ARTIFICIAL INTELLIGENCE
overstretched IT teams and speeds up innovation. Just as importantly, low-code creates a safe
environment to experiment. When development is slow and tied up in procurement, there’s little room to test, learn, or improve. Low-code flips that model – enabling fast iteration, local ownership, and the freedom to adapt quickly when something doesn’t work. This kind of agility is critical in a system as complex as
the NHS. Digital solutions must not only solve today’s challenges but also be flexible enough to evolve. That means choosing technologies designed to support both immediate transformation and long-term strategic goals. For the NHS to become truly digital and deliver on
the 10 Year Plan, it needs platforms that can flex to local needs now, while staying robust and relevant into the next decade. Scalable, low-code solutions provide that foundation – ensuring innovation can grow alongside the health system, not in spite of it.
AI has real potential to speed up safe patient discharge and free up critical hospital beds.
This doesn’t just help patients. It helps families, carers
and the wider health system by reducing the need for unplanned appointments and emergency visits. When combined with sentiment analysis – using natural language processing to detect concern or confusion in patient messages – this becomes a complete feedback loop. One that is constantly learning, responding, and improving outcomes. Across all of this, integration is key. Many NHS Trusts are still operating in silos, with digital tools that work well in isolation but don’t connect across the patient pathway. AI offers the opportunity to join these dots. Whether
it’s linking appointment systems with discharge planners, or integrating community services with hospital records, connected data creates connected care. Low-code platforms make this easier. They allow local teams to adapt and integrate AI-driven tools around their workflows without waiting on central IT. That flexibility is what makes digital progress sustainable. Just as importantly, AI supports staff. By reducing repetition, surfacing key information and automating routine processes, it gives professionals time back for patients – not just paperwork.
John Clarke
John Clarke is head of Client Solutions – Health at Netcall. A former Chief Information officer (CIO) at University Hospitals of Leicester and St Andrew’s Healthcare, John brings over two decades of experience leading digital transformation across some of the UK’s largest and most complex health organisations.
How to scale Recent NHS Trust Performance League tables highlight that many of the top-performing Trusts are those already embedding AI and low-code technologies into their operations. While these rankings reflect a broad range of metrics – from estate management to clinical outcomes – it’s clear that effective communication and digital coordination are key enablers of high-quality care. For this success to scale, digital transformation and AI implementation must stay practical. That means focusing on proven, repeatable interventions. It means listening to staff about what slows them down, and it means designing tools that are inclusive, interoperable and user- friendly. Low-code platforms play a crucial role in this. They
give frontline teams the power to build and refine AI- driven digital services without needing deep technical skills. Self-referral portals, digital triage forms, and post- discharge workflows can be created in weeks instead of months or years. By putting control into the hands of those closest to patient care, low-code reduces reliance on
86 Health Estate Journal January 2026
Building confidence and consistency To make the most of AI across the patient pathway, NHS organisations must also focus on building confidence in its use – among staff, patients and system leaders. That confidence grows when AI tools are deployed with transparency, evaluated clearly, and adapted quickly based on feedback. When clinicians see that automation helps reduce admin rather than clinical autonomy, and when patients find digital touchpoints helpful instead of alienating, trust builds naturally. Consistency is the next step. Right now, use of AI and automation varies significantly between Trusts and regions. Sharing what works – and why – can help scale progress more evenly across the system. National frameworks, integrated care boards and regional collaboratives all have a role to play in enabling this spread of best practice.
Digital champions at the local level are also crucial.
Frontline teams who co-create digital tools are far more likely to use and improve them. That grassroots ownership ensures technology stays relevant and responsive, rather than becoming a top-down mandate. Ultimately, AI should be viewed not as a standalone
project, but as part of a broader cultural shift – towards agile service design, real-time problem solving and joined-up patient care.
A practical path forward Conversations about NHS transformation must focus on tangible, measurable improvements. The priority now is implementation – delivering proven digital solutions at scale and embedding them into everyday operations.
AI and automation should be used where they can
make the biggest impact: improving patient flow, reducing unnecessary appointments, and supporting recovery at home. These technologies are not aspirational – they’re already in use across the NHS, producing reliable gains in efficiency, patient engagement, and care coordination. What’s needed is a system-wide commitment to adopting what works, removing friction for frontline teams, and ensuring patients experience continuity, not confusion. It’s about making recovery processes smarter, repeatable and consistently effective. AI should help the NHS do what it does best – deliver
timely, safe and person-centred care – with fewer gaps and greater confidence. Because in the end, smarter services aren’t about the tech. They’re about delivering better experiences for patients and professionals alike.
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