Duration: 1 Full Day | Timings: 9:00 AM - 4:30 PM | Format: Interactive workshop with practical examples.
Course Introduction
EN 18286 is the emerging harmonised European standard that provides detailed guidance on implementing the Quality Management System (QMS) requirements of the EU AI Act (particularly Article 17). This one-day fundamentals course delivers a clear, practical understanding of the standard's structure, intent, and application for organisations developing or deploying high-risk AI systems.
Participants will explore how EN 18286 translates legal obligations into operational reality, with special emphasis on proportionality, risk-based thinking, and the seven essential requirements that form the backbone of conformity assessment.
Course Agenda
Morning Session: Strategic & Legal Context
- The Legal Obligation – Understanding the mandatory nature of QMS requirements under the EU AI Act, timelines for compliance, and the role of EN 18286 in achieving presumption of conformity.
- Intended Purposes – How to correctly define and document the intended purpose of AI systems and why this is foundational to the entire compliance framework.
- Protection vs Compliance – Balancing fundamental rights protection with practical regulatory adherence, including the ethical and legal drivers behind the standard.
- Proportionality – Applying risk-based and proportionate approaches, with special considerations for SMEs, lower-risk applications, and resource-efficient implementation.
Afternoon Session: The Seven Essential Requirements
A deep dive into the seven core pillars of EN 18286 that support conformity assessment:
- The Risk Management System – Iterative risk identification, evaluation, and mitigation across health, safety, and fundamental rights.
- Data and Data Governance – Requirements for data quality, bias management, provenance, and governance aligned with Article 10.
- Technical Documentation – What must be documented, level of detail, and how to maintain it throughout the AI lifecycle.
- Record-Keeping – 10-year retention obligations, traceability, and effective record management systems.
- Transparency and Provision of Information to Deployers – Clear communication obligations and instructions for use.
- Human Oversight – Designing effective human-in-the-loop mechanisms and oversight protocols.
- Accuracy, Robustness, and Cybersecurity – Technical measures for reliable, secure, and resilient AI systems, including handling of adaptive models.
Learning Outcomes
By the end of this course, participants will be able to:
- Clearly explain the purpose, structure, and legal weight of EN 18286 within the EU AI Act framework.
- Understand the seven essential requirements and how they interconnect with broader QMS obligations.
- Apply the principles of proportionality and risk-based thinking to their organisation's AI development processes.
- Differentiate between legal minimum requirements and best-practice implementation.
- Identify gaps in current practices and develop a prioritised roadmap toward EN 18286 alignment.