Certified AI Assurance Employment Foundation

Who this certification is for

The competency standard for assuring AI used in hiring and employment decisions — the domain where independent bias auditing is increasingly required by law and no settled credential yet defines the competence.

Who it is for. HR-technology assurance, employment counsel, compliance professionals, and the independent auditors who assess automated employment decision tools.

Prerequisites

No formal prerequisites. Candidates are expected to have professional experience in an HR, legal, risk, or audit function.

Status

Open for registrationOpen for registration · Examinations from October 2026

This is the Foundation grade of the AI Assurance — Employment family — Practitioner and Fellow follow it.

What the examination covers

The examination is mapped to New York City Local Law 144, the EEOC selection-rate guidance, and the employment provisions of EU AI Act Annex III. Weightings are indicative until each syllabus issues.

1. 01

   The legal landscape for employment AI25%

   NYC Local Law 144, Title VII, and state laws including Colorado and Illinois — what each requires of an automated employment decision tool.

2. 02

   Disparate-impact fundamentals25%

   Selection rates, the four-fifths rule, and adverse-impact analysis — and what a disparity finding does and does not establish.

3. 03

   EU AI Act employment scope15%

   Annex III high-risk classification of employment systems and the obligations that follow.

4. 04

   Bias-audit mechanics25%

   The data, the methodology, and what an independent audit must evidence to stand.

5. 05

   Notice, transparency, and records10%

   Candidate notice, transparency obligations, and the record-keeping that makes an audit checkable.

Curriculum mapping indicates alignment of learning content with published frameworks. It does not constitute endorsement by, or certification under, any standards organisation or regulator.

What preparation is anchored to

Anchored to the named statutes and to published bias-audit practice. Candidates prepare independently against the published materials.

The Council certifies individuals — it sells no preparation of any kind, and how a candidate prepared is never visible to an assessor. How impartiality is protected.

One route: the examination

The full rules — registration, identity verification, examination conduct, adjustments, retakes — are in the candidate handbook.

Fees and the pass standard are fixed in the scheme rules and confirmed ahead of the October 2026 examination window.

How candidates are assessed

Examination centred on a supplied hiring or workforce AI deployment, requiring the applicable obligations and a defensible bias-audit approach.

Every script is marked twice — an AI assessor first and provisional, an independent human assessor second and final. The credential carries a unique identifier any employer can check on the public register.

Questions about this certification

What are the prerequisites?

No formal prerequisites. Candidates are expected to have professional experience in an HR, legal, risk, or audit function.

When can I sit the examination?

Registration is open now through the candidate portal; examination sittings run from the October 2026 window and are scheduled at booking.

How is the examination marked?

Every script is marked twice, in a fixed order: an AI assessor first, producing a provisional mark, and an independent human assessor second, whose determination is final on any divergence. No result is issued on automated marking alone, and no adverse decision — a fail, a suspension, a withdrawal — is ever made without a human assessor.

How long is the credential valid?

2 years from the date of issue, recorded on the public register. The term and what follows it are set out in the revalidation policy.

Scheme-wide questions are answered on the FAQ and in the candidate handbook.

Background reading

• What is AI assurance? A practitioner's definition

  Producing credible, independently reviewable evidence that an AI system works as intended — and how that differs from governance and compliance.

• AI assurance vs AI audit vs AI risk assessment

  Three terms used interchangeably that mean different things, have different outputs, and require different independence. A practitioner-level distinction.

• How to build an AI risk profile for a deployment

  A seven-step method for producing a risk profile a sceptical reader can challenge, with the failure mode at each step and what the finished artefact contains.