CompliQuest

Course Overview

Developing AI systems under the EU’s AI Act isn’t just a technical challenge; it’s a legal one. This course explains the provider obligations for high-risk AI systems and guides you through each compliance step, from concept to post-market monitoring.

You’ll learn what counts as a high-risk AI system and who qualifies as a provider, then dive into the core responsibilities you must fulfil: implementing a continuous risk management process that identifies and mitigates foreseeable misuse, documenting your system’s design, data, and testing methods in a technical file, establishing a
quality management system that ensures safety and traceability across the lifecycle, and creating an EU Declaration of Conformity that proves compliance with the law. 

Real-life examples demonstrate how to manage risks such as automation bias or user misunderstanding, how to establish an incident log, and why clear instructions for use are essential to ensure deployers operate your system safely.

To simplify compliance, the course includes ready-to-use templates for technical documentation, instructions for use, quality and risk management, and a declaration of conformity. 

By the end of this course, you’ll be able to build AI systems that protect users, satisfy regulators, and maintain market competitiveness, without drowning in
legal jargon.

Who Is This For?

This course is ideal for professionals involved in the development, commercialization, and support of AI systems, including:

1. AI Product & Engineering Teams – Designing systems that meet transparency, safety, and accuracy requirements.
2. Compliance & Risk Officers – Ensuring legal alignment throughout the AI lifecycle.
3. R&D and Innovation Leads – Embedding compliance into early-stage system design and testing.
4. Technical Documentation Specialists – Preparing user instructions, technical files, and conformity declarations.
5. Legal & Regulatory Affairs Teams – Managing provider obligations, liability risks, and regulatory engagement.
6. Quality Assurance & Testing Teams – Validating system performance, robustness, and ongoing compliance.
7. Machine Learning Engineers & Data Scientists – Addressing bias, explainability, and data quality in model development.
8. UX Designers – Designing AI interfaces that support human oversight and user understanding.
9. Customer Success & Implementation Teams – Supporting safe and lawful deployment by clients or users.
10. Sales & Commercial Teams – Understanding the compliance requirements that affect go-to-market strategies.
11. Policy & Ethics Officers – Aligning AI practices with internal values and external regulatory expectations.
12. Post-Market Surveillance Teams – Monitoring real-world use, handling incidents, and updating systems as needed.

Modules

• Provider Obligations under the AI Act - Get a clear overview of your core responsibilities as an AI provider—including compliance with design, documentation, testing, and post-market obligations required under the EU AI Act.
• Technical Documentation: Overview - Gain a clear understanding of the documentation required from AI providers under the EU AI Act, and how it supports compliance across the AI lifecycle.
• Describing Your AI System - Learn how to clearly explain your system’s purpose, architecture, components, and how it is intended to function.
• Documenting Your Design and Development - Record design decisions, training data, testing methods, and development steps to ensure transparency and traceability.
• Monitoring, Functioning, and Control - Document how the system is monitored during operation, how it behaves in real-world use, and how human oversight is applied.
• Instructions for Use - Develop clear, compliant user instructions covering system limitations, required conditions for use, and oversight expectations.
• Your Risk Management System - Set up a process to identify, assess, and reduce potential harms, and keep detailed records throughout development and deployment.
• Your AI Quality Management System - Implement and document procedures that ensure the AI system is consistently developed, tested, and maintained in line with regulatory standards.
• Post-Market Monitoring -Track system performance after release, log incidents, and report serious risks. Ensure your system remains safe and compliant over time.