Artificial intelligence has reached an important moment in UK health and care. For years, AI has been viewed largely as a tool for drug discovery or clinical research. Now, its potential is far broader and more transformative: reshaping how the NHS operates, supporting clinicians in their daily work, and enabling citizens to manage their own health more proactively. In a current climate of rising demand, workforce shortages and ever-increasing pressures across healthcare, AI provides an opportunity to redesign the system, making it more efficient, proactive and ultimately, fit-for-purpose.
Harnessing the opportunities for AI adoption
While high-profile innovations in drug development and clinical research attract much of the attention, the true power of AI lies in supporting everyday care – the routine interactions and decisions that make the biggest difference to patients and professionals.
Increasing proactivity
Firstly, AI has the potential to increase proactivity in the healthcare system. For those living with chronic illnesses, such as COPD, AI-powered predictive analytics could be used to identify key warning signs and recommend preventative actions, such as initiating a course of steroids or antibiotics to treat symptoms. This has the potential to avoid A&E trips or hospitalisation, thereby benefitting both the individual and the system. For those who are admitted, AI could support the analysis of critical data and treatment plans, thereby reducing bed days at a time where resources are constantly stretched.
Supporting independent living and social care
Additionally, AI can be used to support independent living and social care, through the use of wearables and medical devices. These tools can detect if an elderly patient has fallen, has a nutrition deficit, or is showing age-related signals of deterioration or frailty, all of which can then be managed by existing social care interventions.
Whole-system integration
One of the NHS’s biggest challenges is data fragmentation. A patient’s history is spread across GP practices, hospital trusts, pharmacies, dentists and social care providers. AI can be used to draw all this information together and immediately identify trends which aren’t immediately apparent to human users or would take a lot of time to research. The result is better time utilisation by professionals, meaning they can attend to a greater number of patients, and the outcomes will be more tailored to the specific needs of that patient’s situation. Tied with this, AI can support the operational side of healthcare by optimising schedules, appointments, capacity needs and distribution of key drugs and blood when and where needed.
Clinician and at-home diagnoses
In terms of diagnoses, digital AI assistants can support high-stake decisions – from triage to detecting cancers, strokes or fractures – improving both speed and accuracy. Routine cases could eventually be automated, with clinicians focusing their expertise on more complex or urgent patients. There is also greater opportunity to shift forms of healthcare delivery to the home, using AI to enable safe self-assessment, home-based testing and secure digital sharing of results. This can reduce pressure on frontline services while giving people faster, more personalised care.
A well-rounded understanding of citizens
Finally, AI could help to ensure a more joined-up and comprehensive view of citizens. With the right conditions in place, sharing AI across the NHS and government departments will ensure citizens do not fall through gaps in the system, and will allow organisations such as the Department for Work and Pensions to assess eligible citizens for appropriate benefits, and those exploiting the system can be identified. Ultimately this will ensure better outcomes for the individual, and support government cost reduction initiatives, ensuring public spending is targeted and accurate.
The UK’s opportunity to lead on health and care AI
The UK is already a leader in much of the AI space. By focusing on healthcare and showcasing strong integration in AI systems across government, the UK will propel itself from being siloed, expensive and fragmented in the delivery of healthcare and public services, to becoming a global leader. The UK has the potential of becoming the next Estonia through AI.
The ambition, with the likes of the nation data library and the AI Opportunities Action Plan, is there. The challenge is transforming this ambition into reality. A key barrier to this is citizen trust. Ultimately, AI development requires high-quality, representative data, meaning live patient data needs to be exposed to the AI before benefits can be seen. However, public concerns about privacy and the use of personal information remains a major barrier. Moving to an opt-out rather than opt-in model, establishing patient governance boards, and scaling the creation of realistic synthetic data can help balance innovation with public confidence.
Political leadership is crucial. How and where data is stored and protected must be made transparent to citizens, and there must be a strong political commitment toward legislation, regulation and a focus on cybersecurity and encryption to keep data safe. This should form part of a wider “social licence” – a clear, citizen-friendly explanation of how AI is used across health and care, what the risks are, and how individuals are protected.
Responsible AI in healthcare must rest on three core principles. Firstly, AI must be used to assist clinicians, not replace them, and in return clinicians must continually train the AI to improve accuracy. Secondly, fairness and accountability must be ensured through rigorous validation, ethics and bias mitigation so that data training the AI is fair and representative of different demographics. Thirdly, AI innovation must be tested and monitored within a controlled environment before widespread deployment. This is an area where the UK could set the global gold standard.
The next steps to drive innovation
To accelerate progress and deliver benefits at scale, three actions should be prioritised. First and foremost, there must be investment into data infrastructure, with healthcare organisations embracing initiatives, such as the National Data Library, and finding ways for their data to become part of the ‘strategic national asset’. This should be happening at an industry level, not at an individual trust or facility level.
Another important step is targeting high-impact early-use cases to win public confidence. Focusing on high-profile cases like cardiovascular, diabetes or mental health – where solutions are more readily achievable and benefits are easily understood – will demonstrate value to the public. This will help to build trust and will provide valuable data into how a wider AI push will benefit the whole sector.
Crucially, the workforce must be equipped with the relevant skills to use AI. Technology in the NHS has been hit and miss: there are world-class digital tools created by the NHS, but also a continued reliance on outdated or manual processes, therefore a successful AI drive must therefore include a clear development programme, ensuring every clinician and administrator understands how to work effectively with AI tools.
AI cannot cure all pressures facing the NHS and UK social care. However, it certainly provides an opportunity to build a more proactive, personalised and efficient system. Provided the UK can pair strong regulation and public transparency with world-leading technology, it has the potential to transform not only its own healthcare system but lead the world in transforming theirs.
By Fay Cooper, CPO of Scrumconnect