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Women's Health AI Consortium Launches to Set Industry Standards

A coalition of companies announced the Women's Health AI Consortium on May 12, 2026. The group aims to establish the first standards for AI tools used in women's health applications including postpartum care and fertility. Research cited in the announcement showed approximately 60% failure rates for leading AI models on women's health tasks.

Forbes
1 source·May 13, 11:04 AM(16 days ago)·2m read
Women's Health AI Consortium Launches to Set Industry StandardsForbes
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A coalition of companies including Willow Innovations and Ema EQ announced the formation of the Women's Health AI Consortium on May 12, 2026. The group is the first industry body dedicated to developing standards for artificial intelligence tools used in women's health.

The announcement highlights gaps in postpartum care. After giving birth, women typically see an obstetrician once at about six weeks before care shifts fully to pediatricians. Many then turn to AI-powered apps for questions on pelvic floor recovery, when it is safe to resume sex, and mood changes.

Sarah O'Leary, CEO of Willow Innovations, described the experience. " The company's app integrates AI from Ema EQ to respond to such questions.

Researchers who evaluated 13 leading AI models on women's health tasks found approximately 60% failure rates across all large language models. Every model performed worst on "missed urgency," failing to identify the most dangerous situations. A follow-up 2026 benchmark found no model exceeded 75% accuracy on women's health clinical scenarios.

Morgan Rose, chief science officer at Ema EQ and a co-founder of the Consortium, said the root issue is structural. " The group plans to trace failures back to infrastructure decisions made during AI development.

Rose stated there are currently no standards governing AI tools that provide information directly to women on postpartum recovery, fertility or symptoms. The Consortium has no regulatory authority and companies may choose not to follow its standards.

O'Leary compared the effort to B Corp certification and organic food labels, which created reputational pressure before regulations developed. The group hopes to build similar industry expectations. Rose cited the Environmental Working Group's Dirty Dozen list as a model that influenced consumer behavior without new laws.

The Consortium's six governance commitments cover ethical standards, bias reduction, emotional and clinical quality, longitudinal intelligence, mentorship for ethical AI builders, and transparent oversight. Its governance board includes clinicians, technologists, ethicists and legal experts.

Amanda Ducach, CEO of Ema EQ, said the standards aim to ensure AI is clinically safe and culturally aware. The benchmark under development is intended to exceed current practices of member companies. " The Consortium seeks to create a shared standard based on evidence and lived experience.

U.S. courts to date when harm has occurred.

Key Facts

60% AI failure rate
across 13 models on women's health tasks
Women's Health AI Consortium
launched May 12 2026 by Willow and Ema EQ
No existing standards
for consumer-facing women's health AI
Six governance commitments
address bias, quality, ethics and oversight
75% max accuracy
in 2026 women's health clinical benchmark

Story Timeline

3 events
  1. May 12, 2026

    Coalition announces launch of Women's Health AI Consortium.

    1 sourceForbes
  2. 2026

    Follow-up benchmark finds no LLM above 75% accuracy on women's health scenarios.

    1 sourceForbes
  3. 2026

    Researchers report approximately 60% failure rate across 13 AI models on women's health tasks.

    1 sourceForbes

Potential Impact

  1. 01

    The Consortium may create reputational incentives for AI companies to adopt its standards.

  2. 02

    Increased industry focus on bias reduction in models trained on women's health data.

  3. 03

    Development of benchmarks could improve training data quality for women's health AI models.

  4. 04

    Voluntary standards may influence future legislation on AI accountability in healthcare.

Transparency Panel

Sources cross-referenced1
Confidence score75%
Synthesized bySubstrate AI
Word count384 words
PublishedMay 13, 2026, 11:04 AM
Bias signals removed4 across 2 outlets
Signal Breakdown
Framing 2Loaded 1Editorializing 1

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