Digital health funding has remained steady this year, with AI startups increasingly capturing a larger share of venture capital. In the first half of this year, AI-focused startups captured a majority of the digital health sector’s venture funding, with 62% of all venture capital investment in the sector going to companies that use AI to do things like automate documentation, accelerate drug discovery, improve diagnostics and boost patient engagement.
Investors are still laser-focused on AI’s ability to solve healthcare’s problems — but they are ramping up their scrutiny of AI companies as new startups continue to crowd the space, said Vig Chandramouli, partner at Oak HC/FT.
Customers are also remaining enthusiastic about AI — though this is more true for providers than it is for payers, he pointed out.
“I think payers are still getting their hands around what is considered AI and what’s not considered AI, and there’s legal definitions tied to contracting that’s slowing things down. But in the interim, I think providers have been willing to innovate and experiment,” Chandramouli stated.
As health systems deploy more and more AI pilots, he said they are starting to prioritize short-term, hard-dollar ROI — ideally six to nine months post go-live. This “time-to-value” metric is becoming the number one way to evaluate new AI companies, Chandramouli noted.
AI solutions hitting the market have to demonstrate tangible savings, such as reduced nurse staffing costs or increased revenue — and they need to do so relatively quickly, he explained.
“With ambient scribing solutions, I think version one of a lot of the platforms was about burnout, reduction in pajama time and positive feedback from providers. Version two of that story, as renewals of those contracts are coming out, is all about hard dollar ROI, and hard dollar ROI sits in the front end revenue cycle,” Chandramouli remarked.
Now, health systems are telling AI companies statements “We might pay you X, but we want to see a return on those dollars within a year of deployment,” he added.
Long gone are the days when a startup could promise ROI a couple years down the road, Chandramouli declared.
In general, the buying process has changed since the pandemic, he noted. A major part has been the fact that AI startups are increasingly putting fees at risk, tying their payment to achieved ROI.
“The ones that have conviction that they can drive hard dollar ROI will put their fees at risk. Because if you really do the math, Option A is to do a pilot, invest a bunch of internal resources, and do it for about a year, and then it maybe converts — or you just give it to them for free until you hit an ROI cliff,” Chandramouli explained.
And health systems are quite willing to engage in these types of arrangements, he pointed out, because the pain points are so acute. From his point of view, provider organizations are most interested in AI tools to improve nurse staffing, documentation and rev cycle processes.
These organizations, particularly mid-tier systems, are prioritizing fast pilots that solve immediate problems, Chandramouli said.
Ultimately, he believes the next phase of digital health investing will be defined not by the companies with the flashiest AI, but by the ones that can deliver measurable value in months rather than years.
Photo: Richard Drury, Getty Images
