Certification tracks

Three tracks, one standard of evidence

Council certifications are assessment-based and scenario-driven. Candidates are not asked to recall a framework; they are asked to apply one to a deployment they have never seen before.

§ 1 — The tracks

AIAC-01· Foundation

Certified AI Assurance Practitioner

The baseline credential for professionals entering AI assurance: risk identification, testing concepts, governance frameworks, and evidence-based assessment across any industry.

Examination: 3 hours
Delivery: Remote, proctored
Valid for: 3 years
Level: Foundation

Intended for: Risk, audit, compliance, data science, and engineering professionals taking on AI assurance responsibilities for the first time.
Assessment: Scenario-based examination. Candidates produce a structured AI risk profile for a supplied deployment context, prioritize applicable requirements, and defend an implementation plan.

In development · First cohort October 2026Track detail

AIAC-02· Industrial

AI Risk & Quality — Industrial Systems

For engineers and quality professionals deploying AI in robotics, manufacturing, and industrial automation, where system failures carry physical and operational consequences.

Examination: 3.5 hours
Delivery: Remote, proctored
Valid for: 3 years
Level: Practitioner

Intended for: Quality engineers, controls and automation engineers, functional safety practitioners, and operations leaders introducing AI into physical systems.
Assessment: Scenario-based examination set in an industrial deployment context, including a risk profile, a monitoring plan, and a qualification evidence package.

In development · First cohort October 2026Track detail

AIAC-03· Financial

AI Assurance for Financial Institutions

For risk, compliance, and audit professionals in regulated financial services, covering model risk, agentic AI oversight, and supervisory expectations for AI deployment.

Examination: 3.5 hours
Delivery: Remote, proctored
Valid for: 3 years
Level: Practitioner

Intended for: Second- and third-line professionals in banks, insurers, and asset managers: model risk, operational risk, compliance, and internal audit.
Assessment: Scenario-based examination set in a regulated financial services context, including a model inventory judgement, a risk profile, and a committee-level reporting summary.

In development · First cohort October 2026Track detail

§ 2 — Standards alignment

What the curricula are mapped to

ISO/IEC 42001: AI management systems — the certifiable standard for organizational AI governance.
NIST AI RMF: The US framework for identifying, measuring, and managing AI risk across the lifecycle.
ISO/IEC 23894: Risk management guidance specific to artificial intelligence systems.
Sector frameworks: Curricula reference applicable sector guidance, including financial-sector AI risk management expectations in the jurisdictions where candidates operate.

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

§ 3 — Enquiries

Cohorts and candidate enquiries

Syllabi and examination standards are published to the launch list ahead of the first cohorts. For organisation-wide certification, see certification for organisations, or write to hello@aiassurancecouncil.org.