Clinical Product Panel: How to Build Consumer Clinical AI Products Patients Actually Trust
Clinical Product Panel: How to Build Consumer Clinical AI Products Patients Actually Trust
Clinical Product Thinking 🧠
There’s a pattern that’s beginning to repeat in HealthTech AI.
A product performs well in evaluation. The model is accurate. The UX is smooth. Benchmarks look strong. The commercial case is compelling.
Then it meets real patients, real clinicians and real-world healthcare environments and it doesn't work as expected.
Trust breaks in unexpected ways. People over-rely on outputs or ignore them entirely. Edge cases emerge that were not seen in testing. Clinical responsibility becomes blurred. Safety concerns surface not because the model is “wrong”, but because the interaction between human judgement and AI output hasn’t been designed carefully enough.
This is the clinical AI trust gap.
It is the gap between building AI that performs well technically, and building AI that patients and clinicians can safely, appropriately and confidently use in real clinical contexts.
In this panel, we’ll explore what it actually takes to build consumer-facing clinical AI products that earn trust, not just at launch, but over time, across different users, contexts and levels of risk.
Rather than abstract debate, this session is grounded in lived experience from people building, deploying and governing clinical products in high-stakes environments.
What we’ll explore
What “trust” actually means in the context of clinical AI products and why it is multi-dimensional (clinical, emotional, operational and systemic)
Why high model performance does not automatically translate into safe or effective real-world use
Where consumer AI health products most commonly fail when they meet real patient behaviour
How to design for appropriate reliance, uncertainty and escalation in clinical AI systems
What good looks like when embedding clinical thinking into product, design and AI development cycles from the start
You’ll hear directly from:
Alison Paul on building clinical conversational AI interfaces that patients use and trust in a rapidly scaling environment.
Dr Louise Rix on why clinical product is becoming a critical discipline in the age of AI, and what founders and product teams consistently underestimate when building consumer clinical tools
Plus two other clinical AI leaders to be announced soon.