It’s no secret that the rapid growth of AI in radiology is being fueled by venture capital firms eager to see a payoff for early investments in startup AI developers. But are there signs that VCs’ appetite for radiology AI is starting to wane?
Maybe. And maybe not. While one new analysis shows that AI investments slowed in 2023 compared to the year before, another predicts that over the long term, VC investing will spur a boom in AI development that is likely to transform radiology.
First up is an update by Signify Research to its ongoing analysis of VC funding. The new numbers show that through Q3 2023, the number of medical imaging AI deals has fallen compared to Q3 2022 (24 vs. 40).
- Total funding has also fallen for the second straight year, to $501M year-to-date in 2023. That compares to $771M through the third quarter of 2022, and $1.1B through the corresponding quarter of 2021.
On the other hand, the average deal size has grown to an all-time high of $20.9M, compared to 2022 ($15.4M) and 2021 ($18M).
- And one company – Rapid AI – joined the exclusive club of just 14 AI vendors that have raised over $100M with a $75M Series C round in July 2023.
In a look forward at AI’s future, a new analysis in JACR by researchers from the ACR Data Science Institute (DSI) directly ties VC funding to healthcare AI software development, predicting that every $1B in funding translates into 11 new product approvals, with a six-year lag between funding and approval.
- And the authors forecast long-term growth: In 2022 there were 69 FDA-approved products, but by 2035, funding is expected to reach $31B for the year, resulting in the release of a staggering 350 new AI products that year.
Further, the ACR DSI authors see a virtuous cycle developing, as increasing AI adoption spurs more investment that creates more products available to help radiologists with their workloads.
The numbers from Signify and ACR DSI don’t match up exactly, but together they paint a picture of a market segment that continues to enjoy massive VC investment. While the precise numbers may fluctuate year to year, investor interest in medical imaging AI will fuel innovation that promises to transform how radiology is practiced in years to come.