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COMPEL Body of Knowledge

COMPEL Glossary / GL-24

AI System Classification Register

A formal register that classifies every AI system in scope according to risk tier, autonomy level, data sensitivity, regulatory applicability, and criticality — producing a system-level risk profile that determines which governance controls, review processes, and compliance requirements apply.

What this means in practice

Classification drives the entire governance design for each system.

Context in the COMPEL framework

Produced in the Model stage as the first governance design step. All subsequent Model artifacts — control requirements, human validation rules, explainability requirements — are derived from the classification register.

Where you see this

AI System Classification Register is most commonly referenced when teams work across the Model stage — especially within the Operational Readiness layer . It appears in governance artifacts, assessment instruments, and delivery playbooks wherever COMPEL is operationalized.

Related COMPEL stages

Related domains

Synonyms

AI risk register , system risk classification , AI asset register

Related Terms Network

This diagram shows how AI System Classification Register connects to other concepts in the COMPEL body of knowledge. Each linked node is a term you can explore in turn.

Related terms for AI System Classification Register Network graph showing 3 related glossary terms connected to AI System Classification Register. AI System Clas… Shadow AI … Agent Auto… Control Re…
3 related concepts connected to AI System Classification Register.
Accessible list of related terms
  • Shadow AI Inventory — A structured catalogue of AI tools, models, and automated systems already in use across the organization that were deployed outside formal governance channels.
  • Agent Autonomy Classification — A formal classification of every AI agent in scope according to its autonomy level — from level 0 (no autonomy, human executes) through level 4 (full autonomy, agent executes without human involvement) — with corresponding governance requirements, approval boundaries, and monitoring obligations assigned at each level.
  • Control Requirements Matrix — A comprehensive mapping of every governance control required for each AI system — specifying the control type (preventive, detective, corrective), the risk or policy it addresses, the evidence required to prove effectiveness, the owner, and the testing frequency.

See also

  • Shadow AI Inventory — A structured catalogue of AI tools, models, and automated systems already in use across the organization that were deployed outside formal governance channels.
  • Agent Autonomy Classification — A formal classification of every AI agent in scope according to its autonomy level — from level 0 (no autonomy, human executes) through level 4 (full autonomy, agent executes without human involvement) — with corresponding governance requirements, approval boundaries, and monitoring obligations assigned at each level.
  • Control Requirements Matrix — A comprehensive mapping of every governance control required for each AI system — specifying the control type (preventive, detective, corrective), the risk or policy it addresses, the evidence required to prove effectiveness, the owner, and the testing frequency.

Related Terms

Other glossary terms mentioned in this entry's definition and context.