Generative AI shines amid VC funding chill
Amid a chilly health care IT fundraising market, generative AI companies raised over $250 million cumulatively in Q2, according to a recent PitchBook report.
Why it matters: HCIT investors are increasingly prioritizing early-stage profitability in prospective platforms, but generative AI may be an exception to that rule, the report indicates.
Zoom in: Four of the top 10 early-stage VC deals of the quarter were for companies focused on generative AI, including Hippocratic AI's buzzy $50 million seed.
- More than a quarter of Q2's recorded deal value went to generative AI companies, or companies offering generative AI solutions.
By the numbers: The second quarter saw 141 VC deals in HCIT, totaling a deal value of $2.3 billion.
- That's down significantly from the same period in 2022 when there was a total of 355 deals accounting for $5.9 billion.
- The share of angel, seed, and early-stage VC deals in HCIT year to date sunk to 26.2%, compared with an average of 48.9% in the 2020-2022 period.
Of note: Across all industries, 14.2% of U.S. VC deals in the quarter were down rounds, the report says.
Yes, but: The fourth quarter of 2022 "was the nadir of VC healthcare IT funding," writes Rebecca Springer, lead analyst, health care at PitchBook.
- Health systems are recovering from the financial hit of 2022 and more venture dollars are flowing into HCIT, as providers are able to spend more on new tools.
- According to the report, Kaufman Hall's hospital operating margin index hit 1.4% in June, remaining in positive territory for the fourth month in a row.
Between the lines: As health leaders focus on improving efficiencies amid continued reimbursement pressure, generative AI applications are gaining traction.
- "We are presently in an era of circumscribed, GPT-powered solutions for the low-hanging fruit; in existing workflows (that is, anything that requires a summary of a large, unstructured but easily accessible knowledge base)," Springer writes.
The bottom line: Generative AI will stay in its unsexy lane of improving clinical workflows until the industry "identifies widely trusted, high-performing LLMs (likely healthcare-specific)," Springer says.