Demonstration · not a client result
Fractional Chief AI Officer what the deliverable looks like
The structure of the deliverable for fractional Chief AI Officer, how it is produced and how you accept it, with a live specimen generated from the matching free tool’s worked example. Synthetic or permitted data only.
What this page isDemonstration
- Practice
- 04 AI governance & assurance
- The deliverable
- 4 sectionsProduced in 5 stages, each with a review point
- Data
- Synthetic or permittedNot a client result
Demonstration of methodSynthetic or permitted data.Not a client result.
The deliverable, section by section.
What you receive, and what each part is for.
AI portfolio view
Every initiative, its owner, value and risk.
DemonstrationMonthly decision session
Prioritisation and approvals with leadership.
DemonstrationGovernance cadence
Policies, reviews and controls kept current.
DemonstrationBoard reporting
A concise AI section for board meetings.
DemonstrationA live specimen.
Generated from the worked example in AI inventory template: synthetic data, real method. Change the inputs in the tool to see your own.
Demonstration · synthetic data · not a client result
Review queue, highest priority first
- 01Screening job applicationsHigh priority · score 11 of 14 · Personal data · decides about people · not reviewedOwner: none. Last reviewed: never.
- 02Beneficiary helpline assistantHigh priority · score 10 of 14 · Sensitive personal data · informs decisions · sampledOwner: Operations manager. Last reviewed: 11 Feb 2025.
- 03Translating field notesMedium priority · score 6 of 14 · Personal data · drafts or assists · sampledOwner: M&E officer. Last reviewed: 1 Jul 2026.
- 04Drafting donor reportsLow priority · score 3 of 14 · Internal, not personal · drafts or assists · always reviewedOwner: Programme lead. Last reviewed: 20 May 2026.
Oversight gaps
- Gap: “Screening job applications” has no owner.Every AI use needs one accountable person.
- Gap: “Screening job applications” decides about people without human review.Add meaningful human review before outcomes affect anyone.
- Check: “Screening job applications” has never been reviewed.
- Check: “Beneficiary helpline assistant” processes sensitive data with partial review.
- Check: “Beneficiary helpline assistant” was last reviewed over a year ago.
The priority score orders your reviews. It is not a legal classification or a compliance rating.
How it is produced, and accepted.
Each stage ends in something you review; acceptance is tested against criteria agreed at the start.
- 01
Inventory
Inventory AI initiatives, tools and data.
Review pointInventory of systems and data in scope, confirmed by you.
- 02
Applicability
Assess which obligations and risks apply.
Review pointApplicability findings reviewed before controls are drafted.
- 03
Controls
Set the controls and decision rules.
Review pointControls agreed with the people who will run them.
- 04
Ownership
Name owners and hold them to the cadence.
Review pointOwners named and accepted in writing.
- 05
Review
Review monthly and report to the board.
Review pointReview date set, with what will be checked.
How proof is labelled
- DemonstrationsDemonstrations use synthetic or permitted data.
- Documented experienceDocumented experience is attributed to the organisation that held the work.
- Measured resultsMeasured results are added only once they have been measured; none are shown yet.
What needs to move forward?
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