- AI tool predicts NHS staff redundancy using workforce patterns and data
- Royal Berkshire NHS wins award for innovative employee retention technology
- New model explains the reasons behind possible staff departures before decisions are made
An AI forecasting tool built for the Royal Berkshire NHS Foundation Trust in the UK has won acclaim for predicting staff redundancies before they actually happen.
Developed in partnership with the University of Reading, the project draws on workforce data to highlight what pushes employees towards the decision to leave.
It received the Iconics AI Enterprise Business of the Year award at the National AI Awards 2026 after judges weighed in on its real-world application.
The AI model digs into workforce patterns behind possible departures
The system was built to give managers an earlier warning of retention problems across a workforce of around 7,500 NHS staff.
Unlike the Trust’s old reactive process, this model actually explains the reasoning behind each prediction, rather than just spitting out a result.
“This award reflects what is possible when academic expertise in artificial intelligence and forecasting is applied directly to a real problem facing the NHS,” said Shixuan Wang, professor at the University of Reading.
The model pinpoints specific factors linked to attrition risk so HR teams can actually understand why a prediction was made instead of treating it as a mystery.
The initiative links directly to NHS workforce targets, tackling turnover, reducing disruption and looking for ways to keep more staff in post.
It brings together academic research with operational health data, which was not straightforward, and there are still questions about how well these scale or hold up over time.
The Royal Berkshire NHS Foundation Trust provides acute and specialist care across Berkshire, serving around one million people through its hospitals and services.
Prior to this, the Trust relied on reactive reporting, meaning managers often only found out about a retention problem when someone had already decided to leave.
The researchers used data analytics to build an artificial intelligence tool that supports workforce planning while still leaving the final call to human decision makers.
Throughout development, the team kept a close eye on combining operational know-how with academic rigor, without losing sight of responsible AI use in a healthcare environment.
Recognition comes as organizations explore predictive AI systems
“Entries for the 2026 National AI Awards were hugely impressive, with companies spanning a wide range of industries and innovations,” said Fergus Bruce, CEO of The National AI Awards.
The organization said this year’s entries demonstrated measurable value, responsible innovation and real practical results across different sectors.
As LLMs increasingly find their way into workforce management, interest in predictive tools for organizational decisions is growing.
People from diverse backgrounds shaped this project spanning data analytics, strategic HR research and healthcare professionals.
The forecasting tool is meant to give managers more to work with, not replace them, as hiring decisions still rest on human judgment.
Whether tools like this catch on more widely comes down to accuracy, trust, privacy concerns, and whether they actually deliver useful results.
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