AI Assurance Institute
CQMSM - Certified Quality Management System Manager
(High-Risk AI Systems)
Candidate's Guide

Copyright 2026 - AI Assurance Institute. All rights reserved.

Table of Contents

1. Introduction to the CQMSM Certification

The Certified Quality Management System Manager (CQMSM) credential is awarded to professionals who demonstrate mastery in establishing, implementing, maintaining, and continually improving a Quality Management System (QMS) for high-risk AI systems in compliance with the EU Artificial Intelligence Act (Regulation (EU) 2024/1689) and the harmonized standard EN 18286:2025.

This certification validates expertise in protecting health, safety, and fundamental rights throughout the AI system lifecycle, from inception to post-market monitoring. It is designed for individuals responsible for QMS ownership in organizations developing, deploying, or overseeing high-risk AI systems (as classified under EU AI Act Annex III).

The CQMSM is offered by the AI Assurance Institute to meet the growing demand for qualified professionals capable of operationalizing regulatory compliance in AI governance.

2. Purpose and Value of the Certification

The rapid adoption of high-risk AI systems in sectors such as healthcare, finance, justice, and critical infrastructure has created an urgent need for robust quality management frameworks. The EU AI Act mandates providers to implement QMS processes that ensure conformity with essential requirements, including risk management, data governance, transparency, human oversight, and post-market monitoring.

The CQMSM certification:

• Validates comprehensive knowledge of EN 18286 and EU AI Act requirements.
• Demonstrates ability to integrate QMS with technical AI development and deployment.
• Provides evidence of competence in lifecycle compliance, audit preparation, and regulatory interaction.
• Enhances professional credibility with employers, regulators, and notified bodies.

Certified holders are equipped to serve as authoritative QMS owners, leading cross-functional teams and ensuring presumption of conformity under the EU AI Act.

3. Eligibility Requirements

Candidates should meet one of the following combinations of education and experience:

• Minimum 2 years of professional experience in quality management, compliance, or AI governance, with at least 2 years involving regulated systems (e.g., medical devices, aerospace, or high-risk AI).
• Bachelor degree or higher in a relevant field (e.g., engineering, computer science, quality management, law).

All candidates must attest to adherence to the CQMSM Code of Ethics and provide evidence of continuing professional development (e.g., training in EU AI Act, EN 18286 and other relevant harmonised standards).

4. Examination Overview

The CQMSM examination is a 3-hour, 100-question multiple-choice test delivered online via proctored platform.

Passing Score: 70% (70/100 correct answers)

Languages: English

Retake Policy: One free retake within 12 months; subsequent attempts require new application fee.

The exam tests application of knowledge rather than rote memorization, including scenario-based questions requiring analysis of QMS processes, risk scenarios, and regulatory decisions.

5. Body of Knowledge and Domains

The CQMSM Body of Knowledge is structured around the clauses of the EN 18286 Quality Management System draft standard, with emphasis on practical implementation as detailed in the Quality Management System Manager role description. The examination allocates questions approximately as follows:

Domain 1: Context, Scope, and Regulatory Strategy (15%)

Candidates must demonstrate understanding of establishing the QMS foundation per Clause 4. This includes:

• Analyzing organizational context and interested parties' needs/expectations (Clause 4.1), incorporating feedback on fundamental rights (Annex A).
• Identifying and systematically reviewing regulatory requirements throughout the lifecycle (Clause 4.2), integrating them into the compliance strategy.
• Determining QMS scope, boundaries, and alignment with intended purposes (Clause 4.3), ensuring coverage of high-risk systems per EU AI Act Annex III.
• Developing and maintaining the strategy for regulatory compliance (Clause 4.4), addressing QMS requirements, essential requirements, post-market monitoring, serious incidents, and data management.
• Selecting measures for essential requirements compliance (Clause 4.4.3), documenting uncovered requirements with justification and evidence.
• Maintaining documented information for the QMS (Clause 4.5).

Domain 2: Leadership, Policy, and Roles (15%)

Candidates must show proficiency in management responsibility per Clause 5, including ensuring resource availability, establishing quality policy, and assigning roles, responsibilities, and authorities with traceability to policy and objectives.

Domain 3: Planning - Risks, Opportunities, and Objectives (15%)

Candidates must apply planning requirements per Clause 6, including determining risks/opportunities, planning proportional actions, and establishing verifiable quality objectives aligned with policy and regulations.

Domain 4: Support - Resources, Competence, and Communication (15%)

Candidates must understand support elements per Clause 7, including determining and providing resources, ensuring competence, and managing internal/external communications, including regulatory communications.

Domain 5: Operation - Design, Development, and Controls (20%)

Candidates must master operational requirements per Clause 8, including establishing the risk management system, defining lifecycle stages, managing data lifecycle, preparing technical documentation, and ensuring verification and validation.

Domain 6: Performance Evaluation and Improvement (20%)

Candidates must apply evaluation and improvement per Clauses 9-10, including deployment/version management, supply chain controls, change management, post-market monitoring, serious incident reporting, nonconformity management, and continual improvement.

6. Examination Format and Scoring

• 150 multiple-choice questions (4 options, single correct answer).
• Scenario-based questions (60-70%) requiring application of EN 18286 clauses.
• No negative marking.
• Results provided within 5 business days.

7. Preparation Resources

Recommended study materials:

• EU AI Act full text and official explanatory documents.
• EN 18286 (available through national standards bodies).
• AI Assurance Institute QMS Manager Role Description and Quality Manual (provided upon registration).
• AI-Literacy Matrix and COBIT mappings for governance context.

Preparation courses:

• AI Assurance Institute 5-day CQMSM Prep Course (virtual/in-person).
• Self-paced e-learning modules covering all domains.

Practice exams available through candidate portal.

8. Application Process

1. Register online.
2. Pay examination fee (Euro 200 standard fee).
3. Receive registration confirmation within 3 business days.
4. Schedule exam through proctored platform.
5. Upon passing, receive digital certificate and listing in CQMSM registry.

9. Code of Ethics and Professional Conduct

CQMSM holders shall:

• Act with integrity and objectivity.
• Maintain competence through continuing education.
• Comply with all applicable laws and regulations.
• Protect confidential information.
• Report serious violations of the EU AI Act or professional standards.

10. Recertification and Maintenance

Certification valid for 3 years. Recertify by:

• Earning 60 Continuing Professional Education (CPE) credits, OR
• Retaking the examination.

Credits awarded for training, teaching, publications, or professional contributions related to AI Quality Management Systems.

11. Contact Information

AI Assurance Institute Certification Office
Email: certification@aiassurance.institute
Website: www.aiassurance.institute
For examination: https://aiqms.certification.services

This guide equips candidates with the information needed to achieve CQMSM certification and demonstrate leadership in AI quality management system compliance. Success in the examination confirms readiness to serve as an authoritative QMS owner for high-risk AI systems under the EU AI Act framework.