be right. But two years into widespread adoption, the K-12 evidence base is empty.

This matters because the entire edtech AI narrative is built on the assumption that AI integration equals better outcomes. The data doesn’t support that claim. It doesn’t refute it either. It simply doesn’t exist.

The studies that do exist — like the MIT cognitive debt study — measure neural engagement during tasks, not whether students actually learned more or less over time. Others, like Alpha School's claims of doubled learning rates, are self-reported and have not been independently verified.

Teachers aren’t skeptics or believers. They’re pragmatists.

The most interesting finding cuts against the polarized discourse. The same teachers who report that AI is unreliable (52%) and creates additional verification work (71%) also say it improves their methods (69%) and gives them more time with students (55%). The same teachers who see moderate-to-severe risk (87%) also believe it will boost student engagement in the future (87%) and express positive perceptions of AI (55%).

If they were true skeptics, they wouldn’t use it. If they were true believers, they wouldn’t flag the risks. What the data actually shows is a middle position that neither the AI hype cycle nor the AI panic cycle acknowledges: teachers are adopting tools they find imperfect because, on balance, they perceive the trade-off is worth it.

This duality is not a contradiction. It's a signal that teachers are using their professional judgment to make the call on when and how to use AI in their work.

Half of them have had no training.

Roughly 50-52% of teachers report no formal AI training. Fifty-two percent taught themselves. Only 19-51% of schools have AI policies. Sixty percent offer no guidance at all.

Adoption has outpaced institutional readiness. Teachers are making those judgment calls without institutional support. According to Microsoft’s 2025 report, 82% of administrators say AI is integrated into curriculum. Only 54% of teachers agree.

What this means

The research base we have is shallow. Almost every study counts users and lists tasks. Almost none examine the depth or quality of AI use, the invisible labor behind “seamless” integration, or whether the tools are actually changing how students think.

That’s what twenty-five studies and two years of data gave us — a clear picture of the gaps. Now it’s time to fill them.

This is the first artifact in Ed3’s Portrait of a Teacher in the Age of AI project. The full report, including methodology, data tables, and limitations, is available at ed3global.org/portraitofateacher