AI in medical imaging: the key tenets of an effective governance strategy
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The market for artificial intelligence (AI)-based devices in the medical imaging space continues to grow rapidly, with no indication that demand or innovation will slow in the near term. With this ongoing rise, governance strategies to manage the safety, data accuracy and performance of AI devices and software, both at the developmental stage and throughout a product’s lifecycle, are of increasing importance.
AI is having a significant impact across healthcare, not least in the medical imaging space. A report by GlobalData forecasts that AI in healthcare will reach a valuation of $57.4bn in 2029. Looking at the FDA’s list of AI-based medical devices approved in 2026, the overwhelming majority are products designed for applications in the medical imaging space.
In Europe, regulation surrounding AI-based medical devices and software is advancing in the form of the EU AI Act, initially implemented in 2024. Similarly, the UK’s Medicines and Healthcare products Regulatory Agency (MHRA) is currently overhauling its regulatory approach to AI in healthcare to account for gaps in existing regulation.
