Section 01 · Operating Model
Federated development. Central oversight.
This framework assumes a federated AI development environment, meaning distributed across business units (not federated learning). Product teams design, build, and integrate AI systems. A central platform team provides infrastructure, tooling, and shared controls. Enterprise security, risk, and compliance functions provide governance oversight.
Anti-Pattern
AI governance should not require new bureaucratic layers to be effective. It should integrate into existing enterprise risk and security structures. AI systems are treated as a distinct risk class within existing governance channels, not as a separate discipline.
Where AI oversight lives
Embedded within existing structures. No shadow organization.
Decision rights and ownership
Clear ownership boundaries prevent governance confusion. Three functions, three accountabilities.
Business Unit / Product Teams
Accountable for: Operational outcomes
- AI use case definition
- Initial risk tier classification
- Threat model development
- Model performance ownership
- Monitoring business impact
Central AI Platform Team
Accountable for: Systemic AI integrity controls
- Secure infrastructure
- Model registry governance
- Version control enforcement
- Logging and telemetry enablement
- Drift detection tooling
- Deployment templates
Security / Risk / Governance
Accountable for: Enterprise-level exposure management
- Tier 3–4 risk tier validation
- Regulatory alignment oversight
- High-risk deployment review
- Vendor AI risk approval
- Escalation governance
- Incident coordination
When to escalate
Not all AI systems require executive oversight. Escalation is triggered when:
Escalation pathways align with existing enterprise incident response and risk reporting structures, not parallel ones.
Governance maturity scaling
Organizations operate at different maturity levels. The framework supports all four without requiring organizational redesign.
Level 1
Embedded Review
AI risk is reviewed within existing security architecture meetings.
Level 2
Structured AI Oversight
Formalized risk tier registry and standardized threat modeling templates.
Level 3
Dedicated AI Risk Committee
High-impact or regulated AI systems reviewed by a specialized governance body.
Level 4
High-Assurance AI Oversight
Continuous monitoring dashboards and executive-level reporting for mission-critical AI systems.