Districts Spend on AI Chatbots and Robots as K-12 Evidence Stays Thin

Dayton Public Schools in Ohio paid $72,600 for AI tools from SchoolAI, including a social-emotional-learning chatbot called “Jordan,” during the last academic year, then renewed the contract for $78,650 for the current school year, NPR reported on September 28, 2026. The spending is part of a wider pattern of US school districts adopting AI in K-12 schools with little independent evidence that the tools improve learning, according to reporting by NPR’s Lee V. Gaines that surveyed districts, researchers and a review of the academic literature by Stanford University’s SCALE Initiative.

Dayton Superintendent David Lawrence defended the investment. “I think when the history is written, it’ll say that ‘Hey, they were really cutting-edge, innovative and ahead of the curve in the interest of children,'” he told NPR. The Jordan chatbot was designed collaboratively by Dayton schools, SchoolAI and an outside consultant, and is used at the district’s Alternative School at Jackson Center.

What the Stanford SCALE Initiative found on AI in K-12 schools

Stanford’s SCALE Initiative, in a report titled “Artificial Intelligence in K-12 Schools” published in June 2026 by researchers Cristina Barnard, Lily Fesler and Susanna Loeb, reviewed more than 800 academic papers on AI in K-12 education and identified only 20 high-quality causal studies measuring impact on students or educators. The review “found no high-quality causal studies conducted in U.S. K-12 schools on student-facing AI tools,” even as the report’s own survey data show 54% of middle and high school students report using AI for schoolwork and 53% of English, math and science teachers report using it for instructional tasks.

Robin Lake of the Center on Reinventing Public Education described the current landscape to NPR as unregulated: “It feels very Wild West in terms of the randomness.” Rebecca Winthrop of the Brookings Institution raised concerns about experimenting on students without stronger evidence: “I don’t think you should just sort of wildly experiment, especially with really marginalized communities.”

In Wichita Public Schools in Kansas, AI specialist Katelyn Schoenhofer said the district is rolling out tiered AI access by grade level, using tools including an AI math tutor from Edia and the image generator Canva AI. She told NPR the district has not settled on how to measure whether the tools work: “We wrestle with what does success really mean when it comes to AI use? And what metric do we want to use in order to evaluate that? And we have not come to an answer yet.”

The evidence gap has not stopped districts from moving ahead with distinct approaches. New York City is banning student-facing AI for pre-K through eighth grade while allowing limited high school pilots, and Los Angeles Unified suspended generative AI on district devices. Ohio, where Dayton is located, took the opposite approach at the state level: Ohio now requires every school district to adopt a written AI policy, without prescribing which tools to buy or ban. Salamanca City Central School District’s roughly $58,000 humanoid-robot pilot illustrates the range of purchases: the district first deployed the Realbotix “Sally” robot before pausing the pilot after state regulators raised concerns. A separate nonprofit review of AI learning tools also found mixed results for classroom effectiveness, reinforcing the SCALE Initiative’s conclusion that rapid adoption is outpacing rigorous evaluation.

Mike Kentz, an outside consultant who worked with Dayton on its chatbot, acknowledged the limits of current measurement: “Every test, every experiment that I try to measure in some sort of concrete way, I can only get as far as perception.” The SCALE Initiative report recommends judging AI tools by whether they expand access to already-proven educational practices, such as personalized instruction and sustained relationships with educators, rather than relying on vendor-specific claims that can become outdated as products change.

Background

Stanford’s SCALE Initiative operates within the Stanford Graduate School of Education and maintains an ongoing repository of research on AI in K-12 education, which the university said had grown past 1,100 papers by the time its evidence report published in June 2026. The center’s review method screens studies for causal designs, such as randomized trials or comparisons with credible control groups, rather than counting any published paper as evidence of effectiveness. NPR’s September 28, 2026 reporting drew on that review alongside direct interviews with district administrators, an AI specialist and researchers to show how districts are making purchasing decisions in the absence of the kind of evidence the SCALE Initiative says is still missing.

Sources: NPR (via WVIA); Stanford SCALE Initiative; GovTech

Featured image: photo by Yan Krukau on Pexels (free Pexels license).

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Figen Sekin

I specialize in sustainability education, curriculum co-creation, and early-stage project strategy. At WINSS, I craft articles on sustainability, transformative AI, and related topics. When I’m not writing, you’ll find me chasing the perfect sushi roll, exploring cities around the globe, or unwinding with my dog Puffy — the world’s most loyal sidekick.