- 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 possible staff departures before decisions happen
An AI forecasting tool built for the Royal Berkshire NHS Foundation Trust in the UK has won recognition for predicting staff resignations before they actually happen.
The project, developed in collaboration with the University of Reading, draws on workforce data to flag what’s pushing employees toward the decision to leave.
It picked up the Aiconics AI Enterprise Business of the Year award at the National AI Awards 2026, after judges weighed in on its real-world application.
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 employees.
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’s possible when academic expertise in AI and forecasting is applied directly to a real problem facing the NHS,” said Shixuan Wang, a professor at the University of Reading.
The model pinpoints specific factors tied to resignation risk, so HR teams can actually understand why a prediction was made instead of treating it as a mystery.
The initiative ties directly into NHS workforce goals, tackling turnover, cutting down disruption, and looking for ways to keep more staff in post.
It brings academic research together with operational healthcare data, which wasn’t simple, and questions remain about how well these scales or holds up over time.
Royal Berkshire NHS Foundation Trust delivers acute and specialist care…
