The UK's National Commission into the Regulation of AI in Healthcare and the Medicines and Healthcare products Regulatory Agency (MHRA) have published a report setting out how AI should be implemented across UK healthcare. The recommendations follow a public consultation with more than 12,000 clinicians and patients, and arrive as AI adoption accelerates across the NHS.
The report marks a shift toward continuous oversight of AI tools in clinical settings. It proposes moving beyond one-off pre-market assessments to a model of ongoing monitoring and assurance throughout a product's lifecycle.
A patient-centric regulatory vision
The Commission's core aim is to create what it calls a "patient-centric, practitioner-enabling regulatory system." Lawrence Tallon, CEO of the MHRA, said the regulator heard clearly about AI's potential to speed up care and free clinicians for the human aspects of their work.
"We will only realise those opportunities if we have a modern, dynamic regulatory framework that accelerates safe adoption, protects patients and commands public and professional confidence," Tallon said.
Henrietta Hughes, Deputy Chair of the Commission and Patient Safety Commissioner for England, said the message from the public was unambiguous. "People want to know when AI is used in their care, confidence that it supports rather than replaces clinicians and clear accountability if things go wrong," she said.
Five recommendations for AI-enabled devices
The report contains 44 recommendations in total. Five of the key proposals focus directly on how software and AI-enabled medical devices are regulated and tracked:
- The MHRA should review and update the UK Medical Devices Regulations to allow a more tailored approach to software and AI-enabled medical devices.
- The MHRA should consider a function-based approach to regulation that accounts for increasing product complexity.
- Post-market surveillance requirements should be proportionate to a device's risks, benefits, and related uncertainty.
- The MHRA should introduce mechanisms to identify AI-enabled devices once deployed, including version control for traceability throughout a device's lifecycle.
- Healthcare organisations across England and the devolved authorities should adopt a system-level approach to transparency about when AI is used in patient care.
The recommendations are grouped under three focus areas: proportionate lifecycle regulation, system-wide responsibility and safe management, and trust, transparency and predictability. The report argues that balancing patient safety with innovation requires building confidence among patients, clinicians, developers, and regulators alike.
AI rollout continues across the NHS
The report lands during a period of rapid AI deployment in the NHS. Recent moves include a partnership with Microsoft Copilot that gives 500,000 clinicians and support staff access to the software. NHS England Midlands became the first region to procure an AI-powered ambient voice technology provider at scale, signing a deal with Heidi that covers 1,239 GP practices and more than 70,000 clinicians across 15 acute and community trusts.
Separately, the NHS has begun an AI-powered surgical evaluation initiative with Proximie, AWS, and Deloitte. The project is the largest-ever surgical evaluation in the public health service and aims to unlock additional capacity from existing facilities.
For healthcare professionals looking to understand how these regulatory shifts affect their daily work, structured learning can help bridge the gap between policy and practice. The AI for Healthcare Courses & Certifications page covers training relevant to clinical and administrative roles. Professionals in billing and coding may also find the AI for Medical Billers learning path useful as AI tools become more embedded in healthcare operations.
Why this matters for healthcare professionals
The report signals that regulators intend to require clear documentation of when and how AI is used in patient care. For clinicians, that means AI tools will need to be identifiable, version-controlled, and subject to ongoing safety monitoring - not just approved once and left unchecked. Administrative and clinical staff should expect greater transparency requirements around AI-enabled products in their organisations, and a regulatory framework that treats software-based medical devices differently from traditional hardware.
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