For Boards & Committees
AI Decision Records for Boards & Committees
PreMetric helps boards, audit committees, and executive governance bodies evaluate material AI initiatives before approval, deployment, capital commitment, or institutional exposure.
Value case
Business case, projected outcome
Risk exposure
Capital, operational, reputational
Accountability
Governance structure, oversight
Oversight conditions
Approval triggers, reassessment
Board-ready decision record
Institutional defensibility
Point-in-time review. Produces a structured decision record.
Approval without a complete decision record
Boards and committees are increasingly being asked to approve AI initiatives without a complete decision record. Technical teams may present capability, business units may present projected value, and vendors may present implementation pathways — but governance bodies still need to understand whether the decision itself is defensible.
AI approval is no longer only a technical or operational question. For boards, audit committees, risk committees, executive committees, and governance stakeholders, it is a governance, accountability, capital allocation, and oversight question. The organisation's exposure does not begin at deployment — it begins at the point of approval.
A board or committee that approves a material AI initiative without a structured decision record accepts accountability for assumptions it may not have examined and risks it may not have formally considered. When something goes wrong — financially, operationally, or reputationally — the adequacy of the pre-approval process will be the first thing reviewed.
PreMetric helps create a defensible pre-deployment decision record before AI exposure becomes embedded in the organisation's operations, capital position, or regulatory obligations.
What PreMetric provides
PreMetric provides a structured AI Decision Review for board and committee contexts. The review is bounded, documented, and concluded with a clear recommendation. It applies PreMetric's pre-deployment AI decision infrastructure to the specific governance question before approval is given.
The review is designed to give governance bodies clarity on the dimensions that matter most to institutional defensibility — not technical performance metrics or vendor capability assessments.
Decision rationale
The documented reasoning behind the recommendation to approve, modify, pause, or stop.
Projected value
The business case and whether the assumed value is supported by a credible evidence chain.
Capital exposure
The capital at risk if deployment assumptions prove incorrect, incomplete, or premature.
Deployment assumptions
The conditions that must hold for the initiative to deliver the projected outcome.
Governance readiness
Whether the organisation has the oversight structures, accountability assignment, and documentation required for responsible deployment.
Accountability boundaries
Who is responsible for deployment decisions, ongoing oversight, exception handling, and reassessment.
Risk acceptance
The risks being accepted at the point of approval and the basis on which they are accepted.
Evidence gaps
What is not yet known, tested, or documented, and how material those gaps are to the decision.
Oversight conditions
The monitoring, reporting, and escalation conditions that should attach to approval.
Reassessment triggers
The events, thresholds, or observations that should require the decision to be revisited.
Questions PreMetric helps answer
Each review is structured around the questions that matter to governance bodies — not technical benchmarks or vendor assessments. These are the questions that boards, audit committees, general counsel, CFOs, and chief risk officers need answered before approval is given.
Governance decision questions
- —Is the AI initiative ready for approval?
- —Is the business case supported by sufficient evidence?
- —What assumptions must hold for the initiative to succeed?
- —What risks are being accepted by the organisation?
- —Who is accountable for deployment, oversight, and reassessment?
- —What conditions should attach to approval?
- —What would require the decision to be modified, paused, or revisited?
- —Can the decision withstand later scrutiny from regulators, auditors, investors, employees, customers, or counterparties?
When to use it
An AI Decision Review for boards and committees is most valuable at the point of governance — before approval is given, before capital is committed, and before the organisation's exposure becomes difficult to unwind.
- —Before a board or audit committee approves a material AI initiative
- —Before capital is committed to AI deployment
- —Before AI enters a regulated or high-accountability workflow
- —Before approving an AI vendor or procurement decision
- —Before expanding an existing AI initiative into a new scope or market
- —When directors or executives require a clearer evidence chain
- —When an AI initiative may create reputational, regulatory, operational, or financial exposure
Defined outputs
Every review concludes with a defined set of structured outputs. These are institutional records — not slide decks, not advisory summaries. They are designed to be used by boards, audit committees, executive governance bodies, general counsel, and external reviewers.
Board-ready AI decision record
A structured record of the review, findings, and recommendation — suitable for board, committee, or audit use.
AI Decision Review memo
A concise, documented summary of the assessment and its conclusion, suitable for distribution to directors and executives.
Governance and accountability assessment
Evaluation of whether oversight structures, accountability assignment, and documentation meet the standard required for defensible approval.
Capital exposure analysis
Assessment of the capital at risk if deployment assumptions fail or the business case does not materialise.
Deployment assumption review
Structured examination of the assumptions underpinning the AI initiative and where those assumptions are untested or insufficiently evidenced.
Evidence-chain summary
The documented evidence chain supporting or qualifying the value claims and deployment readiness of the initiative.
Approval conditions and reassessment triggers
Defined conditions that should attach to approval, and the events or thresholds that should require the decision to be revisited.
Proceed / modify / pause / stop recommendation
A documented recommendation on whether the initiative is ready for approval, requires modification, should be paused, or should not proceed.
Before the decision is made
The time to create a defensible AI decision record is before approval is given — not after a deployment has failed, a regulatory inquiry has begun, or an audit committee has asked why the risk was not adequately assessed.
PreMetric works with boards, audit committees, risk committees, executive committees, general counsel, CFOs, and chief risk officers where a material AI decision requires a structured record before approval, deployment, or capital commitment.
This is not a continuous governance relationship or a monitoring service. It is a structured, bounded review triggered by a defined governance decision — producing documented outputs that can be used by boards, committees, auditors, regulators, and governance bodies.