AI Governance Operating Model
Purpose: Define ownership, gates, workflow, reporting and continuous governance for AI adoption.
Audience: Governance, compliance, security leadership, architecture review boards, AI steering committee.
| Gate | Applies To | Required Review |
|---|---|---|
| Gate 1 | Any AI tool | AI usage and data handling review |
| Gate 2 | AI with sensitive data | DLP, classification and data protection review |
| Gate 3 | Custom AI application | AppSec, prompt injection and runtime review |
| Gate 4 | Agentic AI | Tool, API, approval workflow and privilege review |
| Gate 5 | Vendor AI platform | Sovereignty, third-party processing and procurement review |
| Gate 6 | Production AI | Audit logging, SOC integration and evidence readiness review |
Governance Bodies
| Function | Responsibility |
|---|---|
| AI Product Owner | Define use case, data scope and business justification. |
| Security Architecture | Review AI design, controls, integrations and residual risk. |
| GRC / Compliance | Validate policy, regulatory, audit and sovereignty requirements. |
| Data Protection / DLP | Validate data classification and leakage controls. |
| AppSec / DevSecOps | Validate custom AI application and AI-assisted development controls. |
| SOC | Validate alerting, logging, investigation and monitoring. |
| Procurement / Legal | Validate vendor terms, data processing, residency and contractual controls. |
Continuous Governance Metrics
- Number of approved AI tools.
- Number of unapproved AI tools detected.
- AI prompt/file policy violations.
- AI coding assistant usage and detections.
- Custom AI apps reviewed.
- Agentic AI workflows approved.
- Open AI risks and exceptions.
- Vendor sovereignty validations completed.
- SOC alerts and incidents related to AI usage.