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A clinician-led initiative · AI for healthcare
A movement to put clinicians at the centre of healthcare AI, starting in anaesthesia. ↓
Supported by & in collaboration with
01 · The mission
Artificial intelligence is presenting new opportunities to transform healthcare. Though AI development is often led by technologists with little input from clinicians, leaving real-world problems unaddressed.
Demand Signalling: AI in Healthcare begins with a problem-focussed, clinician-centred approach to identify the highest priority challenges for AI in health.
The project will generate a consensus 'demand signal' from clinicians across multiple specialties, informed by major stakeholders across academia, industry, policy, healthcare managers and patients.
The results will provide a strategic roadmap for more targeted, impactful, and clinically relevant healthcare AI.
We're inviting clinicians to suggest their highest priority clinical tasks for AI to address. See below for more information.
02 · The approach
Demand signalling turns the real-world experience of clinicians into a ranked, stakeholder-informed agenda for AI. It runs in three phases, the first exercise of its kind in these clinical domains.
An open survey invites practising clinicians to nominate the clinical tasks they most want AI to address. Every response is cleaned, categorised and checked for relevance.
A structured, multi-round Delphi process invites a purposive panel to rank the submissions, building consensus toward a definitive top-ten list of priorities.
Workshops bring together clinicians, academia, industry, policy-makers and patients to refine each priority, defining the problem, the goal and the clinical scope for AI.
03 · The projects
Anaesthesia is our flagship project, the proof of concept for a method built to scale into every specialty. Here's where each project stands, and how you can take part.
The first demand-signalling exercise in the specialty, run with the Association of Anaesthetists. Full publication expected Autumn 2026.
Which clinical tasks in ICM should AI tackle first?
Help set the priorities for AI in emergency care.
The anaesthesia, perioperative medicine & acute pain survey is now closed. Thank you to everyone who contributed.
04 · The team
Demand Signalling is led by practising clinicians and academics working at the intersection of clinical care, perioperative medicine and applied AI.
Chief Investigator
Principal Investigator
Principal Investigator, ICM
05 · Get involved
If you're a practising clinician, the most valuable thing you can do is tell us which clinical problems AI should solve. Each survey takes only a few minutes, and your answers directly shape the roadmap that funders, researchers and industry will follow.
For intensive care clinicians: which clinical tasks in ICM should AI tackle first?
For emergency medicine clinicians: help set the priorities for AI in emergency care.
06 · Collaborate
Demand signalling is a reproducible method designed to travel. Whether you lead a clinical specialty or build the technology, there's a way to work with us.
Want to run a demand-signalling exercise in your field? We share the method, materials and hands-on support to surface and rank your specialty's AI priorities.
Contact coming soonAccess a clinician-validated, consensus view of where AI is genuinely needed, so you can focus development and investment where it will have real clinical impact.
Contact coming soonUse the demand signal to direct funding and horizon-scan regulatory challenges before they become barriers to adoption.
Contact coming soonDirect contact details coming soon. In the meantime, connect with the team via LinkedIn above.
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