🗞️ Nurses Don't Trust AI Yet, Mayo + Abridge Makes a Case for Why They Should

Team Huddle

What sounds worse: Emesis oration or word vomiting? Either way, I’ve been yapping into claude incessantly to organize my thought and create content for you all. There’s just so much to talk about! Once Part 3 (final) article of the Wound Care Software series comes out, we move forward to the Nurse Founded Company research i’ve been working on. 🤭

But I am not the only one with knowledge to share. If you are a Nurse leading in Healthcare, Technology, or Innovation and would like to be featured as a guest writer, email me! RN Forward is a safe place where Nurses can establish thought leadership and I believe we all have something important to share.

Now what i’d like to share for the month in ….

News Nurses Need to Know

1. McKinsey surveyed 500+ nurses on AI. The results are a case for systemic change, of which YOU can be apart of.

   • THE DEETS: McKinsey released a survey of more than 500 US nurses on AI adoption, and the headline is that we're using AI more than we were a year ago but not in any way that has actually changed how nursing works. Nearly 65% of nurses report using more AI tools than they did last year, but only about 2% say AI is embedded in everything they do. The majority of us are somewhere in the middle: aware of it, occasionally using it, but not transformed by it.
     
     

     The barrier isn't knowledge anymore. In 2024, lack of training ranked as the third most common concern among nurses. By 2025, it dropped to sixth. What replaced it: trust in AI accuracy (33%), lack of human interaction (18%), and data privacy (16%). Nurses aren't scared of the technology. We just don't trust it yet, and we have good reasons not to.

     
     Where AI is actually getting used is predictable: documentation and medication management, the structured, repeatable workflows where AI has the clearest value proposition. The more complex stuff like scheduling, workforce optimization, patient engagement, is lagging. The gap between average users and what McKinsey calls "superusers" is largest in exactly those high-stakes areas like medication management and clinical decision support, where superusers engage with AI 77% of the time versus 27% for everyone else.
     
     

     Care setting matters too. Acute care hospitals have a 5% superuser rate. Physician practices are at 21%. While physician practices have more straightforward charting workflows and more control over their own tech stack, hospital nurses have neither.
     

   • WHY IT MATTERS: The McKinsey framing is actually pretty honest about what the problem is, and it's not us. The language they use is "system-level enablement," which in plain terms means hospitals and health systems haven't built AI into nursing work in a way that makes it worth using. Individual nurses adopting AI on their own initiative isn't going to move the needle. The report explicitly calls for workflow redesign, role redesign, and governance — things that only leadership can act on.
     
     Nurses are not resistant to AI. We are specifically skeptical of whether the outputs are accurate, and that is an entirely reasonable clinical position for a nurse to hold. The answer to that isn't more cheerleading about AI's potential. It's evidence, transparency about how the tools work, and governance that makes clear who is accountable when something goes wrong. How each employer is handling that remains to be seen. However, I can tell you that I only know of 1 Nurse Leader outside of traditional “nursing executive ladders” who has the power to influence decision making. 🥲

2. Mayo Clinic and Abridge are have been co-building ambient documentation for nursing, and made a ✨fancy✨ video for nurses week about it.

   • THE DEETS: Abridge announced a co-development partnership with Mayo Clinic to build ambient documentation specifically for nursing workflows. They’ve been piloting with Mayo for a while now so it’s nice to see the partnership continue. The basic idea: as nurses do assessments and talk with patients during care, the system securely captures those conversations and converts them into structured draft documentation in the EHR. Instead of charting after the fact, nurses review and finalize what was already discussed in real time. Video demo: here. On the initial pilot units, use was optional. Between 80% and 100% of nurses adopted it within the first few days. When access expanded to 200 additional users, most slots filled within the first hour.
     
     Mayo's Chief Nursing Officer Ryannon Frederick described the design philosophy as "for nurses, by nurses," with frontline nurses involved in identifying the problem, shaping workflows, and testing outputs from the beginning. Abridge framed it the same way but by way of a expertly produced video because they got that money money now.
     

   • WHY IT MATTERS: Ambient AI documentation for physicians has been a thing for a couple of years now but last year I noticed an uptick on hiring Nurse Scientist at leading ambient scribing companies. I actually bombed an interview for one of those spots. 😅 They finally figured out that nursing documentation is structurally different from physician notes so its nice to see them prioritizing nurses building for nurses. The 80 to 100% voluntary adoption rate is the proof of concept. What makes this worth watching is how this co-design piece plays out.
     
     This also connects directly to what the McKinsey data shows: documentation is where AI adoption is highest for a reason. It's a concrete, immediate pain point with a clear before and after. The cognitive load of remembering to chart everything later is real and constant. Anything that moves that burden into the background of care rather than interrupting it is going to get used.

3. States are starting to regulate how healthcare companies use AI to set prices.

   • THE DEETS: A growing number of states are passing legislation targeting AI-driven and algorithmic pricing, and healthcare companies are explicitly in scope. New York's Algorithmic Pricing Disclosure Act has been in effect since November 2025, requiring any entity using personalized algorithmic pricing to disclose it clearly to consumers.
     
     California's AB 325 took effect January 1, 2026, targeting anticompetitive algorithmic pricing practices under antitrust law. Connecticut passed similar legislation the same day. Pennsylvania and Tennessee both have bills pending.
     
     The laws vary in structure but share a common target: pricing decisions made by AI or machine learning models that use personal data to set individualized prices. In healthcare, the areas most directly implicated are insurance premium pricing, hospital dynamic pricing tools that factor in competitor rates and supply and demand, and direct-to-consumer health services like telehealth platforms that adjust fees based on user behavior.
     

   • WHY IT MATTERS: Algorithmic pricing in healthcare shows up in your patients' bills, in how telehealth platforms charge them, in how insurance companies set premiums. When an AI model is factoring in someone's zip code, claims history, and utilization patterns to decide what they pay, that has direct clinical consequences. People delay or skip care when it costs too much, and we see that at the bedside (especially in the ED) before anyone else does. Our health system cannot handle additional over crowding.

     
     The legislation is also a signal about where regulatory attention is heading. If you work for a health system, a digital health company, or a telehealth platform that uses any kind of dynamic pricing, your employer is going to be navigating this. For bedside nurses in states where protective legislation is in place, tell your legislators about it. 🗣️Then use this information to education the public and patients that this is a problem. Nurses who understand the regulatory environment around the technology they work with are better positioned to educate and ask the right questions.

4. The clinical decision support space just got a lot more interesting, and they’re probably going to target nursing next.

• THE DEETS: If you're not following what's happening in AI clinical decision support (CDS) tools, now is a good time to catch up because the landscape shifted significantly in the last six months.
  
  The category has historically been dominated by UpToDate, the gold standard for evidence-based clinical reference since the 90s. It still is in terms of brand trust and content depth. Wolters Kluwer launched UpToDate Expert AI in late 2025, a conversational AI assistant grounded in its editorial corpus, at around $530 per year for individual access with institutional licensing available.
  
  Then there's OpenEvidence, which has grown faster than almost anything in recent healthcare tech memory. As of early 2026, roughly 430,000 US physicians are registered users, the platform reports over 8 million clinical consultations per month, and it raised $250M in January 2026 at a $12B valuation. It recently announced an enterprise partnership with Mount Sinai that embeds it directly into Epic across physicians, nurses, and pharmacists, one of the first enterprise deployments explicitly described as “covering the full clinical team”. It's free for verified clinicians, funded by pharmaceutical ads. They also recently pulled out of the UK and EU markets due to regulatory uncertainty.
  
  Vera Health, a Y Combinator-backed San Francisco company, is the newer entrant getting the most attention right now. It searches over 60 million peer-reviewed papers, guidelines, and care pathways before generating an answer, with every key statement linked back to its source. Multiple third-party evaluations now rank it ahead of OpenEvidence on clinical accuracy and evidence transparency. It's free for licensed clinicians and trainees.
  
  Doximity, which most of us know as the physician professional network, acquired a company called Pathway Medical and now offers DoxGPT with peer-reviewed clinical answers and 3,200+ drug monographs. Free, but built primarily for physicians.
  
  Other players include Glass Health, Epocrates, and Dynamap.
  

• WHY IT MATTERS: I love me a CDS tool. I’ve proposed building a Code Blue and Wound Staging one at both hackathons i’ve participated in. Most of the current CDS tools are built for physicians, marketed to physicians, and verified by physicians. However a plethora of problems within the nursing workflow can be solved with CDS tools too. However, convincing payers to fund the development of these tools will be trickier because nurses do not generate revenue. Im keen to see what financial levers companies pull to decision makers to invest in nursing tools. We know that the reducing workforce burn out is a common one thats often cited, but I am ready to see more creative levers pulled.
  
  The CDS research horizon is worth watching too. Google DeepMind just published findings on its AI co-clinician project, which in head-to-head physician evaluations outperformed two widely used AI clinical tools across 98 primary care queries, with zero critical errors in 97 of those cases. It's not a product yet, and Google is still in early health system partnership discussions for real-world evaluation. But my crystal ball is clear: clinical AI is moving from search tool to active member of the care team. 🔮

Funding Announcements

💸 = Hiring potential. Follow these companies closely to see Nurse-qualified positions posted. Remember: Just because some positions don’t say “Nurse”, doesn’t mean you aren’t qualified!

• Enzo Health, an AI platform for home health agencies, raised a $20M Series A. The company works with agencies serving 500,000 patients a year and has grown revenue 40x in the last 24 months. Expanding into skilled nursing and hospice next — nurse-qualified roles incoming.)

• Aidoc, an AI imaging platform deployed across 2,000 hospitals, raised a growth equity round ($150M).

• Koda Health, an advanced care planning software platform, received an additional investment from UPMC as part of its recent $7M Series A.

Other Notable Reads and Podcasts

On The Blog ✍️

A 👏🏻 Nurse 👏🏻 did 👏🏻 THAT!

Zach Smith, BSN, RN, the nurse product lead who built NurseGrid into the most widely downloaded nurse scheduling app in the country before it was acquired by HealthStream, just launched a company. GownCard is a collaborative knowledge platform for OR teams that uses AI to capture and centralize surgeon preferences, procedural details, and institutional workflow knowledge into something the whole team can actually access and search. GownCard launched with pilot partnerships at two multi-hospital health systems and pre-seed funding from Hashed Health.

Smith co-founded it with Dr. Alex Langerman, a Vanderbilt surgeon and the founder of ExplORer Surgical, which was acquired by GHX. A nurse and a surgeon building OR infrastructure together. That's the kind of founding team that knows what the room looks like from both sides of the (OR) table. *badum tss*

Forward Nursing: Innovation Opportunities 🏃🏻‍♀️

Round-up of grants and career development opportunities i’ve come across that can help nurse innovators like YOU! (Not sponsored or affiliated with RN Forward.)

• Treehub by AI Health Fund’s 2026 Summer Residency

  • TBH: A healthcare AI accelerator backed by the Wojcicki family with a small cohort model and 1:1 support. If you have a healthcare problem you want to solve and you're in the pre-idea or research phase, this is worth a lookie loo. Nurses with domain expertise and a problem worth solving are exactly who programs like this should be funding.

  • When: Cohort starts June 2026

  • Cost: $50K for 3% equity or $100K for 5% equity on a SAFE, plus $50K uncapped SAFE for programming costs

  • Eligibility: Individuals or teams welcome. Pre-idea and research-phase founders accepted. Academic affiliations encouraged but not required.

  • Due Date: May 15, 2026 (TODAY GET IT DONE)

  • Apply here

• Doximity Fellows Program 2026–2027, Editorial Tracks

  • TBH: Three editorial tracks open to NPs and CRNAs: Clinical Cases (build interactive clinical teaching content), Op-Med (write thought leadership with editorial support), and Original Videos (create short-form clinical content distributed to 3M+ clinicians). You get mentorship, national distribution, and $2,000 in Doximity RSUs upon completion. If you've been wanting to build a clinical voice or get more involved in shaping the tools we use, this is a structured way to do it.

  • When: July 1, 2026 – June 30, 2027

  • Where: Remote

  • Cost: Free

  • Eligibility: NPs and CRNAs (licensed or in training). Active Doximity membership required.

  • Due Date: June 8, 2026

  • Apply here