AI Governance Policy
A versioned policy draft defining accountable ownership, risk-based approvals, information controls and evidence requirements across the AI lifecycle.
37 min readExplore the thinking
Enterprise AI Governance Framework
A sample lifecycle for connecting AI opportunity, proportionate controls and clear human accountability.
Illustrative sample designframework · 6 min exploration
Illustrative sample content. Source material and role attribution are pending; this is not a claim of delivery or measured results.
- Problem
- AI experimentation can outpace decisions about ownership, acceptable data use and release authority.
- Approach
- Treat governance as a lifecycle: intake, classify, design controls, validate, release and reassess.
- Outcome
- Intended outcome: Clearer accountability and a repeatable route from experimentation to governed use. No measured results supplied.
- My role
- Attribution pending. Personal, leadership and collaborative contributions will be specified when the source artifact is supplied.
THE DESIGN IN DETAIL
How it works.
Governance travels with the use case
Select a stage to see what enters, what changes and which decision must be recorded.
Loading the interactive design…
Go deeper into the assumptions, decisions and controls.
Context
Illustrative design only. This sample is not a record of a deployed system, a completed engagement, or measured results.
Problem
A policy alone does not establish an operating practice. Teams need a clear intake route, review criteria and an owner who can make and revisit decisions.
Design principles
- Match review effort to the context and potential impact.
- Name the person accountable for a release decision.
- Reassess when data, scope or autonomy changes.
Lifecycle approach
The lifecycle links an opportunity brief to a risk review, control plan, evaluation record and release decision. Monitoring feeds the next review rather than ending at launch.
Key decisions
Distinguish an advisory tool from a system that takes action. Establish what a user can approve, what must be escalated and which evidence a reviewer needs.
Roles & accountability
Business ownership, technical ownership and review authority should be explicit. The roles shown are a template and do not assert an existing organizational structure.
Implementation considerations
The companion AI Governance Policy and AI Adoption and Governance Implementation Guideline provide full draft requirements, operating guidance and evidence templates. This lifecycle remains an illustrative framework; company-specific adoption, ownership and approval require the tailoring described in those documents.
Business impact
The intended improvement is more consistent decisions about AI use. No compliance conclusion, certification or measured organizational maturity is asserted.