Governance Framework Implementation
This section covers the implementation of formal governance structures for AI-assisted development as the organization scales beyond pilot teams. Governance is the mechanism that ensures AI-assisted development remains safe, compliant, and aligned with organizational standards even as adoption expands. The governance framework includes approval workflows, review gates, compliance checkpoints, audit mechanisms, and exception handling processes. It operationalizes the security policies established in Phase 1: Baseline Security Policies and prepares the foundation for the Organization-Wide Policy in Phase 3.
Approval Workflows
New Team Onboarding Approval
Every team seeking to adopt AI-assisted development MUST follow a formal approval workflow:
- Request submission — The team's Engineering Manager submits a Team Adoption Request that includes: team composition, project scope, data classification assessment, and risk scoring per Risk Assessment Scaling.
- Security review — The Security Lead reviews the data classification and risk score. Teams working with Restricted data require CISO approval.
- Readiness verification — The Governance Lead verifies that all team members have completed training and signed the Acceptable Use Policy.
- Tool provisioning — Platform Engineering provisions tool access with approved configurations upon all approvals.
- Monitoring activation — Metrics dashboards and audit logging are activated for the new team.
Target turnaround time: 5 business days from request to provisioning for standard-risk teams; 10 business days for elevated-risk teams.
Change Approval Workflow
Changes to AI tool configurations, approved model versions, or governance policies MUST follow a change approval workflow:
| Change Type | Approver(s) | Lead Time |
|---|---|---|
| Tool configuration change | Security Lead + Platform Engineering Lead | 3 business days |
| New model version approval | Security Lead + CISO | 5 business days |
| Policy amendment | Governance Lead + Steering Committee | 10 business days |
| New tool addition | Full assessment per AI Tool Assessment | 4-6 weeks |
| Emergency configuration change | CISO (retroactive Steering Committee review) | Immediate |
Review Gates
Review gates are mandatory checkpoints in the development lifecycle where AI-assisted work is evaluated against governance standards. These gates integrate into the Operating Model Lifecycle and the team's existing SDLC.
Gate 1: Pre-Commit Review
When: Before AI-assisted code is committed to a shared branch. Who: The code author (self-review) and at least one peer reviewer. What is checked:
- AI attribution metadata is present on all AI-assisted code
- No Restricted-classified data is present in the commit
- Code has been reviewed for common AI failure patterns (insecure defaults, logic errors, hallucinated APIs)
- Pre-commit hooks pass (secrets scanning, linting)
Gate 2: Pull Request Review
When: Before a pull request with AI-assisted code is merged. Who: Tech Lead or designated senior reviewer with AI-review training. What is checked:
- All Gate 1 checks verified
- AI-generated code has been tested with both AI-generated and human-written tests
- Security-sensitive code paths identified and reviewed with extra scrutiny
- Code meets the team's style and architecture standards
- No unnecessary complexity or "AI bloat" (over-engineered solutions)
Gate 3: Release Governance Gate
When: Before deployment to production. Who: Release Manager with Governance Lead sign-off for elevated-risk releases. What is checked:
- CI/CD pipeline governance checks passed (see CI/CD Pipeline Integration)
- All Critical and High security findings resolved
- AI usage metrics within expected ranges (no anomalous patterns)
- Release-level risk assessment completed for elevated-risk releases
Compliance Checkpoints
Compliance checkpoints ensure ongoing adherence to governance standards beyond individual review gates.
Weekly Compliance Checks
- Automated: AI tool configuration audit — verify all tool configurations match approved settings
- Automated: Prompt log volume monitoring — flag anomalous usage patterns
- Manual: Random sample review of 5 AI-assisted PRs across all teams by the Governance Lead
Monthly Compliance Reviews
- Governance metrics review — Percentage of PRs with proper AI attribution, gate pass/fail rates, policy violation counts
- Access review — Verify all users with AI tool access are current (no departed employees, no unauthorized access)
- Policy compliance audit — Review any reported violations and their resolution status
Quarterly Compliance Assessments
- Full governance audit — Independent assessment of governance effectiveness, including interviews with team members
- Policy refresh — Review and update policies based on lessons learned and evolving requirements
- Regulatory alignment check — Verify governance remains aligned with applicable regulations
Audit Mechanisms
Audit Trail Requirements
The following events MUST be logged. Retention durations MUST follow the normative Retention & Audit Evidence Policy:
| Event | Data Captured | Retention |
|---|---|---|
| AI tool access provisioned/revoked | User, date, approver, reason | 3 years |
| AI tool prompt (where technically feasible) | Timestamp, user, tool, prompt hash (not content if sensitive) | Prompt metadata: 3 years; content: 90 days default |
| AI-assisted PR merged | PR ID, author, reviewer(s), AI attribution metadata | 3 years |
| Governance gate pass/fail | Gate type, result, evidence, reviewer | 3 years |
| Configuration change | Setting changed, old value, new value, approver | 3 years |
| Policy violation reported | Type, severity, team, resolution | 3 years |
| Exception/waiver granted | Scope, justification, approver, expiration | 3 years after expiry |
Audit Access
- Audit logs MUST be immutable and stored separately from the systems they audit
- Access to audit logs MUST be restricted to Security, Compliance, and Governance roles
- Audit logs MUST be available for regulatory examination upon request
Exception Handling
No governance framework survives contact with reality without an exception process. Exceptions allow teams to deviate from standard governance when justified, while maintaining accountability and traceability.
Exception Categories
| Category | Examples | Approval Level | Maximum Duration |
|---|---|---|---|
| Process exception | Skip a review gate due to emergency hotfix | Tech Lead + Governance Lead | Single instance |
| Configuration exception | Use a non-standard tool configuration for specific use case | Security Lead | 30 days, renewable |
| Policy exception | Deviate from data classification rules for a specific project | CISO | 90 days, renewable |
| Tool exception | Use a non-approved AI tool for evaluation | Security Lead + CISO | 30 days, non-renewable |
Exception Process
- Request — Requestor documents the exception needed, justification, risk assessment, and proposed mitigations
- Review — Appropriate approver reviews the request within 2 business days (1 business day for emergency exceptions)
- Decision — Approve with conditions, deny with explanation, or request additional information
- Documentation — All approved exceptions are recorded in the Exception Register with expiration dates
- Monitoring — Exceptions are reviewed at each monthly compliance review; expired exceptions are closed
- Retrospective — Recurring exceptions of the same type trigger a policy review to determine if the policy should be updated
Exception Register
The Governance Lead MUST maintain an Exception Register that tracks all active exceptions. The register MUST be reviewed at every Steering Committee meeting. An exception rate exceeding 15% of teams indicates a systemic governance issue that MUST trigger a policy review.
This governance framework is designed to be rigorous without being burdensome. As the organization matures through Phase 3, many of these manual processes will become automated, but the governance principles remain constant.