World Model Readiness
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Governance & Compliance

Module · The board approves what it cannot question

The Board AI Literacy Check

A board cannot govern what it does not understand, yet most approve AI budgets and strategies on faith. This module tests whether your board can exercise real oversight: whether it has been trained, asks the hard questions, has set a risk appetite, sees unfiltered information, and can still say no.

Question 1 of 5 · The board is trained

Has your board had any AI training beyond a vendor demo?

A vendor pitch teaches you what to buy, not how to govern. Directors need enough grounding to judge a proposal, which is a different thing from knowing how the model works.

Question 2 of 5 · It asks hard questions

When AI is presented, does the board ask about risks, not just returns?

A board that only interrogates the upside prices half the decision. The governing questions are what could go wrong, who is accountable, and how anyone would know in time.

Question 3 of 5 · Risk appetite is set

Has the board defined how much AI risk the company is willing to take?

Without a written appetite, every AI decision is argued from first principles and won by whoever pitches hardest. The appetite is the line management should know before it asks.

Question 4 of 5 · Information is unfiltered

Does the board see AI performance and incidents directly, or only what management chooses to show?

A curated deck smooths over exactly the signals a board needs. Direct access to metrics and incident logs is what separates oversight from ratification.

Question 5 of 5 · It can say no

Could your board reject an AI initiative that management strongly backs?

A board that cannot decline is a signature, not a check. Independence is only real once it has been exercised at least once against a proposal with momentum.

For the statistics · one click each

Three questions for the public picture

These do not affect your score. They feed the anonymised, aggregated statistics; groups under 8 respondents are never shown.

Has your board received any AI-specific training?

None
Informal, self-directed
One formal session
Ongoing education
Not sure

How often is AI a formal item on the board agenda?

Never
Ad hoc, when it comes up
A few times a year
Every meeting
Not sure

Does your board have independent AI expertise?

No one with AI depth
One director with expertise
An external advisor
A dedicated committee
Not sure

Your context

Used to calibrate the report. Company size and sector remain in the anonymized dataset; your email does not.

What the five levels look like

Every dimension in this assessment is scored 1 to 5. This is what the levels mean, dimension by dimension. The graded report diagnoses where your own answers land and what to do about it.

The board is trained

  1. 1None
  2. 2One vendor pitch
  3. 3A single briefing
  4. 4Structured session
  5. 5Ongoing education

At the low end: A vendor demo is marketing, not education. Commission one independent briefing on what AI can and cannot do for your business, pitched at directors, not engineers. What good looks like: Ongoing board education is rare and valuable. Keep it independent of the vendors and executives whose proposals the board must judge.

It asks hard questions

  1. 1Rubber-stamps
  2. 2Asks about cost only
  3. 3Occasional challenge
  4. 4Probes risks
  5. 5Structured scrutiny

At the low end: A board that only asks about returns approves risk it never priced. Add three standing questions to every AI proposal: what could go wrong, who is accountable, how would we know. What good looks like: Structured risk scrutiny is genuine governance. Capture the questions in a checklist so the discipline survives a change of chair.

Risk appetite is set

  1. 1Never discussed
  2. 2Vague sense
  3. 3Discussed, unwritten
  4. 4Written appetite
  5. 5Appetite, with limits

At the low end: Without a defined appetite, every AI decision is argued from scratch. Have the board write one paragraph: how much autonomy, error, and exposure it will accept, and where it will not. What good looks like: A written appetite with limits is what lets the board delegate safely. Revisit it as your AI footprint grows; last year's line may be this year's constraint.

Information is unfiltered

  1. 1Management-filtered
  2. 2Good news only
  3. 3Summary reports
  4. 4Regular metrics
  5. 5Direct + independent

At the low end: A board that sees only what management curates cannot govern it. Insist on direct access to AI performance metrics and incident logs, not just the deck. What good looks like: Direct plus independent information flow is the mature state. Guard it: the pressure to filter grows precisely when the news gets bad.

It can say no

  1. 1In name only
  2. 2Defers to management
  3. 3Rarely pushes back
  4. 4Has said no
  5. 5Independent by design

At the low end: A board that cannot say no is a signature, not a check. Establish that AI proposals can be declined, and demonstrate it once; precedent creates permission. What good looks like: Independent judgment by design is real oversight. Protect it by keeping at least one voice free of management and vendor influence.