Schools Are Playing Catch-Up on AI, New Education First Spinout Says — What Districts Need Next

Efekta, a spinout of Education First, has released research arguing that K–12 schools are struggling to keep pace with the spread of generative AI in education. The finding underscores persistent gaps in training, policy, procurement and assessment that districts must address as tools proliferate.

By Where Should I Learn Editorial · 2026-09-24

New research from Efekta, a spinout of education consultancy Education First, argues that K–12 schools are largely playing catch-up as generative artificial intelligence tools arrive in classrooms. The organization’s report — produced as the company begins working with districts and school leaders — frames AI adoption as a systems challenge that reaches beyond technology procurement and into teacher preparation, curriculum design and governance.

The central tension is simple and familiar: AI tools have moved quickly from research labs and consumer apps into the hands of students and teachers, but school systems remain organized around funding cycles, collective bargaining agreements and curricula that change slowly. That mismatch, the research says, leaves many districts making ad hoc decisions about whether and how to use AI rather than pursuing coherent, strategy-driven approaches.

One immediate implication is professional development. Teachers report encountering AI in their classrooms with little formal training on how to integrate it into instruction, evaluate tool quality, or address new classroom behaviors such as AI-assisted writing or problem solving. Districts facing constrained PD budgets and already overfull in-service schedules often treat AI training as an add-on rather than as part of ongoing instructional improvement.

Infrastructure and equity also surface as practical barriers. Reliable devices, network capacity, and permissive procurement rules vary widely across districts; where these resources are thin, the benefits of AI-driven tools are less accessible. At the same time, privacy protections, data governance and vendor contracts remain a concern for leaders who must balance innovation with student safety and family expectations.

Ethical and assessment questions add further complication. Teachers and administrators must contend with academic integrity when students can rapidly generate text, images or code, and they must decide whether existing rubrics and grading practices remain valid. Without clear policies, teachers are left to apply their own judgments, producing uneven outcomes for students and inconsistent signals about expectations.

Procurement processes present a separate set of hurdles. The market for edtech is fragmented and fast-moving, and many districts lack the capacity to evaluate AI claims or to negotiate contracts that safeguard data and ensure vendor accountability. Short pilot projects can generate useful local evidence, but they rarely scale without clear evaluation metrics and budget commitments.

Some districts have sought to manage these tensions through partnerships and pilots that pair classroom teachers with researchers, vendors and community stakeholders. Efekta’s work positions the organization as one such intermediary: helping districts interpret evolving evidence, design pilot studies, and craft policies that reflect local priorities. The company’s spinout status reflects a broader trend of research organizations moving into direct implementation support for school systems.

Assessment and accountability systems will need to evolve in parallel. Standardized tests and performance metrics were not designed with generative AI in mind, and educators raising concerns about fairness and validity will be looking for alternatives. Formative assessment practices, project-based tasks, and portfolio evidence are often pointed to as more resilient approaches, but they demand time and professional learning to implement effectively.

Experts advocating for a coordinated response recommend a mix of short- and long-term strategies: invest in teacher training that is embedded in everyday practice; create transparent procurement and data-governance standards; design pilot programs with clear evaluation criteria; and involve families and communities in conversations about acceptable uses of AI. District leaders also need forums to share lessons across jurisdictions so effective practices can spread more rapidly than isolated pilots.

Efekta’s research helps draw attention to the structural nature of the problem: AI adoption in education is not just a technology rollout but a policy, professional learning and equity challenge. While the organization’s report frames the issues, districts and state policymakers will face the harder task of turning findings into sustained investment and policy change that match the pace of technological development.

The urgency is practical. As students and families bring AI tools into daily learning habits, school systems that delay action risk producing inconsistent learning environments and widening inequities. Targeted research, coordinated policy responses and sustained investment in teacher capacity can help schools move from reacting to innovation toward shaping how AI is used to support equitable, rigorous learning. Efekta’s early work with districts may provide models for that transition, but broader collaboration among educators, technologists and policymakers will determine whether schools can close the gap.