Can AI Clean Up Europe’s Sterile Workflow?

Hospitals test automated instrument recognition as digital demand grows

28 Jun 2025

Europe’s hospitals are entering a new stage of digital modernisation as artificial intelligence moves from research trials into pilot use within sterile processing departments. Early deployments of automated instrument-recognition systems are drawing attention from healthcare administrators seeking to improve patient safety and manage rising surgical volumes.

A notable example comes from a collaboration between Berlin’s Charité hospital and Fraunhofer IPK, where researchers have introduced an AI tool that identifies surgical instruments during cleaning and sterilisation. The system aims to support teams that rely on manual checks, barcode scans and paper documentation. Initial reactions suggest the technology could reduce handling errors and speed up processing times, though peer-reviewed evidence of large-scale gains remains limited. Analysts argue that clearer, automated identification could nevertheless change how hospitals organise their sterilisation workflows.

The shift coincides with wider digital investment across the sector. Getinge, one of the main suppliers of sterile supply systems, has expanded its tracking platforms, and AI-based recognition is viewed as a natural extension of its software suite. Integrating automated identification with real-time monitoring could offer hospitals a continuous digital record of each stage of the sterilisation cycle, a target regulators and managers increasingly view as central to meeting safety and compliance standards.

Industry observers expect the trend to encourage further consolidation as suppliers aim to provide end-to-end digital oversight, combining automation, analytics and traceability tools. The need for verifiable data is rising, prompting companies to explore new partnerships to secure their position in the sterilisation chain.

Technical and operational challenges remain. Hospitals manage large inventories of instruments that can be worn, near-identical or customised, requiring extensive image databases and regular model updates to maintain accuracy. Budget constraints and staff training demands may slow adoption, particularly at smaller facilities. But executives across the sector argue these obstacles can be addressed as investment and technical infrastructure develop.

European health systems continue to push for higher safety benchmarks and more efficient surgical operations. If current pilots prove successful, AI-based recognition tools could become a central component of future digital workflows, supported by closer collaboration between hospitals, technology groups and equipment suppliers.