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November 10th 2023 – From an outsider’s perspective, the medical imaging AI market may look like an easy win, with the recent publication of the US-FDA AI/ML-Enabled Medical Devices database highlighting an expected increase in the volume of AI/ML-enabled devices for 2023 compared to 2022. However, for those vendors on the ground, significant challenges continue to present themselves, including limited reimbursement, uncertainty on how to deliver innovative and scalable business models, and a lack of real-world evidence for AI products demonstrating health economic benefits. Vendors must, therefore, rise to these challenges, delivering impactful strategies that provide them with a competitive advantage, or face shortening funding runways and limited commercial traction. As the market matures, key questions will remain such as how can vendors leverage AI platforms, establish the most beneficial partnerships, successfully generate funding and fundamentally become a revenue-generating business?
Crafting an Effective AI Platform Strategy
The AI platform market has exploded in recent years. Three main AI platform offerings currently exist:
- AI ISVs that have commercialised an underlying orchestration platform which can host its portfolio of native as well as third-party algorithms
- Third-party AI platform vendors with a sole focus to provide an AI platform that can aid in the deployment, integration and orchestration of third-party AI solutions
- Imaging IT vendors that have developed AI orchestration platform alongside native radiology IT offerings.
Currently, no winner has emerged. Each vendor group faces its own challenges and must make careful considerations. AI ISVs developing independent platforms e.g., Aidoc, Viz.ai must learn how to navigate and promote partnerships with AI ISVs. Due to the time and cost to integrate onto a platform, AI ISVs want to make sure of a return on investment and ensure that their algorithms are promoted equally on a platform. Third-party platform vendors, the likes of Blackford and CARPL.ai are at an advantage as platform development is their only focus. However, the need for established partnerships across a wide range of customer types including hospitals, PACS providers and cloud providers is essential to successfully implement this strategy. Many imaging IT vendors developing their own platforms have focused on seamless integration and coupling with broader enterprise imaging offerings. This approach could almost be viewed as too advanced in the current market, with the length of time it takes to achieve integrations across multiple application areas slowing down the number of partners they can offer in each setting.
Longer term, it is expected that AI platform vendors will evolve to follow one of two paths: one will be creating broad AI platforms with a large array and number of AI application and the second, creating specialist suites to meet niche demands of healthcare providers. These offerings will evolve to go across a service line, providing end-to-end solutions that will also expand beyond the radiology department. To prepare for this eventuality, platform vendors need to prioritise: establishing complementary partnerships to begin building out clinical specialties; developing APIs to EHR and scheduling systems to help integration across the healthcare ecosystem; expanding platform capabilities to offer validation; advanced security features; provide real benefit to physicians through seamless integration.
Breaking M&A Momentum
M&A activity will drive the medical imaging market forward through consolidation. 2022 saw a record number of acquisitions, with 6 throughout the year; before this only 13 had been recorded. It was expected that 2023 would see an increased frequency of acquisitions compared to 2022, with many AI vendors anticipated to run out of funding. However only 3 have been recorded so far. This dip can be attributed, in part, to current global economic headwinds. Increased interest rates, the cost of debt and a greater focus on profit margins means that those vendors in a position to acquire an AI ISV need to ensure that the decision to do so generates a clear return on investment. As well, a lack of clarity on AI vendor pricing only adds to the uncertainty, with previous high valuations given to AI ISVs generating limited revenue, meaning the expected price and perceived value from an acquiree is expected to clash with what a vendor may be willing to pay. With the constantly evolving AI landscape, and challenges associated to price, looser partnerships can de-risk the investment and offer flexibility if the algorithm doesn’t perform as expected, or a more suitable acquisition target emerges.
Partnerships are therefore more prevalent currently as vendors look to advance their capabilities through a route that ultimately presents fewer risks. However, as AI adoption and use becomes more of an expectation across healthcare, we are anticipating the return and intensification of acquisitions. Acquisitions of AI ISVs or third-party platform vendors by imaging IT incumbents should increase as enterprise imaging strategies mature, as could the number of pharmaceutical companies looking to optimise drug development or clinical trial management. As the number of AI ISVs raising large capital investments grows, smaller ISVs could also be cannibalised by larger ISVs in a bid to inorganically expand product portfolios and establish a market leading position and differentiation.
Examining Leaders and Laggards in Funding Generation
As the medical imaging AI market pushes to ‘cross the chasm’, a group of leading vendors have emerged, characterised by having raised more than $100m in capital funding. Funding runways for many smaller vendors are depleting, and as highlighted in Signify Research’s latest VC funding analysis, the number of deals is decreasing year-on-year, with large, later-stage funding prevailing. This could worry some smaller AI ISVs, who typically have smaller product portfolios, as funding may become less accessible. As the market matures and a requirement for comprehensive solutions emerges, these vendors are also at risk of solutions being commoditised by larger vendors with deeper pockets, leading to an increase in smaller vendors exiting the market. Targeting rarer clinical applications provides smaller AI ISVs a better chance of survival.
In 2023, vendors successfully raising larger funding rounds are those demonstrating extensive product portfolios (e.g., RapidAI) and those able to show a route for reimbursement (e.g., HeartFlow). Consequently, these vendors can implement more advanced strategies including targeting new regions and conducting more extensive clinical trials. This not only benefits the vendors themselves, but also the adoption of medical imaging AI, driving market growth and maturity. The question arises, however, whether smaller, less well funded AI ISVs will be able to remain competitive as the gap between vendors widens. Unless vendors have the resources to fund large clinical validation studies and improve product capabilities that may enable them to target reimbursement, they may struggle to become profitable.
Unavoidable Convergence
AI ISVs need to make considerable effort to build their competitive strategies. There are over 220 vendors within the medical imaging AI vendor landscape, making the job for vendors to compete and stand out difficult. Many vendors are therefore looking, in the short term, to establish multiple platform partnerships and raise funding. The hope here is that this could provide greater differentiation in the long-term and position them as an attractive acquisition target. Market consolidation is inevitable; the steps vendors take now will influence how they fare in the future.
Related Research
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About Ellie Baker
Ellie joined Signify Research in 2023 as part of the Medical Imaging team. She holds a BSc in Biomedical Sciences from the University of Bath and an MSc in Clinical Drug Development from University College London.
About the Healthcare IT Team
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