Healthcare technology leaders are forecasting widespread adoption of artificial intelligence (AI) across hospitals, primary care networks, and community services.
The 12 key predictions below outline how AI could transform clinical workflows, workforce planning, and patient-centred care within the NHS.
1. AI readiness across organisations
Dr Harry Thirkettle, Director of Health Innovation at Aire Logic, said many NHS trusts still use electronic patient records (EPRs) mainly as digital filing systems.
He added that safe AI adoption requires clean data architecture, proper governance, and organisational capacity to evaluate and iterate tools effectively.
2. Ambient AI for clinical documentation
Nick Wilson, CEO of System C, predicts that ambient AI voice technology will become standard for capturing clinical notes, reducing screen time for clinicians and allowing more focus on patients.
3. AI integrated into core systems
Wilson also said AI embedded within EPRs and case management systems will replace standalone solutions, delivering smoother workflows and task orchestration.
4. Scaling proven digital solutions
Dr Rachael Grimaldi, Co-Founder and Chief Medical Officer at CardMedic, highlighted the importance of moving successful digital tools, such as interpreter access and accessible communication solutions, from pilot projects to system-wide implementation.
5. Data trust and interoperability
Nadine Carey-Whitehead, Commercial Director at Insource, said automation will only succeed if clinicians can trust the data.
She added that organisations creating interoperable, single sources of truth will be able to deliver patient-centred care at scale.
6. Neighbourhood health models
Sharon Hanley, Director of Primary Care at X-on Health, said neighbourhood models could integrate primary care around local communities, but only with shared infrastructure, clear referral routes, and consistent communication.
7. Prevention-focused, data-led care
Samantha Fay, CEO of SiSU Health, said AI will support prevention-focused care, helping integrated care boards pool resources, set shared goals, and track measurable outcomes.
8. Proactive cardiovascular care
Siim Saare, Founder and CEO of Lifeyear, said remote patient management will move beyond monitoring to include early risk detection, personalised interventions, and reduced clinical workloads, enabled by shared digital infrastructure.
9. Predictive workforce analytics
Karen Swinson, Clinical Lead at RLDatix, said AI will help trusts forecast staffing needs, identify rostering and absence patterns, and support professional decision-making.
10. Workforce optimisation based on demand
Phil Bottle, Managing Director at SARD, said AI will reveal hidden capacity gaps and phantom work, enabling trusts to design teams based on demand rather than rota boxes.
11. Optimisation and innovation through digital foundations
Mark Hutchinson, Executive Vice President at Altera Digital Health, said trusts with strong digital foundations can safely innovate and gradually introduce new tools, improving efficiency while maintaining operational stability.
12. Open platforms and reusable clinical data
Brian Murray, Sales Director at Better, said open digital platforms, interoperable APIs, and reusable clinical data will become operational necessities, supporting longitudinal patient records and the NHS 10 Year Health Plan.
Industry leaders say 2026 will be a pivotal year for AI in the NHS, with organisations expected to move beyond pilots and isolated projects toward fully integrated systems.
The focus will be on embedding AI into core digital infrastructure, improving workflows, supporting staff, and delivering measurable benefits for patients and services.