The use of artificial intelligence in everyday life divides opinion, and healthcare is no exception. Concerns about data privacy, particularly around personal information being used to train AI models, are understandable and widely shared. At the same time, there are genuinely compelling examples of AI improving patient outcomes in ways that would have been difficult to achieve otherwise.

The NHS is expanding its use of AI, with a recent announcement confirming that Microsoft Copilot will be made available to more than 500,000 NHS staff. Significant safeguards have been put in place to keep patient data secure, and staff responsibilities around the appropriate handling of patient information remain unchanged regardless of the tools they use. AI in clinical settings is positioned as a support tool - one that assists, but never replaces, human judgement.

Where AI is already making a difference

Some of the most striking examples are in specialist care. Moorfields Eye Hospital, in a long-running partnership with Google, has used AI over the past decade to help clinicians better analyse eye disease and improve understanding of conditions that can lead to sight loss. AI has also been introduced into every stroke unit in the UK, where faster diagnosis is expected to triple recovery rates for stroke patients.

What this means in primary care

The environment of primary care is quite different, but AI is making inroads here too, and this is where most of us will encounter it as patients.

One growing application is reducing the administrative burden on GPs. Ambient Voice Technology can listen to a consultation and automatically draft clinical notes and referral letters, freeing up more time for face-to-face care. The GP remains responsible for reviewing and approving everything produced. Whether that time saved genuinely translates into longer appointments or simply more of them is, as the BMA has noted, a question of how the technology is implemented and something patients are right to take an interest in.

AI tools are also being used to support the management of chronic conditions - monitoring patient-submitted data such as blood pressure readings or glucose levels, and alerting clinicians when a patient's condition shows early signs of deterioration. The value here isn't simply that it makes monitoring possible, but that it can process far more information far more quickly, enabling earlier intervention.

A note on digital inclusion

As more AI-assisted services move online, there is a real risk that those who are less comfortable with technology find themselves further from the care they need. The BMA has highlighted digital exclusion as one of the significant concerns around AI in healthcare and it is one we share. Our work with Modality, Age UK and Community People on digital inclusion locally is partly motivated by exactly this: ensuring that as services change, no patient is left behind simply because they lack access to or confidence with technology.

If you or someone you know is finding it harder to access services as they move online, please do get in touch. This is precisely the kind of feedback that helps us make the case to the practice on your behalf.

Our view

The BMA's position is that AI is only as good as its implementation. Used well, it has real potential to improve care; used poorly, it can introduce new problems. Patients should know that they are entitled to ask how AI tools are being used in their care, and to raise concerns if something doesn't feel right.

We will continue to keep a close eye on how these developments affect patients locally, and to represent your interests as AI becomes a more visible part of primary care.

Sources

'Life-changing' AI support  helping stroke patients get a second chance
Principles for Artificial Intelligence (AI) and its application in healthcare
500,000 NHS staff to get new artificial intelligence tools to help free up more time for patients
Moorfields and Google Deepmind