A structured, standards-aligned operating model for adopting AI safely at scale — unifying AI governance, data governance, and AI security across the full system lifecycle.
Click any card to see how it shapes the adoption framework. These are the primary references enterprises are expected to align to in 2026.
Govern is the cross-cutting function that feeds Map, Measure, and Manage — applied iteratively across the AI system lifecycle, not as one-time steps.
Leadership establishes AI policy, accountability structures, and risk tolerance before systems are built. Govern is cross-cutting — it informs every other function throughout the lifecycle.
Each phase maps directly to NIST AI RMF functions and layers in the controls required by ISO/IEC 42001, OWASP, MITRE ATLAS, and applicable regulation.
The baseline application-security taxonomy for generative and agentic AI systems. Applied during Phase 3 (Secure by Design) and Phase 4 (Assurance) of the framework.
Every AI use case identified in Phase 2 (Map) should be classified against these four tiers to determine its compliance obligations.
AI agents that process data or drive decisions qualify as "information systems" under NIS2 Article 21 — in-scope entities must fold them into risk management and incident-reporting obligations.
Initial notification to the national CSIRT/authority of a significant incident involving an in-scope AI or information system.
Detailed assessment including severity, indicators of compromise, and initial impact on the AI system or its data.
Root cause, mitigations applied, and cross-border impact where relevant. Management bodies remain personally accountable (Art. 20).
Rate your organization from 1 (Ad Hoc) to 5 (Optimizing) across five pillars to see an overall maturity score, inspired by SANS' AI Security Maturity Model and NIST's Govern function.
ISO/IEC 42001 and NIST's Govern function both require named, accountable ownership — not diffuse responsibility.
Check off what's already in place. This gives a directional readiness score across governance, data, security, and compliance — not a certification.
A phased sequencing so governance, data, and security controls land before AI systems scale in production.