Purpose
Roles, evidence gates, risk tiers, oversight routines and decision records for enterprise AI governance.
FRAMEWORK
AI Governance Operating Model.
Additional page sections
Roles, evidence gates, risk tiers, oversight routines and decision records for enterprise AI governance.
OPERATING MODEL
Structure.
The framework is organized as a practical model for review, implementation planning and evidence conversations.
Lifecycle stages
Intake, classification, design review, evidence collection, approval, monitoring and change control.
Evidence artifacts
Decision records, control maps, test outputs, vendor evidence, risk notes and monitoring plans.
Controls
Governance, security, data, operational and resilience controls mapped to the framework context.
Failure modes
Misclassification, weak ownership, missing evidence, unmonitored drift, supplier opacity and rollback gaps.
Version history
Framework changes should be tracked through the Method Log and linked to related tools.
RELATED TOOLS
Use the local tools.
These tools convert framework concepts into structured checklists, evidence requests and assessment outputs.
AI Governance Evidence Mapper
Map an AI use case to evidence artifacts required for governance review.
use tool →AI Control Readiness Review
Assess whether an AI initiative has minimum controls before production or wider rollout.
use tool →Standards Crosswalk v2
Map AI, cyber, governance, resilience and post-quantum obligations across major references.
use tool →