Source: Dusseault, B., Sims, M., & Berardino, M. (2025). AI early adopter districts: The promises and challenges of using AI to transform education. Center on Reinventing Public Education. https://files.eric.ed.gov/fulltext/ED674608.pdf
LEARN Brief Credit: Dr. Jeannie Haubert
Overview:
This is LEARN brief 1 of 4 coming out of a comprehensive study into AI usage at the district level. The Center on Reinventing Public Education (CRPE) spent a year studying 51 early-adopter districts nationwide — through interviews, focus groups, and surveys with 45 leaders across 22 districts — to answer a simple question: how far has AI adoption actually progressed? The verdict is sobering. Most districts are still experimenting at the margins, running scattered, short-term pilots that were never connected to a broader instructional strategy. Only a small vanguard is treating AI as a lever for real redesign of teaching, learning, and school structure. Superintendents who can honestly locate their own district on this spectrum — and understand what separates the leaders from the laggards — will be far better positioned to move deliberately instead of reactively.
Key Insights:
- CRPE sorted districts into four types, and 80% fall into the bottom two: Dabblers experiment with discrete tools in isolated classrooms with no centralized coordination or long-term goals; Emerging Users have piloted select tools and drafted some internal guidance, but AI work remains siloed from other initiatives and has no systemwide roadmap.
- AI adoption today is overwhelmingly teacher-facing, concentrated on saving time on lesson planning, differentiating content by reading level, drafting IEP language, and streamlining parent communication — real wins, but ones that leave instructional design and student experience largely untouched.
- Teacher-first pilots were often a deliberate on-ramp, chosen because they were lower-risk than student-facing tools (which raise thornier data-privacy questions) and because solving teachers’ own workload problems first builds buy-in among skeptical staff.
- A vanguard of roughly 1 in 5 districts — System Changers and Reimaginers — are embedding AI into broader plans for competency-based learning, redesigned educator roles, and future-of-work readiness. Many of these districts had strong digital-strategy foundations in place well before generative AI entered the public conversation in late 2022.
- The stakes of standing still are real: without an intentional shift toward deeper integration, AI risks becoming just another add-on that makes an already inequitable system more efficient — not more effective, and not more equitable.
Action Steps:
- Name — honestly, with your cabinet — where your district falls: Dabbler, Emerging User, System Changer, or Reimaginer. Don’t let a few enthusiastic early adopters create the impression of systemic progress.
- Inventory every current AI pilot and ask whether each one ladders up to your strategic plan, or exists as a disconnected side project championed by a single teacher or department.
- Study System Changer and Reimaginer districts — such as Elma School District (WA), which spent three years aligning AI with a competency-based learning system, and Gwinnett County (GA), which built a decade-long vision for AI-ready graduates — for concrete models worth adapting.
- Set a 12-month target to move at least one department or grade band from isolated pilot to a documented, resourced, systemwide strategy.
- Resist the urge to rush toward student-facing tools before your teacher-facing foundation and staff trust are solid — sequencing matters more than speed.
Full Article:
Read the full CRPE report: https://files.eric.ed.gov/fulltext/ED674608.pdf
