3. Simulation and digital twins – Before deploying AI or robotics in live clinical environments, hospitals increasingly want to train, test and validate these systems in realistic virtual environments. For example, Apian and NVIDIA are deploying photorealistic digital twins at NHS hospitals to safely develop and validate autonomous logistics robots before they ever enter patient care environments— a simulation-first approach helping to accelerate innovation while maintaining the safety standards healthcare requires.
4. Healthcare-specific foundation models – Healthcare has unique requirements around governance, privacy and regulation, driving growing demand for sovereign
AI built specifically for the sector. OneAdvanced’ s work with NVIDIA to develop what it describes as the UK’ s first private sovereign healthcare LLM, trained on NHS primary care data, shows how organisations are building AI grounded in local clinical workflows while meeting stringent governance and data residency requirements.
The common thread connecting these examples is that AI is becoming foundational infrastructure for healthcare.“ Whether it’ s helping researchers discover new medicines faster, enabling hospitals to safely deploy robotics, or giving clinicians AI systems that work alongside them, the greatest impact will come from AI augmenting human expertise and helping
64 September 2026