Indian IT giant Infosys has secured a £1.2 billion contract (approximately €1.2 billion) from the UK’s NHS Business Services Authority (NHSBSA) to deliver AI-enabled workforce management system.
The 15-year deal will replace the ageing Electronic Staff Record (ESR) system and drive transformational change across England’s and Wales’s NHS workforce operations.
This deal is one of the largest long-term technology contracts awarded in the UK health sector in recent years.
The Electronic Staff Record (ESR) system has long been the backbone of NHS employee management, but limitations in scalability, flexibility, and modern functionality have constrained its ability to support future demands. Infosys’s AI-enabled workforce management solution aims not just to replace but to supersede ESR with a modular, AI-enabled platform.
The platform aligns with the NHS’s 10-Year Plan, which emphasizes workforce sustainability, digital modernization, and efficiency in patient care. By giving staff better tools, the NHS hopes to reduce administrative burdens and free up more time for clinical care.
By embedding AI, analytics, and automation, the platform is intended to help the NHS make smarter decisions: forecasting staffing requirements, optimizing rosters, spotting trends in retention or attrition, and planning recruitment.
One of the goals is to deliver a more intuitive, self-service experience for NHS employees, letting them manage personal information, onboarding, career progression, and retirement more seamlessly.
The NHS is advancing several technology-led programmes beyond workforce systems. One is the Digital Productivity programme, which pushes adoption of tools like Robotic Process Automation (RPA), Real-Time Locating Systems (RTLS)/RFID, and Extended Reality (XR), in order to reduce staff burden, cut costs, speed up care, and improve patient and staff satisfaction. Internally, several NHS trusts are deploying RPA to automate repetitive administrative tasks and speed up workflows.
The AI in Health and Care Awards has committed over £123 million in grant funding to 86 organisations to trial and evaluate AI solutions that align with NHS goals. The NHS AI Lab is also facilitating regulatory work, ethics initiatives, and platforms to support safe, equitable, and responsible deployment of AI across the country.
Another area is remote monitoring and mobile technology: trusts like Nottingham University Hospitals have put mobile devices in the hands of clinicians, enabling them to use apps for live clinical observations, track nurse staffing in real time, and improve information access at the point of care. The NHS Long Term Plan aims to make the NHS App a “digital front door” for patients, giving them access to their records, test results, appointment bookings, and eventually secure digital consultations.
There are also diagnostic-support initiatives. For example, NHS trialling of AI-driven tools in dermatology and stroke care; using deep learning to automatically classify certain chest X-rays as normal with high confidence to free up radiology capacity; and a pilot AI tool at Chelsea and Westminster NHS Trust designed to generate discharge summaries to speed up hospital discharges.
Finally, programmes like the Global Digital Exemplar (GDE) promote digitally advanced NHS trusts to serve as models for others, sharing learning especially around electronic health record systems, helping spread good practice and innovation.
Rajani Baburajan
