Summary
- The MHRA has published research and call-for-evidence findings for the National Commission into AI regulation in healthcare.
- Respondents supported monitoring, safety checks, transparency, accountability, and human oversight.
- NHS AI adoption will depend on regulatory confidence as much as technical performance.
The Medicines and Healthcare products Regulatory Agency has published evidence from patients, clinicians, industry, academics, and wider health-system stakeholders to shape the UK’s future regulation of AI in healthcare.
The material will inform the National Commission into the Regulation of AI in Healthcare, whose recommendations are due later this summer. The MHRA has published both a call-for-evidence summary and a wider research and engagement report, bringing together public polling, deliberative research, stakeholder engagement, an Ask Me Anything session, and insights from the agency’s AI Airlock programme.
The published reports show broad recognition of AI’s potential benefits in healthcare, provided regulation sets appropriate standards for safety and efficacy. The call for evidence received 760 responses from people and institutions.
Several themes stand out. Contributors supported ongoing monitoring of AI technologies after they are put into practice, rather than relying only on pre-deployment checks. They also pointed to the need for rigorous safety checks, transparency, accountability, and human oversight, while recognising that different AI uses carry different levels of risk.
That risk-based view is essential for the NHS. AI in healthcare can mean administrative tools that draft letters, systems that summarise consultations, diagnostic support for imaging, triage models, clinical decision aids, or generative systems that help produce patient-facing material. Lumping all of those use cases together would either over-regulate low-risk tools or under-scrutinise systems that can affect diagnosis and treatment.
The MHRA’s work also arrives as the NHS faces severe operational pressure. Waiting lists, workforce shortages, administrative burden, and regional inequality all create demand for technologies that can support clinicians and improve throughput. AI suppliers will find a willing market where tools can genuinely reduce friction, although adoption will still stall if hospitals cannot see clear regulatory routes, liability models, evidence standards, and post-market monitoring duties.
Healthcare AI regulation is difficult because performance can change over time. Models can drift, clinical workflows can alter outcomes, and systems can behave differently when used across populations or sites. That makes lifecycle monitoring central. A tool that performs well in a trial may still need surveillance once deployed into busy services with different data, staff, equipment, and patient groups.
Trust is not a soft issue in this market. It affects whether clinicians use tools, whether patients accept them, whether procurement teams approve them, and whether suppliers can scale beyond pilots. Public confidence depends on knowing who is accountable, how errors are handled, how data is used, and whether humans remain meaningfully involved in decisions that affect care.
The Commission’s recommendations will shape more than regulatory paperwork. They will affect how AI suppliers design evidence packages, how NHS organisations procure tools, how clinicians are trained, and how patients are told about AI use. The UK has repeatedly said it wants to be a leader in health AI, but deployment will depend on a route that is safe enough for clinical use and clear enough for suppliers, hospitals, and commissioners to follow.
