This past school year brought a defining question to the forefront of K-12 education: How can we harness the rapid rise of artificial intelligence in ways that are responsible, equitable, and useful to education leaders, students, and their families? We asked five leaders from across Education Analytics to reflect on what they observed working alongside our partners, and what that could mean for the path ahead. Below, they share key takeaways from the 2025-26 school year.
This year reinforced for me how much momentum exists across states to rethink how education data can better serve students, families, and educators. From digital learner records to Ed-Fi modernization and workforce readiness initiatives, we’re seeing partners move from conversations about interoperability into real implementation and collaboration across systems. What continues to inspire me most is that the strongest progress happens when people stay deeply connected to the mission behind the work. Sustainable transformation requires trust, shared ownership, and cross-functional teams willing to solve hard problems together.
The word I keep coming back to this year is momentum. For years, partners have been building the analytic foundation around core administrative and outcome data — understanding who students are, where they are, and how they’re performing. Now I’m seeing real energy to layer on top of that: connecting programs and interventions that answer how students are being supported, and workforce and career outcomes that answer how education prepares them for the world. With responsibly applied AI, combining those three lenses into a full picture of student success is more within reach than ever.
This year’s theme has been dividends. Education agencies that have made investments in their data infrastructure during the last seven years are seeing a number of use cases blossom from the availability of data. The addition of AI to the ecosystem has forced a reckoning with the concepts and practice of governance, data management, and data variety that furthers the value of long-term data infrastructure investments.
There is now wide interest in rigorous pedagogically appropriate AI software to improve education outcomes. The sector has been moving toward using learning science methods to evaluate these AI systems as education interventions, as well as agency-controlled privacy and security governance. The infrastructure is catching up to the demand.
Education agencies are joining the national movement of government agencies working together across the country to build the software they need to support their core operations. What's interesting is how many of the problems that need to be solved to empower AI use cases are really problems that predate modern AI. How do school systems manage their own data, determine who can interact with the data, and apply their agency's policy and interpretation opinions to the data?
The 2025-26 school year asked school districts to develop policies around the responsible use of AI, while also managing the essential questions around data governance, asking school leaders to further prepare for safe, secure, and modern infrastructure as the foundation for best serving students.
