Preparing Educators to Teach AI Use

What’s happening

Student use of AI for schoolwork has risen sharply in three years while formal guidance for the teachers supervising it has moved far less. The guidance that does exist concentrates on the teacher's own productivity and on detecting AI-written work. Almost none of it addresses the job the evidence says decides the outcome: teaching students to use AI in ways that build capability instead of replacing it.

What the evidence shows

A nationally representative survey of 2,069 public K-12 teachers fielded in February and March 2026 found 82% receive no formal guidance on applying AI tools to their work. The pattern inside that number is the point: “no guidance” rates were highest for the student-facing uses — 69% for one-on-one instruction and tutoring, 71% for coaching their own practice — and lowest for producing worksheets and assignments, at 47%. Guidance is most available where AI saves a teacher time, and least available where it touches a student. (Survey commissioned by a foundation that promotes AI adoption in K-12; fieldwork was conducted on a probability-based national teacher panel.)

Separate national polling of 806 sixth- through twelfth-grade teachers describes what the training that does occur actually covers. Across all of them, only 11% say “how to respond if you suspect a student's AI use is detrimental to their well-being” was covered in any AI training or information their school provided — the least common topic asked about, below detecting AI-generated student work (18%) and responding to suspected misuse (15%). Teachers' own top-ranked priority was guidance on using AI tools effectively, and that was the most commonly covered topic at 29%. On the student side, more than 80% of students report their teachers did not explicitly teach them how to use AI, and 30% of teens say a teacher has ever discussed how to use AI safely.

This matters because the instructional evidence identifies teacher design as the variable that decides the outcome. In a randomized trial of roughly 1,000 high school students, unrestricted GPT-4 raised in-session performance 48% but left those students 17% worse on a later unassisted exam; a version whose safeguards were written by two of the school's own math teachers eliminated that harm entirely. And in a two-year randomized trial across 18 middle schools, an AI tutor deliberately configured to coach rather than give answers produced gains resembling the same platform without AI — because 96% of students tried it, but the median student messaged it on only a third of the days they practiced, and in only 17% of the sessions where they made a mistake. The tool was built correctly. Nothing taught the students, or the adults around them, to use it that way.

Where it reaches constituents

Teachers in every subject and grade, and the students they supervise. Because the effect of student AI use turns on usage mode rather than access, the adult best positioned to change the outcome is the classroom teacher — and that is the role current guidance addresses least. The gap is also uneven: district-level AI training reached 67% of low-poverty districts in fall 2024 against 39% of high-poverty districts, and nearly all of it was optional.

The current legal & regulatory landscape

Federal Executive Order 14277 (April 2025) directs the Secretary of Education to prioritize existing discretionary grant funds for educator AI training and to support professional development for educators across subject areas. It creates no new appropriation and requires nothing of states or districts. At least 27 states had issued K-12 AI guidance as of August 2025; that guidance is advisory in every case reviewed, and several state documents say so explicitly.

A much smaller number of states have legislated anything about educator AI training, and one has gone furthest on what that training must look like. Maryland's Artificial Intelligence Ready Schools Act, signed May 26 and effective June 1, 2026, requires the state education department to provide professional development to educators and school leaders that is “sufficient in duration and quality” and substantively covers effective use, privacy, security, academic integrity, and means of avoiding overdependence — delivered either during the regular workday as designated professional-development time or as a course eligible for licensure-renewal credit. The duty runs to the department to offer it, not to the individual teacher to complete it. The same Act requires every local school system to adopt an AI policy within 120 days of the department's guidance and to designate an AI coordinator. Idaho and Hawaii have enacted measures including training provisions, Hawaii's with a $5 million pilot. No rigorous evaluation of an AI-specific educator training program with measured student outcomes appears to exist: a Stanford review screened more than 800 papers and identified 20 high-quality causal studies, none of them evaluating AI teacher professional development.

Considerations policymakers are weighing

• ·Whether educator AI training addresses the instructional mediation of student AI use, or is bounded by tool mechanics and academic-integrity policing — the two areas the national data show currently dominate.
• ·How the format of any training requirement compares with what the professional-development research associates with measurable effect. A review of 35 rigorous studies identifies content-specific focus, coaching, collaboration, modeled practice, and sustained duration; NCDPI's own guidance recommends a four-to-six-week practice period. Short asynchronous module formats are the most common approach and the least studied.
• ·Whether a training requirement is paired with evaluation, given that no rigorous evaluation of AI-specific educator professional development currently exists to copy.
• ·How curriculum requirements for students are sequenced relative to preparation for the teachers who deliver them.

Listed as live debates, not recommendations. CPAI does not take a position on how these should be resolved.

Key sources