- AI tool predicts NHS staff resignations using workforce patterns and data
- Royal Berkshire NHS wins award for innovative employee retention technology
- New model explains reasons behind potential staff departures before decisions are made
An AI forecasting tool created for the Royal Berkshire NHS Foundation Trust in the United Kingdom has gained recognition for predicting staff resignations before they actually occur.
The project, developed in collaboration with the University of Reading, draws on workforce data to pinpoint what is pushing employees to make the decision to leave.
It won the Aiconics AI Enterprise Business of the Year award at the National AI Awards 2026, after judges evaluated its real-world application.
AI model delves into workforce patterns behind potential exits
The system was created to give managers early warning of retention issues in 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 AI 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 related to resignation risk, so HR teams can truly understand why a prediction was made rather than treating it as a mystery.
The initiative links directly to NHS workforce objectives, tackling turnover, reducing disruption and looking at ways to keep more staff in place.
It brings together academic research with operational healthcare data, which was not simple, and questions remain about how well these scale or sustain over time.
Royal Berkshire NHS Foundation Trust provides acute and specialist care across Berkshire and cares for approximately one million people through its hospitals and services.
Before this, the Trust relied on reactive reporting, which meant managers often only became aware of a retention issue once someone had already decided to leave.
Researchers used data analytics to create an artificial intelligence tool that supports workforce planning while leaving the final say to human decision makers.
Throughout development, the team closely followed the combination of operational knowledge with academic rigor, without losing sight of the responsible use of AI in a healthcare environment.
Recognition comes as organizations explore predictive AI systems
“The 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 showed measurable value, responsible innovation and genuinely practical results across sectors.
As LLMs increasingly find their way into workforce management, interest in predictive tools for organizational decisions continues to grow.
People from different backgrounds shaped this project, which encompassed data analysis, strategic human resources research, and healthcare workforce operations.
The forecasting tool is intended to give managers more to work with, not replace them, since job decisions still rely on human judgment.
Whether tools like this catch on more broadly will depend on accuracy, trustworthiness, privacy concerns, and whether they actually deliver useful results.
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