The future of Artificial Intelligence (AI) within medical asset tracking: what’s next for EBME teams in the NHS
In the NHS, the ability to find, maintain, and monitor medical equipment is not just a matter of operational convenience, it’s critical to estate compliance, sustainability, and patient safety. Yet for many EBME teams, asset management still feels like a balancing act, with thousands of devices across multiple sites and ever-growing demands.
As the NHS Ten Year Plan outlines a future shaped by digital transformation, it’s clear that medical asset tracking is undergoing a transformation of its own. What began as a tool for locating equipment is fast becoming the backbone of more intelligent, automated decision-making. Dave Bryan, Idox Product Manager, shares his insights on the future of Artificial Intelligence (AI) within medical asset tracking.
Stage One: From location to visibility
The early years of medical asset tracking were about locating equipment. Systems like barcode scanning and passive RFID brought order to inventory chaos, offering the first step toward digital asset management. EBME teams could log movements, reduce losses, and gain basic audit functionality.
But this visibility was static. A device could be logged as “last seen” at a location, but without certainty of where it was now, or how long it had been there. Maintenance schedules often ran on guesswork. Manual audits remained time-consuming and inconsistent. These tools served a purpose, but the gaps were obvious.
As devices moved outside hospitals into homes, hospices, and mobile services, the limitations of static tracking became more pronounced. And with pressures mounting around patient safety, resource optimisation, and regulatory compliance, the demand for real-time, context-aware systems grew.
Stage two: From visibility to intelligence
Today, many NHS Trusts are embracing real-time location systems (RTLS) using BLE, Wi-Fi, and GPS. These technologies offer continuous awareness of where assets are—not just where they were.
This live visibility opens the door to intelligent asset management. It’s not just about seeing location anymore, but connecting that data to wider workflows:
- Automatically alerting when a device is due for service
- Identifying patterns of underuse or hoarding
- Triggering compliance actions based on time, use, or location
- Supporting faster turnaround of critical kit across sites
Tracking systems capture the data, but AI can help turn them into decisions
Dave Bryan
Idox Product Manager
This kind of insight requires more than just smarter tags, it requires data accuracy—structured logs, interoperable systems, and clean, consistent records. This is where the groundwork for Artificial Intelligence (AI) begins.
Stage three: Preparing for AI-driven EBME
AI doesn’t replace EBME teams, it empowers them. Soon, we’ll be able to see tools that can:
- Predict equipment failure based on subtle behavioural patterns
- Optimise asset distribution across hospitals using demand forecasting
- Use visual recognition and wearable tech to instantly identify and locate devices
- Automatically prioritise service tasks based on risk and availability
However, AI is only as good as the systems beneath it. Without clean data, interoperability, and secure handling of location information, the risks outweigh the benefits, especially in healthcare.
This is why adaptable, technology-agnostic platforms like Idox’s iAssets are designed to serve as foundations for long-term transformation. Idox’s iAssets brings together RFID, BLE, GPS, and Wi-Fi tracking into one flexible system, giving EBME teams the visibility they need now, and the infrastructure to support AI-readiness later.
Already, NHS Trusts such as Royal Papworth and Gloucestershire Hospitals have cut audit time, improved maintenance cycles, and reduced equipment loss using iAssets. But more importantly, they’ve started the journey toward intelligent, accountable, and proactive asset management.
Conclusion: AI is coming, but it starts with the basics
The NHS Ten Year Plan sets out a clear expectation for digital transformation in healthcare, and AI is poised to have a big impact on the sector. It is vital that EBME teams begin setting the foundation with visibility, data accuracy, and integration—ensuring that infrastructure is future-proof and AI-ready.
The journey from manual logging to intelligent asset management is already well underway. For Trusts laying the right foundations today, the next ten years won’t just bring digital transformation—they’ll develop an NHS that is smarter, more connected, and built to last.