May 162024

Private Equity Investors’ Attitudes Towards Healthcare AI Investment Opportunities

Chad Ehrenkranz
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Sidley’s Chad Ehrenkranz and UK-based U.S. investor Chris Yoshida consider which AI-based healthcare applications are of most interest to private equity investors, and the way in which healthcare AI lies in a desirable spot between startups and government uses of AI.

This spring, the EU has made a significant step forward towards encouraging responsible innovation within the AI space – including healthcare AI applications – with the recent approval of its EU Artificial Intelligence Act (EU AI Act). While the EU AI Act encourages responsible innovation, it indicates that strict prohibitions on certain AI practices classified as high-risk will be in place. This groundbreaking legislation creates the world’s first comprehensive framework for AI regulation, and its impact is expected to extend far beyond the EU’s borders, reshaping the global AI landscape.

This is a landscape in which AI-use cases within healthcare are quickly growing. There are increasing investment opportunities in biotech around AI products that have the ability to analyze genomics and genetics. AI is now enabling research labs to move much faster, with the research that some biopharma and life sciences companies have recently been able to conduct using AI that is equivalent to decades’ worth of work. AI-driven research in life sciences has included applications looking to address extremely broad-based therapeutic areas, such as diabetes, cancer, and chronic kidney disease.

Across the market, we are seeing life sciences innovators applying AI to real-world evidence, and using it to take an algorithmic approach to drug discovery. There are also exciting societal applications of AI in healthcare, such as the homecare that is now being made available via teledocs and telehealth medicine. In addition, a great deal of investment is being channeled into AI-powered preventative healthcare, including genetic mapping. In the U.S., in particular, the health law known as ‘patient choice’ is currently seeing a significant investor-driven push towards the use of AI.

Healthcare AI is also of particular interest to investors because it sits in a desirable location between government-use cases of AI – a space that is not readily accessible to outside incumbents and disruptors – and the highly price-sensitive startup community. This makes healthcare able to tap into both the startup and high-end markets, both of which are large and contain real-life problems that are in need of practical and immediate solutions. Hereditary cancer, genomics, patient care, and preventative diagnostics are good examples of these.

Some healthcare investors are very bullish about investing in AI. However, some are cautious, and this can lead to hurdles for healthcare AI companies seeking to secure investor buy-in. It can be helpful for innovators facing such a hurdle to ensure they fully explain to investors the cost of the capital needed to develop an end-to-end AI product. Startups could explain to investors the money spent on hardware, and how they will resolve the conundrum of generating a real return on that investment. In order to do so, a startup will need to demonstrate that it has a dedicated belief in its technology, a distribution channel, and, ultimately, a sales force.

Another reason why investors may be encouraging caution in the healthcare AI space is related to the fact that valuations for AI companies are generally extremely high at the moment, with 50-100 times revenue multiples being common. The high valuations that investors are seeing from AI-based companies can make them difficult to lean into and invest in, given that the success of an AI-based company is so path-dependent and that it’s statistically unlikely that it will be able to follow its anticipated path and be successful.

However, investment goes in waves. There are two ways in which investors can catch the AI healthcare wave. Either, by luck, they will be there at the right early moment. Or, they will prudently wait until valuations come back down. This is likely to happen either because AI healthcare companies realize they can’t run at scale, or because they are unable to compete with the largest players. When valuations come back to Earth, as they always do, then private equity will be able to justify the valuations and the risk-reward of its capital in the healthcare AI space, and we will see the next wave.

Chris Yoshida has worked in New York for Goldman Sachs, in London for Morgan Stanley Deutsche Bank, and world-renowned PE firm, The Carlyle Group. He has raised money for a tech startup and has been the President and CFO of Germany-based HPC hyper-scaler Northern Data, which built the foundation for the cloud and, at one point, ran the largest graphic processing unit (GPU) cluster in the world. He is currently the managing partner of PineTree Partners, a private investment vehicle backed by some of the most influential families in the world.

This post is as of the posting date stated above. Sidley Austin LLP assumes no duty to update this post or post about any subsequent developments having a bearing on this post.

Chad Ehrenkranz

New York, Miami

chad.ehrenkranz@sidley.com

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