Women's Health AI Outperforms VC's Own Benchmarks

Women's Health AI Outperforms VC's Own Benchmarks—Yet The Funding Gap Persists

Geri Stengel Mar 09, 2026 at 07:00am EDT - Forbes

Female founders are building AI navigation tools designed specifically for women's health—in part because general-purpose AI, trained on historically male-skewed clinical data, has been shown to systematically downplay symptoms in women and ethnic minorities.

Female-founded companies show better survival rates, lower burn, and a quarter of all US venture exits. The capital allocation doesn't reflect the data.

Women are healthcare’s power users; they account for 60% of US healthcare spending—$2.1 trillion annually—and make roughly 80% of household healthcare decisions, according to an Ingeborg’s report. They are the market. Yet female founders who focus on women's health receive a small fraction of healthcare venture capital.

PitchBook's 2025 US All In: Female Founders in the VC Ecosystem reported a record $73.6 billion raised by female-founded companies last year. Strip out Anthropic and Scale AI, and the number drops to roughly $43 billion. All-female founding teams raised $3.2 billion, down 22% year-over-year.

The headlines and the underlying data are telling different stories. But there is a third story in the same numbers—one about capital misallocation. The women building AI for women's health aren't just surviving a brutal funding environment. By PitchBook's own metrics, they're outperforming the metrics that rule that environment.

Prediction vs. Navigation: AI Built Differently

The broader AI market is undergoing a structural shift. Investors who spent years rewarding top-line growth are now demanding outcomes-based models—a transition Annemarie Donegan, senior analyst at PitchBook and author of the All In report, compared to the shift toward value-based care in healthcare. Women's health AI founders arrived at that architecture years earlier, not by choice but by constraint.

Diagnostic AI trained on male-default data is a commercial liability in women's health, not an asset. MIT Jameel Clinic research found that GPT-4, Meta's Llama 3, and the healthcare-focused Palmyra-Med all recommended lower levels of care for female patients. That is a data quality problem with clinical and financial consequences—and it is exactly what Kathrin Folkendt, founder of Femtech Insider, has argued for years: "AI was supposed to fix healthcare bias. Instead, it's making it worse for women."

Founders working in this space identified the same problem from the product side. "The most common bias is the 'male default,'" said Karishma Patel, cofounder and chief brand officer at Ema, an AI platform that helps women navigate healthcare. "The training data and design patterns assume a standard human that is, in fact, male."

The solution they built wasn't a better diagnostic engine. It was a navigation layer—tools designed to guide women through fragmented care systems rather than predict diagnoses from unreliable data. "Prediction asks, 'What might be wrong?' Navigation asks, 'What's next for you?'" Patel said. 

That design logic extends into the workplace. Abbey Donnell, founder and CEO of Work&, which designs workplace wellness suites and connects employees to benefits they often don't know exist using Ema, described the same principle: "We make no claim to be experts in your health. What we do is help you understand what's happening and show you what options you have." 

Navigation-first, outcomes-oriented, built to work with incomplete data. That is the architecture VC is now being forced toward. Companies like Ema and Work& were already there. 

Female Founders Have Better Survival Rates, Use Less Capital

PitchBook tracked a cohort of 13,172 female-founded companies from the first VC round through all subsequent outcomes. The results show that female-founded companies advance at a higher rate after round one and go bankrupt at a lower rate than the all-US cohort. Their median monthly burn rate: $0.35 million, versus $0.39 million overall.

Those are the metrics investors say they prioritize. The funding distribution doesn't reflect them.

Donegan was direct about why. "VCs are looking to cast a wide net and hope that at least one of them is enough of a moon shot to compensate for losses across other companies." Portfolio construction optimized for one Anthropic-scale outcome doesn't reward durability—it ignores it. Her explanation of why female founders advance at higher rates was equally pointed: "Maybe that’s a function of women dotting their i's and crossing their t's. Or maybe it's a reaction to the reception they've got."

Both explanations identify a market distortion, not a personal one.

The Ema case makes the efficiency argument concrete. Amanda Ducach, the company's CEO, raised $3 million to build a proprietary hybrid language model, a clinical governance framework, and bias monitoring infrastructure. The platform is already embedded in Willow and other women's health tools. At most AI startups, $3 million is a prototype budget. "It forces focus and discipline," Ducach said. "We built something scalable without the waste that often comes with overfunding." 

The burn rate advantage is narrowing, down to $0.04 million per month in 2025. When it closes entirely, one of the most consistently documented arguments for investing in female-founded companies disappears from the data. Investors who haven't acted yet are running out of time.

The Exit Data Nobody's Leading With

Female-founded companies generated 24.9% of all US venture exits by count in 2025. The spread between capital entering and exiting is the central market-pricing question the data raises, and the Follow the Exits: Why Women’s Health Is a Smart Bet in Healthcare report by AOA Dx suggests the undercount dates back 25 years.

Exit value more than doubled year over year to $51.1 billion; transaction count rose more than 20%. Biotech and pharma—a sector where female founders are overrepresented—was among the few to grow in both deal value and deal count, producing two of the year's largest transactions: Capstan Therapeutics ($2.1 billion M&A) and Orbital Therapeutics ($1.5 billion M&A). 

Asked for her single forward-looking indicator for 2026, Donegan didn't hesitate: "I would point to the growth in exit activity, as well as the variety of exit types and industries represented on that list."

But the 2025 data may still undercount what women's health has actually returned. Follow the Exits documented more than $100 billion in women's health acquisitions and IPOs between 2000 and 2025—including $27 billion in transactions in 2025 alone, the largest year on record for the category. Most investors have never connected to the category. The reason: Those companies were classified in investment databases as diagnostics, oncology, or medical devices, never as women's health. 

"When you look up these companies in PitchBook, they're all segmented under equipment or diagnostics," said Anna Jeter, co-founder of AOA Dx and lead author of the report. "None of them are classified as women's health."

Donegan acknowledged the same gap. PitchBook's methodology still cannot cleanly track the health of women as a distinct investment category. Database taxonomy is a capital allocation infrastructure. When a category doesn't register in the tools investors use to evaluate markets, it doesn't appear in portfolio models. "The biggest misconception," Jeter said, "is that women's health is a small market. And that it is charity."

Eighty-two percent of VC decision-making roles at US firms with $50 million assets under management are held by men, per PitchBook. The performance data tells a consistent story: better survival rates, lower burn, and women-founded companies delivering 24.9% of exits. The question is whether their portfolio construction models are built to surface it. Markets that systematically misprice assets tend to correct. Women's health AI may be that correction already underway.