Digitalising Regulatory Affairs and Quality Management in regulated industries with artificial intelligence. Practical and drawn from my own experience, for Heads of RA and decision-makers who want to prepare their teams for new technologies and see results quickly.
Mission Critical AI is AI for tasks where "roughly right" is not good enough. The information is complex, yet the results must be precise, traceable and repeatable, as close to deterministic as possible. That applies to medical devices and pharma just as much as to defence, automotive, aviation, critical infrastructure and mechanical engineering. The underlying procedures are very similar, so methods and experience carry over from one industry to the next.
For decades, Regulatory Affairs has been document-driven: technical documentation, declarations of conformity, QM records, all as files, all started again from scratch with every change. Data-driven models are changing what is possible. Combined with AI, they become a clear competitive advantage.
Invest in a document system today and you will have a tidy archive tomorrow. Invest in a data model and you will have a platform that scales with AI. Documents then become just one possible output. The effort is the same; the result is not.
Tool-neutral where it makes sense, within your organisation's own systems and accountable for the result.
Build the requirements of the EU AI Act into your existing ISO 13485 system and technical documentation instead of creating parallel structures.
Move Regulatory Affairs and Quality Management from file shares to structured data with traceability and history. Start with one product family, not everything at once.
RA teams learn to build AI agents themselves and to use them safely and effectively. Where needed, I take responsibility as interim or project lead until the agreed result is achieved.
Head of AI Transition, Regulatory Affairs & Cross-Industry Compliance
For more than twenty years I have worked at the intersection of digitalisation, innovation and regulated products. At BSH Home Appliances I developed global IoT, cloud and augmented reality initiatives and, as co-founder and CTO of WeWash, took a connected product from my own idea through VDE approval to market launch (Bosch Innovation Award 2017).
At Carl Zeiss Meditec, as Head of Regulatory & Clinical Affairs, I was responsible for the global regulatory pathways for Software as a Medical Device (SaMD) and AI functions. I followed the EU AI Act there from its first drafts and anchored it early in the existing ISO 13485 system.
Today I am Head of AI Transition at CertHub, delivering data-model-driven transition projects at medical device manufacturers and in other industries.
As a freelance trainer, I teach RA teams to work with AI agents, mostly with Microsoft Copilot, Copilot Studio and GitHub Copilot.
I also lead AI Act integration projects. My focus: from document to data model, and with AI to greater efficiency.
Where I recently spoke about data models, AI agents and Regulatory Affairs.
Why agents need deterministic data with traceability and history
Routes to a regulatory data model, MDR and IVDR paths compared
Each episode takes on one concern or misconception from everyday RA work: factual, product-neutral, in under a minute. Published on LinkedIn.
Migration strategy, data models, the AI Act or AI-supported Regulatory Affairs: I look forward to a professional and pleasant exchange.
Send an emailcontact@missioncriticalai.eu