AIAC-10 · Executive track
For directors and executives accountable for AI risk. Not how to build AI — how to challenge a decision about it, and what to require before approving one.
§ 1 — Intended candidates
Non-executive directors, audit and risk committee members, CROs, CISOs, general counsel, and executive teams.
§ 2 — Examination domains
Domain weightings are published with the full syllabus ahead of the first cohort.
Separating decisions a board must take from those it should require evidence about, and those it should leave alone.
Interrogating what is presented — and identifying what has been left out of it.
Expressing appetite in terms that constrain a deployment decision rather than describing a technology.
The specific challenges that reveal unowned risk, undocumented deployments, and unmonitored vendor models.
Who answers, on what record, and what the board needed to have asked beforehand.
§ 3 — How to certify
Preparation is optional. Choose whichever route suits how you already work — the examination, the fee, and the marking standard are the same either way.
Register and sit the examination. Suitable for practitioners already working in assurance who want the credential without preparation.
The same examination, bundled with self-paced preparation mapped to the syllabus. Taking it confers no advantage in marking and is never required.
Preparation is optional. The examination is available at the same fee and marked to the same standard whether or not preparation was purchased, and assessors are not told which route a candidate took. How we manage this conflict.
§ 4 — Assessment
Scenario-based examination requiring challenge of a supplied AI risk paper: what is missing from it, and a reasoned approve-or-defer decision.
Successful candidates receive a credential with a unique identifier that any employer can check against the public record. See credential verification.
Curriculum mapping indicates alignment of learning content with published frameworks. It does not constitute endorsement by, or certification under, any standards organization or regulator.
§ 5 — Further reading
Producing credible, independently reviewable evidence that an AI system works as intended — and how that differs from governance and compliance.
Three terms used interchangeably that mean different things, have different outputs, and require different independence. A practitioner-level distinction.