Advocating for a fair and effective AI legal framework for members
16 Jul 2026
Estimated read time:
2 min read
Dr Sarah Townley, Deputy Medical Director at Medical Protection, discusses the “Closing the AI Liability Gap” report published earlier this month.
At Medical Protection we want to help our members and their patients realise the potential benefits of AI, while providing advice and support to manage emerging risks. We are equally focused on ensuring that AI tools – and the legal frameworks that underpin them – work fairly and effectively for those using them.
It is the shortcomings of the UK’s product liability framework that led us to publish our June report, “Closing the AI Liability Gap.”
In this report, we highlight to the UK Government that under the current Consumer Protection Act 1987, clinicians who use AI systems - particularly those suggesting diagnoses and treatment plans - are at risk of absorbing all legal responsibility if a patient comes to harm, even if harm arises due to a defective AI system.
This is because AI systems are not clearly defined as “products” - meaning developers, manufacturers and suppliers of AI tools, may be shielded from the liability rules that would usually apply if a defective product caused harm.
This might make it difficult for patients to bring product liability claims against these parties if harm occurs. The default may therefore be to pursue the end user of the AI - the clinician - through a clinical negligence claim.
We believe the current framework is inequitable and have urged the Government to act quickly in introducing legislation which clearly classifies AI systems as products. Such a change should distribute responsibility for harm caused by defective systems more fairly - rather than solely to clinicians through claims.
The potential benefits from swift action on this are clear: fairer outcomes when things go wrong, better protection for members when harm arises from defective AI, and the introduction of safer AI tools, as shared liability creates stronger incentives for developers to prioritise safer design and ongoing testing.
We will continue to advocate on this issue on behalf of our members.
Last year we launched the AI Safer Practice Framework, aimed to help healthcare professionals integrate AI safely and responsibly into practice. The framework is comprised of two parts: INFORMED and RECORDS.
INFORMED guides ethical decision-making using AI, while RECORDS documents AI-assisted decisions for accountability and clinical rationale. The framework has been structured around these acronyms for ease of use.
The AI Safer Practice Framework can be accessed at: AI Safer in Practice
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