🚀 Mission View
A sharper perspective on this week's issue that matters at the intersection of health and AI.
The latest Wharton AI Adoption Report offers a reality check for the moment we’re in. Across industries, the ambition for AI is sky-high, but the capability to deliver may not be keeping pace.
Nearly half of organizations now report technical skill gaps, yet investment in training has declined (–8 points), and confidence in workforce learning as the path to fluency has dropped even further (–14 points).
That stands in sharp contrast to how some leading health systems are tackling the challenge. At NYU Langone’s AI Symposium, one of the biggest takeaways was that “AI fluency isn’t optional. It’s foundational.” As Dr. Triola put it, “Everyone in healthcare will engage with AI — whether they’re building it, testing it, or using it at the bedside.”
Yes, AI’s promise rests partly on more powerful models — but even more on capable people who trust the technology and know how to use it. Fluency, not fear or fanfare, will ultimately define who shapes the future of health.
🛜 Field Signals
A quick hit on this week’s key policy shifts and industry trends.
Sam Altman bets on brainwaves, not brain surgery. The OpenAI co-founder is funding Merge Labs, a new startup using ultrasound to read brain activity — a noninvasive alternative to Elon Musk’s Neuralink implants. If it works (still a big if), brain–computer interfaces could move from the operating room to the outpatient clinic.
University partnership wins NSF grant for AI in healthcare. A consortium of universities has been awarded a grant from the National Science Foundation to establish a new Center for AI in Healthcare. The initiative will research and develop AI tools tailored for clinical settings, with a focus on data-sharing, ethics, and improving access in underserved communities.
Healthcare’s AI ROI enters its high-stakes era. Healthcare is moving past pilot projects and into scaled AI deployment, according to PYMNTS. Nearly half of industry leaders say AI agents are already in production, with many organizations running multiple systems across operations, patient experience, and clinical support. The sector’s ROI is now tied less to experimentation and more to execution, where governance, trust, and data integrity will determine which organizations turn early adoption into lasting advantage.
Insurers are ramping up AI to fight hospital AI in coding and billing ~ STAT News. Health insurers say they’re deploying more AI tools to counter what they call “aggressive” coding by hospitals, pointing to provider use of automation as a contributor to rising claims and shrinking profits.
AI steps into menopause care ~ Axios. As doctors struggle to cover complex issues like menopause in 15-minute visits, clinics are turning to AI tools to fill the gap. At Cedars‑Sinai, researchers built an AI/VR platform where patients speak with an avatar using Apple Vision Pro to navigate symptoms like hot flashes in immersive settings. Meanwhile, the app Flourish allows women to chat with an AI modeled after a specialist, get treatment suggestions (with physician approval), and prepare for clinic visits — showing early promise for evidence-based, always-on support via AI.
FAO spotlights AI’s role in global food safety. A new UN Food and Agriculture Organization report offers the first worldwide look at how AI is being deployed to protect the food supply — from lab testing to outbreak prediction. Reviewing 141 studies, including work by the FDA and U.K. Food Standards Agency, FAO found that AI’s promise depends on strong data, human oversight, and ethical guardrails. The agency urges global investment in AI literacy and governance to ensure smarter, safer, and more resilient food systems.
Senate moves to track AI’s impact on jobs. Senators Mark Warner (D-VA) and Josh Hawley (R-MO) introduced the AI-Related Job Impacts Clarity Act, a bipartisan bill that would require major companies and federal agencies to report layoffs, retraining efforts, and hiring tied to AI to the U.S. Department of Labor. The move signals rising legislative concern about AI’s workforce effects and a push for transparency as automation expands.
FDA weighs gen-AI in digital mental health. Yesterday, the FDA’s Digital Health Advisory Committee discussed a regulatory framework for generative-AI–enabled mental health devices.
🛠️ Practical Edge
Actionable tips, tools, and thoughts to help leaders strengthen capacity and apply AI in their work.
Stop trying to make one AI do everything ~ The Neuron. Some AI users aren’t “model maxxing” — they’re simple maxxing: using multiple tools, each for what it does best. Claude works great as a command center for structured prompts, Gemini shines at long-form document analysis, ChatGPT is still unmatched for web lookups, Grok rules real-time X/Twitter intel, and Google’s AI Studio excels at quick prototype builds. The takeaway: every AI product has a superpower. When a use case isn’t clicking, stop re-prompting the same model — switch tools, simplify the task, and chain the right ones together into an efficient workflow.
Becoming an AI power user. The Wall Street Journal reports that “AI power users”—employees who own and integrate AI tools into their workflows—are already gaining edge and visibility at work. These aren’t AI engineers, but everyday professionals refining prompts, training their digital assistants, and automating tasks to stand out. The lesson? Instead of treating AI as a novelty, identify one tool, build a consistent relationship, and let it catalyze your work. Consistency beats chasing every new model.
🌅 On the Horizon
A quick look at the developments and events expected to shape the weeks ahead.
Nov. 5–6: GovAI Coalition Summit 2025 in Arlington, VA.
Nov. 18-20: AI in Healthcare & Pharma Summit 2025 (RE•WORK) in Boston. Register here.
Nov. 26-27: World AI Congress, London.
Dec. 8-9: Fortune Brainstorm AI San Francisco. Apply to attend here.
Feb. 11-13: The Complexities of AI in Health Care by American Health Law Association in Las Vegas and Virtual. Register here.
⌚️ Closing Time
A parting thought on what health leaders need to be focused on.
Tech/AI author, Alberto Roberto, recently pointed out an important tension in the AI-narrative: one major study says 95% of generative AI pilots fail, while another — from Wharton (as mentioned above) — reports 75% of enterprises say they see positive ROI on gen-AI. Which one’s right? Neither, fully. Statistical extremes alone don’t tell the full story. The real insight lies in how organizations build the capabilities behind the pilot or ROI number — the skills, workflows, governance, and culture that turn potential into performance. As we’ve seen, healthcare may be ahead in adoption, but it still faces a fluency gap. So the question isn’t “Is AI working?” but “Are we working with AI in ways that last?”
Till next time,
