AIRG Institute Frameworks
Practical governance frameworks for responsible AI, cybersecurity resilience, critical infrastructure protection, and enterprise accountability, designed for boards, executives, auditors, compliance leaders, and organizations deploying AI in high-impact environments.
Priority Frameworks for 2025
Three frameworks at the intersection of AI governance, cybersecurity, and public-interest accountability, available now for enterprise and institutional use.
AI-Cyber Critical Infrastructure Readiness Framework
A practical readiness model for assessing AI systems that affect cybersecurity, public-interest infrastructure, operational resilience, and high-risk enterprise environments. Covers six readiness domains from governance and accountability through agentic AI controls and incident reporting.
Governing Intelligence Framework
Helps boards, executives, AI governance leaders, risk teams, auditors, and public-interest institutions evaluate whether AI systems are legitimate, human-centered, controlled, and accountable, before and after deployment. A structured lens for oversight without requiring technical expertise.
U.S. AI Governance Observatory Framework
A public-interest research model for tracking AI policy, state governance maturity, AI incidents, regulatory developments, and institutional readiness across the United States. The foundation for AIRG Institute's U.S. AI Governance Observatory initiative.
All AIRG Frameworks
Our complete library of governance frameworks, standards-based, audit-ready, and designed for real-world implementation across enterprise and public-sector environments.
U.S. AI Governance Maturity Index
A scoring framework for evaluating how prepared U.S. states are to govern AI responsibly, transparently, and effectively. Supports benchmarking, policy advocacy, and public accountability.
AI Governance Assurance Framework
A standards-based model for helping organizations align AI governance with ISO/IEC 42001, ISO/IEC 27001, NIST AI RMF, NIST CSF, and audit-readiness expectations. Maps controls to evidence requirements.
AI Incident Taxonomy Framework
A structured classification system for AI-related incidents: data leakage, prompt injection, unauthorized agent action, unsafe code generation, hallucinated operational guidance, bias-related harm, and AI-enabled cyber abuse.
AI Governance Evidence Framework
A practical evidence model for documenting board oversight, AI inventories, risk assessments, control testing, incident records, and audit evidence, supporting internal audits and third-party assessments.
Designed for Leaders Governing AI at Scale
Boards & Executives
Oversight tools and risk appetite frameworks that translate AI complexity into board-level accountability.
Cybersecurity Teams
Controls and readiness assessments for AI systems affecting security posture, attack surface, and operational resilience.
Compliance & Audit Leaders
Evidence frameworks and control mapping tools aligned to ISO/IEC 42001, ISO/IEC 27001, and NIST AI RMF.
Public Agencies
Procurement guidance, transparency models, and accountability structures for government AI deployment.
Researchers & Policy Teams
Observation and tracking models for AI policy, governance maturity, incidents, and regulatory developments.