Artificial intelligence is already reshaping how school districts plan instruction, support teachers, and engage students. AI has the potential to transform the education delivery model and address learning gaps—but without more support, guidance, and resources, it could have the opposite effect.
This study examines how 27 “Early Adopter” school districts approached systemic AI adoption during the 2024–25 school year. Drawing on surveys, focus groups, and interviews with district leaders, the report identifies key patterns in district behavior, barriers to adoption, and enabling conditions that support meaningful progress.
Key Findings
- Early Adopters are still piloting AI strategies, not scaling them. Most districts remain in early, fragmented stages of AI experimentation.
- Early Adopters focus on efficiency over transformation. Districts are mostly using AI primarily to reduce teacher workload and improve productivity.
- A small vanguard is leading with bold visions for broader change. A few districts are strategically embedding AI into broader transformation agendas, using it to reimagine learning models, educator roles, and student experiences.
- Common enabling conditions are emerging. These include a clear vision, strong leadership that encourages a culture of innovation, integrated tech-instruction teams, and robust infrastructure (including tech access and readiness).
- Districts cannot unlock AI’s potential without investing in adult capacity. Most districts lack codified training or competencies for understanding AI.
- Many leaders report edtech fatigue and decision paralysis. The rapid pace of AI development, aggressive vendor marketing, and limited evidence of tool effectiveness are overwhelming educators.
- Lacking clear policies, infrastructure, and expertise, Early Adopters do not have a roadmap for AI adoption. Even committed Early Adopters face deep structural and policy barriers that constrain their ability to scale AI beyond isolated use cases.
- Early Adopters lack the tools and readiness to support special populations effectively. While AI shows promise for improving access and personalization, few tools currently meet the specific needs of multilingual learners or students with disabilities.
The report includes robust, stakeholder-specific recommendations for:
- District Leaders to embed AI into broader instructional and operational goals.
- Funders to focus on capacity building, systemic redesign, and inclusive innovation.
- State Policymakers to provide clear, coherent guidance and infrastructure.
- Edtech Developers to build tools that align with educator needs and system priorities.
Read the full report to dive in and learn more.
