Governance Framework & Policy Matrix
Governance Framework
Area | What It Covers | Example Practices |
Ownership & Roles | Who is responsible for AI policies, decisions, and updates | Assign an AI Governance Lead, set up a cross-functional task force |
Policy & Usage Rules | What is allowed, what’s restricted, and what needs review | Red / Yellow / Green matrix for tools, data, and use cases |
Tooling & Access | Which AI tools are approved and how people gain access | List of approved tools; request process for new tools or licenses |
Data Security & Risk | Rules for handling sensitive or client-related data in AI systems | Pseudonymization rules; “no copy-paste of client data into external tools” |
Review & Accountability | When AI outputs need human review or approval | “Client-facing outputs must be reviewed by project lead” |
Training & Enablement | How teams are educated on responsible and effective AI use | First 5 safe tasks to try, role-based onboarding, prompt libraries |
Monitoring & Feedback | How AI usage is tracked, reviewed, and continuously improved | Quarterly usage reviews, incident reporting, feedback loop |
Escalation & Exceptions | Where to go if rules are unclear or exceptions are needed | Slack channel or form for AI questions, documented escalation path |
Ethical & Legal Guardrails | How ethical principles and compliance standards are integrated | Fairness, transparency, human-in-the-loop, GDPR, client contract alignment |
Change Management | How updates to the framework are rolled out and communicated | Version control, stakeholder briefings, visible changelogs in Confluence |
Policy Matrix
Category | Green – Safe to Use | Yellow – Use with Caution / Review Needed | Red – Not Allowed |
AI Tools | Approved internal AI tools (e.g. Microsoft Copilot, Notion AI) | Unvetted external tools used internally for drafts | Tools that store data externally without compliance (e.g. ChatGPT web, Gemini) |
Use Cases | Internal drafts, brainstorming, formatting, text clean-up | Client-facing content if reviewed by human | AI-generated final outputs sent to clients without review |
Data Types | Public/internal non-sensitive documentation | Anonymized or pseudonymized client data | Raw client data, financials, personal identifiers (PII) |
Project Context | Internal documentation, team templates, backlog item summaries | Risk logs, project reports, stakeholder emails (with review) | Legal statements, contractual content, compliance-critical deliverables |
User Skill Level | Trained users using prompt templates | New users with oversight from AI champion | Untrained users using AI for sensitive tasks |
Approval Needs | None – within green scope | Needs peer review or sign-off before sharing externally | Blocked unless reviewed by governance lead or security |
Tool Access | Pre-approved tools with SSO and audit trail | Trial tools in sandbox environment with logged testing | Personal AI tool accounts connected to work platforms |