Featured Resources

  • 2026 Quarter 1 AI & Interoperability Brief Release

    Interoperability is foundational to AI success in education, and building an underlying structure grounded in data standards and data maturity is key to implementing AI that will truly benefit schools and students.

    The 2026 Quarterly AI and Interoperability Brief Series explores the intersection of interoperability and AI, highlighting the latest trends, case studies, and tools you can use to improve your educational technology ecosystem.

  • Ensuring Timely and Consistent Implementation of IEPs for Military-Connected Students with Disabilities

    Currently, the lack of standardized, national definitions for core service terms creates a systemic ‘transfer gap.’ This lack of clarity often results in significant delays for students waiting to receive comparable services in a new district. To address this, researchers convened an expert panel to establish a much-needed consensus on these terms.

  • AI Data Use and Protection - Worksheet

    In the rush to adopt an AI tool, don’t let data security become an afterthought. The AI Data Use and Protection Worksheet is designed to help cross-functional leaders—from the CISO to General Counsel—a clear, standardized vetting process.

    This worksheet allows teams to create a side-by-side risk matrix for every vendor, allowing them to make a safe, confident, and informed decision before entering a vendor agreement.

  • Considerations for the School Districts in Considering Large Scale AI Model Deals

    As Artificial Intelligence (AI) and frontier AI models rapidly reshape the educational landscape, school systems face a dual challenge: harnessing these tools' transformative potential while rigorously safeguarding student data, privacy, and well-being. Procurement is no longer just about purchasing; along with AI literacy, it is the first line of defense in responsible AI governance.

    The following slide deck is available for consideration and understanding.

  • Considerations for the School Districts in Considering Large Scale AI Model Deals

    As Artificial Intelligence (AI) and frontier AI models rapidly reshape the educational landscape, school systems face a dual challenge: harnessing these tools' transformative potential while rigorously safeguarding student data, privacy, and well-being. Procurement is no longer just about purchasing; along with AI literacy, it is the first line of defense in responsible AI governance.

    For years, Project Unicorn has championed the need for data to flow seamlessly and securely between systems to inform instruction and operations. Simultaneously, the EDSAFE AI Alliance has led the global charge on the SAFE (Safety, Accountability, Fairness, and Efficacy) benchmarks for AI adoption in education.

    Now, as "frontier models"—highly capable, large-scale AI systems—enter our schools, these two missions must converge. Procurement is the intersection where safety meets connectivity.

    We developed this resource to bridge the gap between technical data governance and ethical AI implementation, responding to practical needs from our work leading 29 school district policy labs and 10 state policy labs. These questions are designed to help district and state leadership vet tools not just for what they can do, but for how they fit into a secure, interoperable, and learner-centered ecosystem. Whether you are evaluating a standalone AI app or integrating a large-scale frontier model, this guide can be part of your blueprint for responsible innovation.

Resource Database

District/School, Educators Project Unicorn District/School, Educators Project Unicorn

Privacy, Security, Interoperability

Why One Supports the Other: Data interoperability is a helpful component to building and maintaining quality software. Interoperability isn't a panacea, but making intentional and informed choices about implementing an interoperability standard contribute to better development practice, better privacy practice, and better security practice. Here are 5 ways interoperability, privacy, and security enhance each other.

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Parents Project Unicorn Parents Project Unicorn

Parents Value, Trust, and Rely on Education Data (DQC)

On behalf of the Data Quality Campaign, Harris Poll surveyed 914 US parents with children ages 5–17 about their attitudes toward data collection and data use in schools. This infographic displays key findings from the 2018 poll, demonstrating that parents value, trust, and rely upon publicly reported education data and individual data about their child to make important decisions to support their child’s educational success.

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