By Karen Taylor, Director, Centre for Health Solutions

There is understandably an ever-increasing focus on the potential of AI to transform NHS services, with a heightened expectation of its potential to boost productivity but also to improve the quality of patient care and relieve staff from burdensome administrative tasks. This expectation is not only vested in more advanced technologies like GenAI, but also in proven technologies like robotic process automation (RPA) and machine learning (ML).  Our first blog of 2025, NHS productivity: what is the current situation and how might the new NHS plan tackle this? noted that commercial digital and AI solutions are expected to drive productivity improvements. This week’s blog considers the conditions necessary to optimise the potential of AI solutions and the importance of being clear what problem the NHS wants AI to solve?

A robust digital infrastructure in important in optimising the use of AI solutions

Having a robust digital infrastructure is essential if the benefits of AI tools are to be fully realised. However, the NHS comprises multiple services and organisations, whose digital maturity has evolved at different rates. In June 2019, our Deloitte report Shaping the future of UK healthcare: closing the digital gap, found that despite a decade or more of policies, strategies, programmes, and IT funding, aimed at improving and standardising the NHS’s digital transformation, progress had been slow and fragmented. At the time frontline staff rated their experience of digitalisation as ‘slow, expensive and challenging’ and the consensus of our 65 interviewees was predominantly negative, including concerns over the wide gap in digital maturity and access to funding within and across the sector. Indeed, the scale of the gap in digital maturity in NHS trusts was quantified in the 2018 National Information Board (NIB) digital maturity self-assessment ranging from 18 to 93/100.ⁱ

In 2020-21, the COVID-19 pandemic accelerated the pace of digital transformation across the NHS, but this also exposed still further the wide variation in digital capacity and capability in NHS organisations and concerns over digital exclusion. While the intervening years have brought measurable improvements in closing the digital maturity gap, challenges remain.

In late 2023 the NHS’s new NHS Digital Maturity Assessment (DMA), found that although 90 per cent of trusts had an electronic patient record, only 10 to 30 per cent of these trusts considered they had key functionality and were making full use of their system, such as integrated prescriptions and record sharing with citizens and other providers. Similarly, while 70 per cent of Integrated Care Systems had introduced electronic bed management systems, fewer than 40 per cent reported that they were seeing benefits. Importantly 20 per cent of providers reported gaps in more basic infrastructure, including fast network connectivity Wi-Fi access.^{ii iii}

This week, (29 January), the Committee of Public Accounts (PAC) report on NHS financial sustainability concluded that despite ambitions to improve productivity through the introduction of new technologies, the switch to digital in parts of the NHS has been glacially slow with NHS investment in technology over the period 2022–23 to 2024–25 ‘stalled because funding was redirected to mitigate Integrated Care Boards’ spending deficits’. NHS England (NHSE) in its evidence to the PAC noted that a crucial challenge was that the NHS still lacks a consistent data infrastructure and that providers varied in their levels of technological maturity.^iv

On the same day that the PAC report was published, the NHSE chief executive and deputy chief executive were giving evidence to the Health and Social Care Committee, and acknowledged that while a lot of work has been done in digitalising the NHS there is a lot more still to do and that ‘investing in every NHS organisation to have a decent electronic patient record (EPR) is hugely important building block for everything else’. They highlighted a point in the PAC report that providers that have implemented EPRs have productivity levels that are 13 per cent higher than those without them.^v

Why does this matter and what is the potential of disruptive technologies like AI?

Healthcare is on the cusp of radical digital transformation, with some of the most cost-effective digital improvements like robotic process automation (RPA) which uses software robots that can mimic human actions to execute rule-based tasks are relatively inexpensive, easy to implement and can and do deliver better experiences and relieve skilled valued staff from having to do repetitive administrative tasks. However, they do operate more effectively if the digital infrastructure is robust. Research shows that RPA, can enable complex organisations to achieve a 30-50 per cent productivity boost through transformation and automation. But requires technology investment, and a willingness to rethink workflows and for staff to work differently.^vi

Then there is the ‘game-changing’ disruptive potential of AI-enabled technologies. Digital advancements like AI-enabled virtual care using population health data, have the potential to support the government’s ‘three shifts’ (hospital to home, analogue to digital, and prevention) and move the system from reactive acute care towards more proactive, personalised care. Done well, this data-driven approach, with a focus on population health management, could help drive a better patient experience, improve patient outcomes, lower costs, enhance clinician well-being, health equity, and environmental sustainability. Indeed, the scope of disruptive technologies to transform healthcare is enormous, see Figure 1. ^vii

Figure 1. Disruptive technologies can revolutionise the delivery of healthcare, empower the workforce and transform patient care.

Arguably the most talked about disruptive technological  innovation over the past two years is GenAI, as highlighted in our recent life sciences and healthcare prediction 2030,  Intelligent healthcare and the democratisation of health data. GenAI’s ability to analyse complex and unstructured verbal and written information and use large language models to update EPRs without the need for clinician/nurse transcription, has potential to improve many aspects of healthcare, from clinical decision-making and more precise diagnostics to improving patient flow and efficiencies in healthcare settings and create predictive models for crisis preparedness To prepare for AI integration, HCPs will need to build their data fluency and technical skills and learn the applications of AI and GenAI in their field of interest or expertise. They will also need to be aware of best practices and standards such as data quality, privacy, security and ethics.

What are the risks?

There is a risk, as we have seen through our research, that NHS organisations become over-excited by ‘shiny new toys’ and underestimate the complexity of implementing the more advanced types of AI, when what is needed is to focus on the problem that needs fixing and involving end users in designing evidence-based solutions that could help. This could both delay the speed at which transformation happens and undermine clinicians trust and adoption. Consequently, the most important questions for organisations to ask themselves is what is the problem that needs solving?

There is also a risk of undermining productivity improvements by failing to prioritise interoperability and provide access to health data. The NHS Federated Data Platform (FDP) is an important step in addressing this challenge especially in making anonymised NHS data safely accessible to any approved user with a General Data Protection Regulation-compliant IP address. It will also provide an opportunity to accelerate the training and development of new AI algorithms. In the meantime, policy work is ongoing to develop “guardrails” for AI models that will ensure they are working as intended.^viii

Conclusion

Despite some impressive areas of progress, the NHS continues to face hurdles, primarily around resource allocation and ensuring uniform digital standards across all organisations and regions. The technology and platforms to deliver this already exist but adoption is at best sporadic. Accelerating, the technologically simpler transformations in every part of the NHS could improve productivity and staff satisfaction now, whilst also creating the environment, including the digital infrastructure, for optimising the use of more sophisticated AI tools that our most innovative organisations are developing. A priority needs to be levelling up the digital infrastructure across the NHS and ensuring that organisations are clear what problem they are seeking to address.

Karen Taylor - Director, UK Centre for Health Solutions

Karen is the Research Director of the Centre for Health Solutions. She supports the Healthcare and Life Sciences practice by driving independent and objective business research and analysis into key industry challenges and associated solutions; generating evidence based insights and points of view on issues from pharmaceuticals and technology innovation to healthcare management and reform.

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ⁱ Shaping the future of UK healthcare | Deloitte UK

ⁱⁱ NHS England » Digital maturity assessment

ⁱⁱⁱ DMA results show only 10-30% of trusts with an EPR have key functionality

^iv NHS financial sustainability

^v No set date for the NHS to be paperless, says Amanda Pritchard

^vi Understanding RPA - Guidance for designing, delivering and sustaining RPA within the NHS - NHS Transformation Directorate

^vii Intelligent healthcare and the democratisation of health data

^viii NHS England » NHS Federated Data Platform uptake and benefits