Majority of districts initiate AI training for teachers, reveals recent survey

A recent national survey indicates substantial growth in artificial intelligence (AI) training for teachers in U.S. school districts. According to the latest data from the American School District Panel (ASDP), over half of U.S. school districts have begun initiatives to integrate AI training for educators, marking a significant increase from previous years. As of fall 2024, 48% of districts reported training teachers on AI, up from 23% in fall 2023.

The ASDP is a collaborative research effort by RAND, the Center on Reinventing Public Education, and other educational organizations. The report reveals that district leaders hope to train nearly three-quarters of teachers on AI by fall 2025. Despite this growth, disparities persist across districts of different poverty levels. In fall 2024, 67% of low-poverty districts had provided AI training for teachers, while middle-poverty and high-poverty districts lagged at 42% and 39%, respectively.

Insights were gathered from interviews with 14 district leaders who initiated or planned AI training. These interviews highlight strategies in overcoming teachers' reluctance toward AI technologies. As one superintendent noted, the primary aim was “to lower the fear, lower the anxiety about students using it and encourage [teachers] to use it in whatever capacity . . . just play around with it, mess around with it.”

Districts varied in their approaches, with many preferring voluntary and opt-in formats over mandatory sessions. A superintendent emphasized, “I am not trying to push AI with my people, but I am trying to give them the tools if they’re interested.”

The do-it-yourself nature of these training programs, as described by 11 of the 14 district leaders, was driven by the need for tailored content and lack of external resources. This self-reliance also stems from previous overwhelming experiences with AI professional development.

Overall, the report suggests that while progress is noteworthy, the gap between low- and high-poverty districts continues to pose challenges. It proposes that equitable sharing of best practices and additional support for high-poverty districts are essential for minimizing disparities in AI education opportunities.