IBMS response: AI regulation findings

The Commission’s final recommendations are expected later in 2026, but its latest findings already point to issues that will be highly relevant to biomedical scientists and laboratory services.
 

What does the Commission’s work cover?

The Commission’s research and engagement looked at views from patients, the public, healthcare professionals, industry, regulators and system partners. Its findings focus on how AI should be regulated, monitored and governed as it becomes more widely used in healthcare.

Key themes include:

• Patient safety and effectiveness: AI tools must be shown to work safely and effectively in real-world healthcare settings, not just in controlled testing environments.
• Human oversight: AI should support professional judgement, not replace it. Healthcare professionals must be able to understand, review and challenge AI outputs.
• Lifecycle regulation: Because AI systems can change over time or perform differently in different settings, regulation needs to go beyond one-off approval and include ongoing monitoring.
• Transparency and trust: Patients and professionals need clear information about when AI is being used, what role it plays and how decisions can be questioned.
• Equity and bias: AI systems must be tested and monitored to ensure they do not worsen existing health inequalities or perform less well for particular groups.
• Accountability and liability: There is still uncertainty about how responsibility should be shared between manufacturers, healthcare providers, professionals and regulators when AI contributes to decisions or errors.

Why does this matter to biomedical scientists?

Biomedical scientists work in services where quality, validation, audit, professional judgement and patient safety are central to practice.

As AI tools become more widely used in healthcare, they may support areas such as workflow management, image analysis, diagnostic support, reporting, triage or interpretation of results. These tools could bring benefits, including improved efficiency and earlier detection of disease, but only if they are properly validated, monitored and governed.

For laboratory medicine, the key question is not simply whether an AI tool works, but whether it works safely and consistently in the specific setting where it is being used. That includes the patient population, the data, the equipment, the workflow and the professional context.

AI systems must also be subject to the same level of scrutiny expected of other tools that influence diagnosis, monitoring and treatment. Biomedical scientists will need confidence that any AI used in their services has been tested appropriately, has clear limitations, and can be monitored effectively after deployment.

Human expertise remains essential

One of the strongest themes in the Commission’s findings is that AI should support, not replace, healthcare professionals.

This is particularly important in biomedical science. AI may help identify patterns or flag potential issues, but it cannot replace the scientific expertise, contextual understanding and professional accountability of biomedical scientists.

Professionals must be able to understand the basis of AI-supported outputs, recognise when they may be unreliable, and challenge or escalate concerns where needed. That will require not only good regulation, but also training, governance and clear local processes.

The importance of real-world monitoring

The Commission’s findings highlight strong support for ongoing post-market surveillance of AI systems.

This matters because AI tools may behave differently across different settings. Performance can be affected by changes in data, local practice, software updates or the population being served. A system that performs well in one environment may not perform in the same way elsewhere.

For laboratory services, this reinforces the importance of quality assurance, audit trails, version control, incident reporting and ongoing evaluation. AI systems used in healthcare should be monitored throughout their lifecycle, with clear mechanisms for identifying and responding to emerging risks.

David Wells, Chief Executive of the Institute of Biomedical Science, said:

Artificial intelligence has the potential to support healthcare professionals and improve services for patients, but it must be introduced safely, transparently and with proper professional oversight.

As regulation develops, it is vital that the voice of biomedical scientists and laboratory staff is included. Our members understand the importance of quality, evidence and patient safety, and these principles must remain central to the future use of AI in healthcare.

What happens next?

The National Commission is expected to publish its final recommendations later in 2026. These will inform how the MHRA, government and the wider health system approach future regulation of AI in healthcare.

For biomedical scientists, this is an important area to watch. AI regulation will have practical implications for quality management, workforce training, professional accountability, patient safety and the future delivery of laboratory services.

The IBMS will continue to monitor developments and highlight issues of relevance to members as the regulatory framework evolves.