When does a large language model (LLM) become a medical device?
28th August 2025
When does a large language model (LLM) become a medical device?That critical question shaped a series of insightful discussions at our recent expert workshop, part of the Qualification and Risk Classification of LLMs project led by the AI & Digital Health Group at the University of Birmingham.
Funded by The Health Foundation and supported by CERSI-AI, we brought together regulatory experts from the Medicines and Healthcare products Regulatory Agency, notified bodies, and AI verification specialists to explore one of digital health’s most urgent challenges.
Together, we analysed real-world LLM use cases across healthcare, mapped regulatory pathways, and assessed device classifications and risk levels under existing frameworks. The conversations highlighted both the practical hurdles and exciting opportunities facing innovators and regulators alike. A huge thank you to everyone who attended and contributed to the discussions, and to our brilliant team for helping to shape such a thought-provoking and productive day.
This work reflects our commitment to enabling smarter, more adaptive regulation that supports safe and effective innovation in digital health – a commitment we’ll continue advancing through our ongoing collaborative workshops.
What does it take for NHS organisations to be truly AI ready?
28th August 2025
On 11th July 2025 at the Wellcome Trust in London, CERSI-AI was proud to support a high-energy, expert-led workshop exploring exactly that. We welcomed policy makers, clinicians, public representatives, and digital leaders to define what “AI readiness” looks like in practice.
Hosted by the University of Birmingham and University Hospitals Birmingham NHS Foundation Trust‘s AI and Digital Health Research & Policy group, with support from NHS England and The Health Foundation, the workshop focused on four core aims:
- Characterise the organisational risks and opportunities of AI adoption
- Develop a readiness framework grounded in real-world NHS contexts
- Co-design practical tools to help provider organisations assess and build readiness
- Signpost existing tools, frameworks and evidence that can support NHS organisations on their AI journey
The day included implementation case studies, collaborative risk-mapping, and lively group discussions on what success should look like, all rooted in NHS realities and future ambitions.
A huge thank you to our Chairs Jeff Hogg and Alastair Denniston, our brilliant speakers Robin Carpenter, Andy Mayne and Kevin Percival who shared valuable lessons from across the system, and to everyone who contributed their time, insight and expertise.
This work is a vital step toward supporting safe, responsible and scalable AI adoption in the NHS. We’re looking forward to sharing the project’s outputs as they develop.