Why “time to value” is the No. 1 metric healthcare AI customers care about
Digital health funding has remained steady this year, with artificial intelligence startups increasingly receiving a larger share of venture capital funding. In the first half of this year, AI-focused startups received the majority of venture capital investment in digital health, with 62% of all venture capital investment in the space going to companies using AI to automate documents, accelerate drug discovery, improve diagnostics, and increase patient engagement.
Vig Chandramouli, partner at Oak HC/FT, said investors remain highly focused on artificial intelligence’s ability to solve health care problems, but they are increasing their scrutiny of AI companies as new startups continue to flood the space.
He noted that customers also remain enthusiastic about AI, although this is more true for providers than for payers.
“I think payers are still learning about what is and isn't considered AI, and the legal definitions related to contracts are slowing down. But in the meantime, I think providers have been willing to innovate and experiment,” Chandramouli said.
As health systems deploy more and more AI pilots, he said, they are starting to prioritize real ROI in the short term — ideally six to nine months after go live. Chandramouli noted that this “time to value” metric is becoming the primary way to evaluate new AI companies.
He explained that AI solutions entering the market must demonstrate tangible savings, such as reduced nurse staffing costs or increased revenue, and they need to do so relatively quickly.
“For environmental striping solutions, I think the first version of many platforms was about burnout, reduced pajama time and positive feedback from providers. As those contracts come up for renewal, the second version of the story is all about hard dollar ROI, and hard dollar ROI is in the front-end revenue cycle,” commented Chandramouli.
Now, health systems are telling AI companies to state “We might pay you X, but we want to see a return on that money within a year of deployment,” he added.
Gone are the days when startups could promise ROI in a few years, claims Chandramouli.
He noted that, in general, the buying process has changed since the pandemic. The main reason is that AI startups are increasingly putting fees at risk, tying their payments to the ROI achieved.
“People who are convinced that they can drive ROI are putting their fees at risk. Because if you really do the math, option A is to do a pilot, invest a lot of internal resources, for about a year, and then it might convert — or you just give it to them for free until you hit the ROI cliff,” explains Chandramouli.
He noted that health systems are more than willing to participate in such arrangements because the pain points are so acute. From his perspective, provider organizations are most interested in AI tools to improve nurse staffing, documentation and circulation processes.
These organizations, especially mid-tier systems, are prioritizing quick 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 those that can deliver measurable value in months rather than years.
Photo: Richard Drury, Getty Images
