AI in Medical Devices - Expectations in a Maturing Field

This course provides a structured orientation to the regulatory environment around AI in medical devices, combined with a realistic view of what is expected today and how expectations are evolving. It is designed both for professionals new to the topic and for experienced practitioners who want to update and calibrate their understanding. The scope of this course is AI that is integrated into a medical device or that qualifies as a medical device in its own right. It does not address the use of AI within quality management systems, regulatory processes, or other internal operations.

The course is an expert-led session covering the regulatory landscape, current expectations, and typical pitfalls associated with AI-enabled medical devices. It combines foundational clarity with an up-to-date view of where regulation, standards, and industry practice are heading.

Unlike our customized trainings, this course does not adapt to a specific organization or product. Its purpose is to provide shared understanding, orientation, and a common vocabulary across roles and organizations.

What we cover

The course is structured around three connected areas. Together, they provide both regulatory clarity and a realistic view of implementation.

Regulatory landscape and interpretation

An overview of how the EU AI Act, MDR/IVDR, and FDA expectations relate to each other for AI-enabled medical devices, including where they overlap, where they do not, and where common misinterpretations arise.

Expectations across the AI model and data lifecycle

A structured view of what regulators and standards expect regarding intended purpose and claims, data governance, development evidence, risk management for AI, supplier and tool control, and post-market performance monitoring.

Typical pitfalls and organizational realities

A discussion of recurring misconceptions, where standards help and where they mislead, what "good" looks like in practice, and how expectations are likely to evolve over the coming years.

Concrete examples and typical situations from the medical device industry are used throughout the seminar to illustrate the concepts.

Course Tutor

Lukas Block is a Senior Consultant in Medical Devices with more than 10 years of experience advising manufacturers on how to build, document and maintain compliant products and QMS processes. He is known for bridging regulatory expectations with engineering reality, especially where multiple standards, stakeholders, and evidence streams intersect. Lukas supports both delivery (documents, processes, remediation) and decision-making (trade-offs, rationale, defensible positions), with an emphasis on consistency across the lifecycle.

His expertise includes international regulatory and quality strategy with a primary focus on EU and U.S. frameworks, complemented by experience across additional global markets. He brings comprehensive QMS expertise covering all aspects and nuances, as well as deep experience in risk management and usability engineering and their integration.

Lukas has a strong focus on software-driven medical devices, including Software as a Medical Device (SaMD), cybersecurity, and the controlled use of AI in regulated products and quality systems.

Lukas holds a Master of Science in Biomedical Engineering from the University of Applied Sciences in Hamburg, Germany.

Areas of Expertise: Regulatory Affairs, Software in Medical Devices, AI in Medical Devices, Risk Management, Quality Management, and Strategic Consulting.