Move over, celebrity weight-loss drugs. Here comes AI

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Key Takeaways

AI-enabled medical technology is gaining momentum, with the FDA approving a record number of AI and machine learning-enabled devices in 2023.

AI is particularly promising in diagnostics and detection, including CT scans, PET scans and ultrasounds.

AI can efficiently and accurately analyse complex medical imaging data, leading to better health outcomes and cost savings.

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The FDA has been approving a growing number of med-tech tools that tap AI and machine learning. These devices are revolutionising medical diagnostics and detection, offering benefits for patients, hospitals and investors alike.

When people think of the most promising medical technologies making headlines today, they might think of the new class of highly effective weight-loss drugs with brand names that we can’t mention here. (A quick internet search into “GLP-1” anti-obesity medications will tell you all you need to know.) Investors have been driving up stock prices of these GLP-1 producers, but there’s another innovation that has been quietly gaining momentum in the med-tech industry, and artificial intelligence (AI) is a key catalyst.

In 2023, the US Food and Drug Administration (FDA) approved a record number of “novel” medical according to McKinsey & Company1. This trend was largely driven by FDA approvals of AI and machine learning-enabled devices, which also hit a high-water mark last year (see chart). One of the most promising areas for AI is in the diagnostics and detection space – particularly computerised tomography (CT) scans, positron emission tomography (PET) scans and ultrasounds.

FDA approvals (AI/machine learning-enabled)
Number of approvals
FDA approvals (AI/machine learning-enabled)

Source: McKinsey & Company; Evaluate Medtech; FDA database. Data as atMarch 2024. The FDA publishes lists of approved AI/machine learning-enabled medical devices primarily based on information provided in the summary descriptions of the submitter’s marketing authorisation document. The 023estimates are annualisations via linear regression.

What’s the benefit of using AI for diagnostics and detection? For starters, well-trained software can efficiently and accurately analyse complex medical imaging data, helping radiologists diagnose diseases more quickly and precisely. This brings a range of benefits:

  • Better health outcomes for the population at large
  • Significant cost savings for hospitals
  • Recurring revenues from AI software capabilities, providing med-tech providers with smoother earnings profiles that tend to attract investors

As medical diagnostic tools become increasingly advanced and capable of generating vast amounts of data, AI will be an essential way to analyse and interpret this information, improving overall patient outcomes. We expect to see regulators issue more approvals to novel technologies tied to AI, and we expect to see an overall widespread adoption of AI-enabled medical devices – all good news for investors. We will be watching closely as AI becomes a rich source of innovation and disruption for the health care industry.


1 McKinsey & Company, March 2024. In the FDA’s parlance, “novel” doesn’t simply mean “new”. These are devices that address an unmet need, or that can be safer and more effective than currently available options.

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