A new government report calls for clear rules on who bears responsibility when artificial intelligence influences clinical decisions, warning that current negligence frameworks risk pushing liability onto healthcare professionals without accounting for the role of AI system design.
The National Commission report, published on 10 September 2026, recommends that regulations require standards or oversight for devices "where there is sufficient risk to patients." It also flags a structural problem in how claims unfold: under existing negligence procedures, cases are disproportionately brought against healthcare professionals and providers because they carry the clearest duty of care.
"Responsibility for errors may be transferred onto healthcare professionals and providers without sufficiently recognising the influences of AI systems and wider system design," the report warned.
Pharmacists and the accountability gap
Mark DasGupta, director of professional development at the Pharmacists' Defence Association, said the report's findings align with concerns the PDA raised in its own August 2026 guidance on AI use in pharmacy practice. "As AI becomes increasingly integrated into healthcare systems and pharmacy workflows, questions about accountability, responsibility and liability are being raised more frequently," he said. "Pharmacists recognise that AI may influence decisions, but there remains uncertainty about how responsibility is shared between healthcare professionals, employers, organisations deploying AI systems and the developers of those systems."
DasGupta pointed to a specific tension: pharmacists may remain professionally accountable for decisions shaped by systems they have limited visibility into or control over. He added that a coordinated approach to building professional capability could help establish consistent standards, though it should "complement, rather than replace, profession-specific guidance and training."
Where responsibility should fall
Tase Oputu, president of the Royal College of Pharmacy, reinforced the need for accountability that follows control. "Pharmacy professionals should remain accountable for decisions within their professional control, but responsibility for risks, such as product defects, unsafe updates and organisational failures, should be allocated according to who is best placed to control and mitigate those risk across the AI lifecycle, rather than defaulting to frontline clinicians," she said.
Recommendation 32 of the report urges a coordinated approach across the Department of Health and Social Care, devolved health departments, regulators, and royal colleges to develop AI use in healthcare. This spans initial education, postgraduate training, and continuing professional development. The report also recommends that contracts between AI device manufacturers and healthcare providers include an explicit allocation of responsibilities for controlling risk.
Oputu said the recommendation reflects the College's contribution to the Commission's work. "Our existing policy also recognises the importance of building digital and AI capabilities across the pharmacy workforce, with education and training tailored to different roles and levels of interaction with AI," she added.
Regulatory response
Kathie Cashell, chief executive of the General Pharmaceutical Council, welcomed the report and said the GPhC "will be carefully considering its recommendations." She confirmed the regulator has recently published resources on AI in pharmacy practice, revalidation, and education and training, with further work planned as part of reviews of standards for pharmacists, pharmacy technicians, and registered pharmacies.
"We strongly agree with the recommendation that a coordinated approach is needed to building professional capability in the safe and effective use of AI in healthcare," Cashell said.
Why this matters for healthcare professionals
The report signals that liability frameworks are lagging behind clinical reality. If you are using AI tools in practice - whether for decision support, workflow automation, or patient-facing services - your professional accountability may extend into systems you did not design and cannot fully inspect. The push for contract-level clarity between manufacturers and providers is an early indicator that responsibility allocation will become a formal part of procurement and deployment. For those looking to build competence in this area, structured learning paths like AI for Healthcare and role-specific training such as AI for Medical Billers offer ways to develop the skills that regulators and professional bodies are now calling for.
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