AI governance should be implemented as an operating system, not a policy PDF. In regulated environments, governance fails when controls are disconnected from architecture and delivery cadence.
What changes in regulated environments
Compared with standard digital products, regulated AI systems introduce three additional requirements:
- Traceability: teams must be able to explain what data, model version, and prompt/retrieval configuration produced a decision.
- Risk-tiered controls: higher-impact workflows need stronger pre-release and post-release checks.
- Human accountability: approval rights and escalation paths must be explicit.
A practical governance stack
1. Intake and risk classification
Create a mandatory intake step before build starts. Every use case gets a risk tier and required controls list.
- Tier 1 (low impact): standard QA + monitoring.
- Tier 2 (medium impact): expanded testing + domain review.
- Tier 3 (high impact): independent validation, sign-off workflow, and stronger logging retention.
2. Design controls at architecture stage
Governance must be embedded in design artifacts:
- data lineage model
- model/prompt versioning strategy
- fallback and rollback behaviour
- access and approval boundaries
If controls are deferred until UAT, governance becomes a release blocker.
3. Pre-release gates
Add release gates in CI/CD with objective criteria:
- quality thresholds against agreed evaluation sets
- policy and safety checks for disallowed outputs
- documentation completeness checks
4. Runtime controls
After deployment, governance shifts to operations:
- drift and incident alerting
- sampled human review
- periodic model/prompt revalidation
- controlled change windows for high-risk workloads
Common failure modes
- Policy-heavy, telemetry-light: strong policy language but missing runtime evidence.
- Single-signoff theater: one approval event treated as permanent compliance.
- No ownership map: unclear who owns model quality, business impact, and incident response.
What good looks like in 90 days
- Week 1-3: governance intake, risk tiers, and minimum control baseline.
- Week 4-8: CI/CD gates + runtime observability for one priority workflow.
- Week 9-12: operating cadence (review board, incident drills, and monthly revalidation).
This sequence gives teams a governance baseline without stalling delivery.