Agentic AI set to ease NHS strain & free up GBP £340 million

The adoption of agentic artificial intelligence (AI) systems in the National Health Service (NHS) is being highlighted as a key approach to alleviate workforce pressures, increase efficiency and streamline workflows. As the NHS grapples with long wait lists, exhausted staff, and repeated calls for reform, organisations are examining whether AI-powered digital assistants can provide needed support without requiring substantial increases in staffing or budgets.

Role of AI agents

Unlike simple chatbots, AI agents are capable of making decisions, understanding natural language, and conducting multi-step tasks across various systems, such as electronic patient records, human resources, and booking platforms.

"Proactive AI systems that understand natural language, work across multiple platforms, and can carry out multi-step workflows from start to finish are essential to mitigate bottlenecks, boost efficiency, cut patient queues, and save time & money," said Joseph Kim, Chief Executive Officer, Druid AI

AI agents are envisioned not to replace NHS staff, but to function alongside them, enabling clinical and non-clinical teams to access the necessary information quickly when making patient decisions. According to Kim, these technologies allow staff to focus on care delivery rather than administrative processes.

Process automation

In practical terms, AI agents can be deployed in areas such as patient booking, HR, finance, and referral management. By handling high-volume, repetitive, and logic-driven tasks around the clock, they reduce the burden on staff. The Tony Blair Institute for Global Change estimates that implementing AI in patient navigation could free up 29 million general practitioner appointments annually in the UK, equating to resource gains valued at £340 million each year.

Agentic AI can centralise data, remove siloed workflows and allow patients to receive remote advice or treatment when appropriate. This can also streamline the processes of appointment scheduling, referral prioritisation, and patient follow-ups.

Data security concerns

Data protection remains a major concern for healthcare providers adopting new digital technologies. AI agent platforms are being developed with information encryption, independent detection and monitoring of sensitive data, and biometric security. Role-based access controls can limit exposure of personal information to authorised staff based on their professional duties.

These AI systems can be integrated with existing clinical infrastructure, such as EMIS or Epic, as well as legacy procurement or HR software, while maintaining privacy standards. Automated patching and software updates provide a further layer of protection as technology requirements evolve.

Patient experience

The NHS, having adopted new treatments over decades, now faces challenges in keeping service delivery aligned with patient expectations. AI agents can tap into extensive health databases, enabling rapid response to patient queries and providing clear guidance with more regular symptom checking and faster detection of potentially serious illnesses.

While generative AI models are noted for providing human-like conversation, they still face issues such as errors and bias. In contrast, agentic AI can guide patients through preventive strategies, prescription management, and scheduling, while cross-checking their decisions in the background with medical best practices.

Supporting staff

In addition to benefiting patients, AI agents can assist NHS staff by providing easy access to knowledge databases and workflow aids. By eliminating the need for repeated queries and manual data collation, administrative time can be reduced, allowing clinical staff to focus more on patient care.

Kim stressed that ethical deployment is central to the approach: "The ethical use of AI should be to inform and support the clinical decisions made by a human, not make the decisions for them."

AI agents are described as collaborative tools, offering options based on up-to-date data and deferring critical decisions to qualified personnel. With agentic AI, the NHS may be able to manage operational strain and save resources without sacrificing quality, security or the human dimension of care.

"With an agentic AI system in place, the NHS can reduce operational strain, keep patient data secure, and support innovation in treatment delivery, all while saving time and money," said Kim.