📄 Full text: NASBE · local
Definition
A NASBE/CRPE policy analysis (May 2026) examining how US states can shape conditions for effective teacher AI adoption — setting guardrails, providing resources, and building capacity without micromanaging implementation.Key Data Points
- 54% of students used AI for school in 2025 (+15 pp vs. prior)
- ~2/3 of K-12 teachers used AI in 2024-25
- Teachers using AI weekly saved ~6 hours/week on planning, grading, feedback, admin
- Only 45% of principals report having school/district AI policy/guidance
- 35 states/territories have official AI guidance (as of Dec 2025), mostly nonbinding
- Equity gaps: suburban, majority-White, low-poverty districts twice as likely to provide AI training vs. urban/rural/high-poverty
Five Recommendations
1. Define statewide vision — align with workforce needs; create AI task forces; adopt literacy frameworks 2. Shift to learning organization model — capacity over compliance; cross-functional teams; rapid guidance updates 3. Support tool evaluation and procurement — "fewer, better" tools; evidence standards; outcomes-based contracts 4. Center human connection — AI must foster, not replace, human relationships 5. Build evidence infrastructure — fund research on what works; share findings across districtsConnections
- Complements faculty-development-genai with state-level policy levers
- Extends regulation discussion with concrete state-level mechanisms
- Equity gaps data reinforces concerns in equity-in-ai-education
- "Human connection" emphasis connects to teacher-role
Related Pages
- teacher-ai-adoption-confidence — Policy levers for building teacher AI confidence