Neurosurgeons in London have carried out what health officials described as the world’s first successful AI-assisted operation to remove a brain tumour, in a case that could shape future use of artificial intelligence in delicate surgery.
The procedure took place in May at the National Hospital for Neurology and Neurosurgery, part of University College London Hospitals NHS Foundation Trust, but details were kept back until the event date while the patient recovered. The patient was identified as Rhys Hibbert, a 48-year-old man from Bedfordshire who had been diagnosed in 2024 and had seen his symptoms worsen over time.
According to The Guardian, the operation was designed to save his sight. Hibbert had a small 11mm pituitary tumour, and the surgical team faced the familiar challenge of working around nerves and blood vessels packed tightly together around the gland. In that area, even a tiny error can have severe consequences, including blindness, stroke or death.
The AI system did not replace the surgeons. Instead, it analysed live camera footage during the operation and highlighted key anatomical structures that needed to be avoided. The hospital had previously used the technology as a research tool, but this was the first time it had been deployed on a patient.
That distinction matters. The report describes the operation as AI-assisted rather than AI-led. The clinical team remained in full control, while the software helped colour-code important anatomy and make tiny structures more visible in real time.
The patient’s recovery has been presented as evidence that the intervention worked. Hibbert said he could see clearly when he woke up, could walk independently within a week without glasses or sticks, and has since returned to work as a customer service manager. Health officials said the operation spared his sight, which had been at risk as his symptoms worsened.
The technology’s technical lead, Dr Sophia Bano of UCL, said the system had learned from hundreds of surgical videos and was meant to help surgeons recognise critical anatomy, instruments and tissue interactions during highly delicate procedures. The system’s purpose is not to make the decision for the surgeon, but to support them when the visual field is crowded and the margin for error is narrow.
The hospital and the National Institute for Health and Care Research, which funded the surgery as part of a clinical trial, presented the case as a sign of how advanced AI can enter operating theatres in a controlled way. Prof Mike Lewis, NIHR’s scientific director for innovation, said the surgery highlighted the potential of AI to support surgeons and improve patient care.
For UCL, the case also fits a longer institutional story. Hibbert noted that NHNN dates back to 1859 and was the world’s first dedicated neurosurgical hospital, making it a symbolic site for the first AI-assisted neurosurgery as well.
The report leaves some questions open. It does not suggest that AI will soon replace human surgeons, and it does not claim the technology is ready for routine use across all neurosurgical cases. What it does show is that live computer analysis can be used as an extra layer of guidance when the target is small, the structures are crowded and the consequences of a misstep are severe.
That is a modest but important step. In a field where millimetres matter, the difference between a traditional visual field and one supported by machine analysis may prove significant. For now, the London operation is being treated as a milestone for clinical AI, and as a carefully watched proof of concept for future trials.
