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<td><span style="font-family:Helvetica, sans-serif; font-size:20px;font-weight:bold;">Health Tech | Fierce Healthcare</span></td>
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<td><a href="https://www.fiercehealthcare.com/providers/womens-health-sector-could-grow-600b-industry-2030-new-report-says" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Women's health could grow to $600B sector by 2030: PwC</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Mar 20th 2026, 13:44</div>
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<p><div class="col content" morss_own_score="5.214953271028037" morss_score="49.048286604361365">
<p>The global women’s health sector could reach $600 billion by 2030, but, when factoring in underdiagnosed conditions and new digital and consumer-directed models, the opportunity could be even larger, according to PwC.</p>
<p>A new <a href="https://www.pwc.com/us/en/industries/health-industries/library/assets/pwc-2026-future-of-womens-health.pdf">analysis</a> (PDF) found the current global market for women’s health is estimated to be between $430 billion and $440 billion, representing a 6% to 8% annual growth rate by 2030.</p>
<p>Moreover, the market for core women’s health—from gynecological conditions to oncology—is currently estimated at $195 billion to $205 billion and projected to reach $270 billion to $280 billion by 2030.</p>
<p>Women’s health currently accounts for approximately 5% of total healthcare research and development and investment funding despite comprising roughly half of the population, researchers said, citing a January 2026 <a href="https://www.weforum.org/publications/women-s-health-investment-outlook-2026/">World Economic Forum</a> report.</p>
<p>“The gap is not simply one of equity; it can reflect a structural inefficiency in how healthcare markets have been defined and funded,” the report said.</p>
<p>Researchers say a “broader lens” should be applied when defining women’s health to include conditions unique to women, those that affect women differently and those that disproportionately affect women.</p>
<p>Expanding the definition, according to researchers, not only shows women's necessary lifetime continuity of care but also “reframes women’s health as a longitudinal market opportunity rather than a set of episodic events.”</p>
<p>Between 2020 and 2025, nearly $60 billion was invested across the women’s health sector, per the report. While investments have initially focused on reproductive care, researchers say funding has previously overlooked areas, with women’s oncology and menopause advancing as top areas for growth.</p>
<p>As spending increases, researchers estimate the following growth year over year for respective industries through 2030: </p>
<ul><li>Consumer technology: 14% to 17% annually</li><li>Pharmaceuticals: 8% to 10% annually</li><li>Payer and employer: 8% to 10% annually</li><li>Provider and care delivery: 5% to 7% annually</li><li>Device and diagnostic: 4% to 6% annually</li></ul><p>Researchers note new revenue sources may also be created with better identification of underdiagnosed conditions, scale of digital and artificial-intelligence-enabled models and expanded sex-specific research and development.</p>
<p>“Healthcare leaders who act early can help define the future of women’s health,” the report said. “In doing so, they may unlock one of the more consequential value creation opportunities in modern healthcare.”</p>
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<td><a href="https://www.fiercehealthcare.com/health-tech/verily-banks-300m-accelerate-ai-roadmap-transitions-independent-company" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Verily banks $300M to fuel AI road map, separates from Alphabet</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Mar 20th 2026, 13:44</div>
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<p><div class="col content" morss_own_score="5.274193548387097" morss_score="71.92075392337884">
<p>Verily raised a $300 million investment round to accelerate its work in artificial intelligence and precision health as it also moves out from under the corporate umbrella of Alphabet.</p>
<p>The massive round was led by Series X Capital and includes an investment from Alphabet, which will remain a significant minority investor but will no longer have a controlling stake in the company, Verily said in a press release.</p>
<p>Verily transitioned its legal structure from an LLC to a corporation and changed its name to Verily Health.</p>
<p>“At Alphabet, we applaud Verily’s tenacity in using technology to address longstanding challenges in the healthcare industry,” said Ruth Porat, president and chief investment officer at Alphabet and Google, in a statement. “Bringing in new investors, alongside Alphabet’s ongoing involvement, enables Verily to further scale the business to help improve patient outcomes and lower the cost of healthcare delivery through their AI health platform.”</p>
<p>UCHealth and the University of Colorado Anschutz also became investors, the company said. Verily has built deep ties with the health system and the academic medical institution through <a href="https://www.fiercehealthcare.com/ai-and-machine-learning/verily-inks-tech-and-research-collaboration-uchealth-university-colorado">tech and research collaborations </a>announced last October.</p>
<p>“Partnering with Verily to bring a shared data framework to healthcare data, making it AI‑ready, creates a generational opportunity for UCHealth and for medicine,” said Richard Zane, M.D., UCHealth chief medical and innovation officer, in a statement. "This collaboration helps unlock the long‑promised potential of personalized care, benefiting our patients and, ultimately, all patients. It will save lives, and we’re eager to get started.”</p>
<p>Launched in 2015, Verily began as a moonshot of Google X, and, as an Alphabet subsidiary, the company evolved into a data platform and AI company focused on precision health. In the past three years, Verily, once a sister company to Google, sharpened its focus on digital precision medicine and clinical research platforms.</p>
<p>The company developed Verily Pre, a precision health platform that serves as the data and technical foundation for all Verily solutions. Last fall, it launched a free consumer health app, called <a href="https://www.fiercehealthcare.com/health-tech/verily-rolls-out-consumer-app-free-health-guidance-ai-agent">Verily Me</a>, to connect patients with personalized care recommendations based on their health data. The app is intended to identify care gaps and provide tailored health recommendations, Verily executives said, and it includes an AI agent, Violet, to answer questions users have about their health records.</p>
<p>"From research to care, our customers need solutions that bring the best of clinical and scientific rigor together with AI to deliver the next generation of healthcare—one that is as precise as it is personal. Series X Capital, Alphabet, UCHealth, the University of Colorado Anschutz and our many investors will be fantastic partners in this transformation of healthcare," Stephen Gillett, chairman and CEO of Verily, said in a statement.</p>
<p>Verily is laser-focused on building and scaling AI models and agents for research and care workflows. On the clinical side, it has developed <a href="https://www.fiercehealthcare.com/health-tech/ahip-2024-verily-unveils-new-chronic-care-platform-called-lightpath">Lightpath</a>, a chronic disease and weight loss management program subsidized by employers, payers and pharmacy benefit managers. It also has built innovations for public health, such as Sightline, a wastewater-based epidemiology program for <a href="https://www.fiercehealthcare.com/providers/hlth24-verily-monitors-vegas-wastewater-infectious-disease-insights">early detection of infectious diseases</a>. </p>
<p>The $300 million investment will fuel the company's work in AI and precision health including expanding Verily Pre and Verily Me capabilities, launching new agents and driving new commercial opportunities globally, executives said.</p>
<p>"This means further investment in Pre data solutions such as Workbench, which already powers the NIH’s All of Us Research Program, supporting over 21,500 researchers worldwide. It means expanding capabilities for Sightline, an essential solution for nationwide monitoring of infectious disease, and growing Lightpath to help more people manage the day-to-day realities of diabetes and hypertension with tailored care and always-on support," Gillett wrote in a <a href="https://verily.com/perspectives/our-next-chapter-verily-health">blog post.</a></p>
<p>"On the clinical research side, it means further growing our Viewpoint Evidence tools to run real-world studies, using our registry of re-contactable participants, Refinery for health data harmonization, and Workbench for multi-modal data analysis," Gillett wrote.</p>
<p>Verily, a <a href="https://www.fiercepharma.com/fierce-50/verily?linkId=16695631">Fierce 50 of 2025 </a>company, also has been growing its commercial partnerships. In a collaboration with Samsung, the two companies are integrating sensor data from the Galaxy Watch 8 into Verily’s Pre platform to support real-world research and population health monitoring. Verily also <a href="https://www.fiercehealthcare.com/ai-and-machine-learning/salesforce-partners-healthex-verily-and-vizai-build-out-healthcare-ai">teamed up with Salesforce</a> to integrate its precision health platform with Agentforce for Health "to help providers make sense of messy medical data," Gillett said in the blog post.</p>
<p>Further, Verily is <a href="https://www.fiercehealthcare.com/ai-and-machine-learning/verily-innovaccer-and-diligent-robotics-tap-nvidias-ai-tech-stack">working with Nvidia</a> to integrate its AI technology stack into its Pre platform to speed up research and analysis and accelerate the development of AI agents and models for clinical care and research.</p>
<p>In the blog post, Gillett acknowledged that Verily's evolution as a business "hasn't been a linear journey."</p>
<p>In early 2023, Verily began to pull back from the many different areas of the healthcare sector in which it once played to better tailor its bets on becoming a more profitable company, Fierce Medtech's Conor Hale <a href="https://www.fiercebiotech.com/medtech/conversation-verilys-medical-science-chief-andrew-trister-companys-narrowed-focus">reported</a>.</p>
<p>Once known for tackling everything from smart contact lenses and wearable sensors to surgical robotics and virtual clinics, Verily shifted to a slightly-more-centralized stated goal: to focus on products that enable precision in medicine.</p>
<p>"Over the last few years, we’ve gone through a deliberate—and honestly, sometimes difficult—transformation. We had to make hard calls about where to double down and where to let go. But that work fueled the focus that was needed to launch innovative solutions like the Verily Pre platform," Gillett wrote in the blog post.</p>
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<td><a href="https://www.fiercehealthcare.com/ai-and-machine-learning/industry-voices-stop-buying-ai-tools-start-designing-ai-architecture" style="font-family:Helvetica, sans-serif; letter-spacing:-1px;margin:0;padding:0 0 2px;font-weight: bold;font-size: 19px;line-height: 20px;color:#222;">Industry Voices—Stop buying AI tools, design AI architecture</a>
<div style="font-family:Helvetica, sans-serif; text-align:left;color:#999;font-size:11px;font-weight:bold;line-height:15px;">Mar 20th 2026, 13:44</div>
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<p><div morss_own_score="2.9151193633952257" morss_score="79.41511936339523"><p>Health systems and payers are entering a new era of artificial intelligence adoption—but their buying strategies haven’t caught up yet given how fast the technology and market are moving. Many are still purchasing AI the same way they bought software a decade ago: one tool, one use case, one department at a time. </p>
<p>The result in today’s fast-moving market ends up being a mishmash of vendors, pilot purgatory, mounting integration complexity and unclear return on investment.</p>
<p>To move past experimentation into enterprise‑scale deployment, healthcare leaders must rethink how they evaluate, procure and govern AI across their organizations. That shift requires moving beyond point‑solution evaluation toward intentional system design. Increasingly, buyers are no longer asking whether a solution works, they’re asking where it fits, what it depends on and how it compounds value over time. </p>
<p>AI can no longer be treated as an application decision; it needs to become an architectural one. Leaders must stop evaluating tools in isolation and start designing a cohesive enterprise AI architecture.</p>
<p>Organizations have the potential to find success through a new framework for AI procurement, one that recognizes three distinct layers: core enterprise platforms, foundation model platforms and specialized context-aware, use‑case innovators. For startups, this architecture view is no longer optional as they think through their go-to-market strategies. It is quickly becoming the lens through which enterprise buyers evaluate relevance, durability, moats and long‑term strategic fit.<br> </p>
<h3>Layer 1: Core infrastructure and enterprise platforms<br> </h3><p>Core infrastructure and cloud platforms now form the foundation of the healthcare enterprise stack, led by hyperscalers such as Microsoft Azure, AWS and Google Cloud. These providers deliver the compute, storage, security primitives and data services that underpin modern AI capabilities. Sitting on top of this infrastructure layer are longstanding systems of record and enterprise application vendors—most notably Epic, along with platforms like Workday, ServiceNow and Salesforce—which continue to serve as the digital backbone of most healthcare organizations.</p>
<p>Together, these vendors increasingly embed AI directly into the enterprise stack, leveraging privileged access to data, workflows, identity and compliance frameworks that health systems and payers already trust. Hyperscalers in particular are becoming foundational not just as infrastructure providers, but as policy‑setting actors defining how data can be stored, moved and secured and, increasingly, how AI workloads are governed at scale.</p>
<p>For startups, this layer defines the gravitational center of the enterprise. Core platforms and cloud providers shape procurement constraints, deployment patterns and architectural boundaries long before a point solution is evaluated. They determine where data live, how models are accessed and what “enterprise‑ready” actually means. While this layer offers the lowest‑risk adoption path for buyers, it compresses opportunity for vendors whose value propositions overlap too closely with native functionality or cloud‑embedded services. Startups that fail to account for this reality risk being sidelined by platform evolution rather than displaced by direct competitors.<br> </p>
<h3>Layer 2: Foundation model platforms<br> </h3><p>The emergence of foundation model platforms introduces both opportunity and strategic tension. New offerings such as OpenAI’s Frontier and Anthropic’s Cowork point toward a future where enterprises can operate secure, organization‑specific AI environments that sit between core systems and end‑user applications. And these offerings are becoming more and more woven into the Layer 1 infrastructure (e.g. Microsoft’s recent Copilot Cowork announcement that is powered by Anthropic’s Cowork offering).</p>
<p>These platforms function as orchestration layers, enabling custom application development, centralized governance, reusable prompts and workflows, and controlled access to proprietary data. For startups, this layer could increasingly represents the control plane of enterprise AI. Products that align with it—rather than attempt to bypass it—may benefit from faster procurement cycles, deeper enterprise embedding and clearer paths to scale.</p>
<p>At the same time, foundation platforms raise existential questions. If they become the default operating system for enterprise AI, startups must decide whether they are building on top of, alongside or in competition with them. That choice has implications for product architecture, deployment models, data ownership and even pricing strategy. Startups that fail to articulate this positioning clearly may struggle to earn enterprise trust, regardless of model performance.<br> </p>
<h3>Layer 3: Specialized AI startups<br> </h3><p>There remains an expanding universe of AI startups attacking discrete operational pain points—from prior authorization and claims management to revenue cycle optimization and clinical documentation. Many of these companies deliver fast, measurable ROI and solve problems that core vendors are slow to address.</p>
<p>But the bar is rising. Enterprise buyers are increasingly evaluating Layer 3 solutions not just on functionality, but on architectural compatibility. How does this product integrate with core platforms? Does it leverage foundation model environments already approved by the organization? Can it scale without introducing fragmentation, redundant infrastructure or governance risk?</p>
<p>As Layers 1 and 2 mature, startups that succeed will be those that position themselves as architectural complements rather than isolated tools. Integration strategy, data boundaries, security posture and governance alignment are becoming as important as algorithmic sophistication.<br> </p>
<h3>The strategic imperative<br> </h3><p>Healthcare AI procurement is no longer about picking winners one use case at a time. It’s about orchestrating across layers—aligning enterprise platforms, foundational capabilities and specialized applications into a coherent system that can evolve.</p>
<p>This shift demands a new level of enterprise awareness from startups. Winning vendors will understand not just their buyer’s problem, but their buyer’s stack. They will design products that slot cleanly into existing and emerging enterprise architectures and communicate that fit with clarity and discipline.</p>
<p>Healthcare’s digital frontier is no longer about whether to adopt AI, but how to organize it. Procurement strategy has become a core enterprise capability. The ability for startups to understand where they fit within that strategy may determine whether they scale, stall or disappear.</p>
<p><em>Keith Figlioli is managing partner at LRVHealth, a venture capital platform that invests in technology-based businesses in the healthcare sector on behalf of health systems and payers.</em></p>
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<p><strong>Forwarded by:<br />
Michael Reeder LCPC<br />
Baltimore, MD</strong></p>
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