As regenerative medicine moves towards increasingly personalised treatment planning, artificial intelligence is beginning to play a larger role in patient assessment, imaging, documentation and clinical workflows. However, specialist insurer Hamilton Fraser has warned that practitioners must ensure AI supports rather than replaces clinical judgement, particularly when making biological treatment decisions. 

The company says many clinics are already using AI-powered tools, often without formal policies, structured oversight or a clear understanding of how liability may be affected if something goes wrong. As AI adoption accelerates across regenerative medicine, the insurer highlights how governance must evolve alongside the technology. 

AI and clinical-decision making  

Hamilton Fraser says one of the biggest concerns is the growing use of AI in patient assessment and treatment planning, where automation bias or over-reliance on AI-generated outputs could contribute to poor clinical decisions or unrealistic patient expectations.  

In regenerative medicine, where treatment selection increasingly considers factors such as tissue quality, inflammation, lifestyle and biological ageing, AI has the potential to support clinical decision-making by analysing complex datasets. However, Hamilton Fraser stresses that insights generated from AI should complement – not replace – the clinician’s expertise and individual patient assessment. 

While AI may support clinical reasoning, responsibility for treatment decisions remains with the practitioner. The company warns that AI cannot hold liability or professional indemnity in the way a clinician or practice can, making appropriate oversight essential whenever these systems are used within patient care. 

Eddie Hooker, founder and CEO of Hamilton Fraser, said, “From an insurance perspective, the key principle remains unchanged: responsibility sits with the practitioner and the clinic. AI does not remove clinical accountability, and it cannot hold liability if something goes wrong.” 

Patient awareness and use of AI  

The business is also seeing signs that complaints are becoming more sophisticated, as AI tools become more accessible to consumers.  

As patients increasingly use AI to research regenerative treatments and compare protocols, practitioners may find themselves facing more informed – and sometimes AI-influenced – questions and expectations during consultation.  

Even tools that appear relatively low risk, such as facial simulation or imaging software, may influence patient expectations if AI-generated simulations or visualisations are interpreted as predicted outcomes rather than illustrative examples. This makes clear communication, documentation and informed consent increasingly important. 

Hamilton Fraser also advises that practitioners should be prepared to address misinformation or unrealistic treatment recommendations generated by AI, helping patients understand where emerging technologies can support care and where clinical expertise remains essential. 

Building safe AI governance 

Although professional indemnity policies are evolving as AI becomes more widely adopted, Hamilton Fraser warns that practitioners who rely heavily on automated systems without appropriate oversight may increase their exposure to complaints and claims. 

The insurance provider says clinics should take a cautious, structured approach to AI adoption, particularly in areas involving patient-facing communication or clinical documentation. 

Clinics should: 

1. Maintain independent clinical judgement at all times 

2. Treat AI outputs as advisory rather than authoritative Clearly document where AI tools are used within workflows 

3. Make sure consent processes reflect relevant AI involvement 

4. Use only GDPR-compliant systems for patient information 

5. Introduce formal AI-use policies and staff training 

It is also essential that clinics are transparent with their insurers about the AI-supported tools used within the business, particularly where they influence clinical workflows, patient communication or treatment planning.  

For regenerative practitioners, where treatment plans are often highly personalised and evolve as new evidence emerges, robust governance will be essential to ensure AI enhances patient care without compromising professional accountability.  

Keeping pace with innovation  

As AI becomes more deeply embedded within regenerative medicine, questions around accountability are likely to become increasingly important. Where treatment decisions involve input from AI-supported software, responsibility may not always be straightforward, particularly as legal and regulatory frameworks continue to evolve.  

“At the moment, standards around AI use in aesthetics are still evolving,” said Hooker. “The industry needs greater clarity around accountability, transparency and safe use within clinical decision-making. Technology is moving quickly, but patient safety and professional responsibility must remain the priority.” 

For now, one principle remains clear: technology may support clinical practice, but accountability continues to rest with the practitioner. 

As regenerative medicine continues to embrace technologies that promise greater precision and personalisation, ensuring AI is implemented responsibly will be key to maintaining patient trust, supporting evidence-led care and ensuring innovation does not outpace clinical accountability.