The NIST AI Risk Management Framework gives organizations a useful structure for trustworthy AI governance, but districts need that structure translated into practical questions, maturity levels, evidence expectations, and improvement steps. CAGR, the CyberReady AI Governance Rubric, was built to make that translation usable for K-12 environments.
CAGR follows the four core AI RMF functions: GOVERN, MAP, MEASURE, and MANAGE. GOVERN focuses on accountability, policy, organizational culture, stakeholder engagement, and third-party governance. MAP focuses on intended use, context, categorization, AI components, and impact characterization. MEASURE evaluates methods, metrics, trustworthy AI characteristics, risk tracking, and feedback loops. MANAGE addresses prioritization, response, third-party risk, communication, incidents, and continuous improvement.
The value of a maturity rubric is that it gives leadership a path. A district may begin with informal AI awareness and partial tool lists, then advance toward documented policy, formal inventory, risk classification, monitoring, and board reporting. This is more useful than a yes-or-no checklist because it shows both current posture and what needs to change next.
CAGR is paired with CAIRE, CyberReady's AI governance evaluator methodology. CAIRE helps evaluators collect evidence, interview stakeholders, document notes, and validate whether a maturity level is supported. That distinction matters because a district can claim to have AI governance, but governance maturity should be supported by policy, process, ownership, review cycles, and documented decisions.
For buyers, CAGR creates a defensible AI governance product layer. It aligns to a recognized national framework while remaining specific enough for K-12. It can support district self-assessment, third-party evaluation, managed governance services, or a broader platform that combines cybersecurity and AI oversight in one executive reporting system.