Month: August 2025

MIT Report Crosses the GenAI Divide

Posted on by Jason Barry

It only takes one look at the key findings from MIT’s GenAI Divide report to see why it made such a big splash this week: 95% of GenAI deployments fail.

MIT knows how to grab headlines. The paper – based on interviews with 150 enterprise execs, a survey of 350 employees, and an analysis of 300 GenAI deployments – highlights a clear chasm between the successful projects and the painful lessons.

  • After $30B+ of GenAI spend across all industries, only 5% of organizations have seen a measurable impact to their top lines. Adoption is high, but transformation is rare. 
  • While general-purpose models like ChatGPT have improved individual productivity, that hasn’t translated to enterprise outcomes. Most “enterprise-grade” systems are stalling in pilots, and only a small fraction actually make it to production.

Why are GenAI pilots failing? The report suggests that it’s not the quality of the models, but the learning gap for both the tools and the organizations that’s causing pilots to fail.

  • Most enterprise tools don’t remember, don’t adapt, and don’t fit into real workflows. This creates “an AI shadow economy” where 90% of employees regularly use general models, yet reject enterprise tools that can’t carry context across sessions.
  • Employees ranked output quality and UX issues among the biggest barriers, which both directly trace back to missing memory and workflow integration.

What’s driving successful deployments? There was a consistent pattern among organizations successfully crossing the GenAI Divide: top buyers treated AI startups less like software vendors and more like business service providers. These orgs:

  • Demanded deep customization aligned to internal processes and data
  • Benchmarked tools on operational outcomes, not model benchmarks
  • Partnered through early-stage failures, treating deployment as co-evolution
  • Sourced AI initiatives from frontline managers, not central labs

There’s always a catch. Most of the pushback on the report was due to its definition of “failure,” which was not having a measurable P&L impact within six months. That definition would make “failures” out of everything from the internet to cloud computing, and underscores why enterprise transformation is measured in years, not months.

The Takeaway

The GenAI growing pains might be worse than expected, but that’s helped startups realize that they need to ditch the SaaS playbook for a new set of rules. In the GenAI era, deployment is a starting line, not a finish line.

Medallion Lands $43M and Unveils First National Credentialing Clearinghouse

Posted on by Jason Barry

Medallion keeps building its case to be the go-to platform for provider network management after locking in another $43M and unveiling the industry’s first national credentialing clearinghouse, CredAlliance.

Less friction, more healthcare. Providers have to jump through countless operational and compliance hoops before they can start caring for patients, and Medallion specializes in AI-powered hoop jumping.

  • Medallion helps automate away the back-office workflows that delay care – and revenue – such as credentialing, enrollment, and monitoring.
  • The platform not only onboards providers 40X faster (cutting intake time from 8 days to under 2 hours), but it also serves as a unified system of record that allows customers to verify credentials, stay in-network, and connect patients to care more efficiently.

Own the market by shrinking it. There’s roughly 4M credentialed providers in the U.S., and they’re each contracted with an average of 19 payors. That adds up to about 25M times a year that providers need to get credentialed.

  • The launch of CredAlliance will allow payors to verify providers once and syndicate results, eliminating duplicative work and reducing costs for everyone involved.
  • That has the potential to eliminate $1.2B in duplicative spend annually, but it could also shrink the exact market that Medallion exists to serve. It’s a risk they’re willing to take.

What’s next? The fresh funds will bring Medallion’s AI automation to thousands of state-, provider-, and payor-specific workflows, while simultaneously scaling CredAlliance across more payors.

  • CredAlliance already has dozens of payors signed on, and it’s in talks to bring on five of the nation’s 10 largest health plans.
  • If that ends up making credentialing so efficient that there’s less of a need for automation, we’ll chalk it up as a good thing for the industry and Medallion will be just fine (enterprise ARR is up 106% in the wake of launching three new products – Privileging, Integration Engine, and CAQH Management).

The Takeaway

Medallion had a front row view of the wasteful spending in the credentialing trenches, and it raised $43M to help eliminate it with the first national credentialing clearinghouse. Bravo.

Healthcare’s Sci-Fi Future at Epic UGM

Posted on by Jason Barry

Where there’s smoke, there’s fire, and Epic just lit up its sci-fi themed User Group Meeting with enough futuristic new solutions to prove last week’s rumors true – and then some.

The future is now. This year’s event gave us a look at over 160 AI projects currently under development at Epic, including a three-product family set to immediately shake up the industry.

ART is a provider copilot for charting, pre-visit summaries, queuing up orders, and yes – ambient scribing.

  • ART will reportedly be able to provide real-time suggestions during visits, and its highly-anticipated scribe still came as a surprise after Epic revealed that it will be powered by Microsoft when it arrives in early 2026. More on that later.

Emmie is a patient-facing advocate within MyChart that can help with everything from scheduling and reminders to education and navigation.

  • Epic is positioning Emmie as the best place for patients to ask health questions and get answers that are actually grounded in their personal medical history.

Penny is an administrative assistant targeted at revenue cycle management, generating appeal letters, and supporting back-office tasks.

  • There isn’t as much information out there on this one, but Epic doesn’t appear to be shying away from claims and payor workflows.

The EHR is dead, long live the CHR. Judy grabbed even more headlines by announcing that she’s retiring the term “EHR” in favor of “Comprehensive Health Record,” which seems fitting considering the other major announcements that joined the Big Three.

  • Cosmos AI will provide diagnosis and treatment support, as well as discharge planning.
  • MyChart Central will give patients a single login across all sites of care.
  • Flower Pot will expand access to lightweight Epic implementations for smaller practices.

The scribe is real. Now what? Epic’s decision to team up with Microsoft on documentation was pretty unexpected given its 46-year track record of building everything in-house, confirming that the CHR giant would rather bend its core rules than lose market share.

  • Scribes proved how fast health systems would layer on their own AI if Epic couldn’t keep up, and we’ll now have to wait and see if the cost and experience of Epic’s scribe is enough to compete with the flock of ambient AI innovators dedicated to this problem.
  • Epic might own the “operating system,” almost as much as Microsoft owns Windows, but just because MS Paint exists doesn’t mean the world doesn’t need Adobe Photoshop.

The Takeaway

Some call it consolidation. Others call it innovation. Either way, this year’s UGM will probably go down as a key step along Epic’s march toward intergalactic domination. 

Is AI Robbing Physicians of Their Skill? 

Posted on by Jason Barry

A study in The Lancet threw some refreshingly cold water on the AI hype train after finding that healthcare’s shiny new models might be de-skilling physicians.

Here’s the setup. Researchers tracked four Polish health centers that gave their gastroenterologists AI to help spot polyps during colonoscopies before yanking it away after three months.

  • Long story short, the doctors’ ability to detect polyps plummeted 6% below baseline following the AI rugpull.
  • Unassisted polyp detection rates fell from 28.4% before the AI teaser to 22.4% after, raising concerns that relying on AI might rob physicians of hard-won skills. 

Sounds familiar. The findings echo a recent MIT preprint that showed that people who used AI to write essays used less of their brains and had worse recall of their writing than those who mustered up the words on their own.

  • That’s probably not a shocker to anyone that’s used ChatGPT for more than five minutes, but it’s easy to see that it might spell trouble when applied to medicine.
  • If gastroenterologists start leaning on AI to detect polyps, what happens if they lose their ability to detect them without it?

Right idea, wrong question. People were better at mental math before they had calculators, but that doesn’t mean society would be better off without them. The question we have to ask ourselves is, which skills are we willing to lose?

  • Gastroenterologist Dr. Spencer Dorn nails it: AI doesn’t just risk de-skilling doctors in polyp detection, it risks diminishing their overall critical thinking skills.
  • “My real concern is not the technical skills we can afford to lose, but the foundational ones we can’t: critical thinking, sound judgment, and compassionate care. These aren’t just important to preserve – they’re irreplaceable.”

The Takeaway

If doctors keep outsourcing their thinking to AI, it could be a one-way ticket to a world where Dr. GPT is the only one patients can turn to. Seems dystopian, but is it really that bad if it also means better outcomes for those patients?

AI Spotlight on Epic, Abridge, and Oracle 

Posted on by Jason Barry

Epic, Abridge, and Oracle just gave us a year’s worth of blockbuster AI announcements in three days, and at least one of them was more than speculation and old news.

‘Twas the week before UGM, and the rumor-mill has been overheating with reports that Epic might finally launch its own EHR-native scribe at its upcoming User Group Meeting.

  • Over 40% of U.S. hospitals are already on Epic, which means its scribe would have access to one of the biggest distribution channels in healthcare even if its UX and performance aren’t best-in-breed (which they won’t be).
  • That means about 100 ambient AI startups could be about to find out why scribing is a feature – not a product – and the race will be on to differentiate through other capabilities like RCM and specialty-specific tuning.

Abridge doesn’t plan on being commoditized. Less than 24 hours after Epic’s scribe leaked, Abridge unveiled the exact type of solution that’ll define who survives the incumbent squeeze: real-time prior authorization at the point of conversation.

  • Abridge is co-developing the new solution alongside Highmark Health, a Pittsburgh-based payvidor that operates both a multistate payor division and the 14-hospital system Allegheny Health Network.
  • Integrating Abridge’s ambient AI platform across Highmark’s entire organization will allow patients to get approval for necessary treatments before they even leave the office, a perfect example of how “scribes” can be truly transformative beyond just transcripts.

Oracle couldn’t let Epic and Abridge have all the fun. It decided to “usher in a new era of AI-driven health records”… by reintroducing us to the same AI EHR it unveiled last October.

  • Although mostly a PR stunt to grab headlines ahead of UGM, the new EHR includes several features that underscore where the AI puck is heading, including a native scribe, voice-first navigation, and agents to support clinical workflows.
  • These features are also a good list of use cases where startups might not have a lot of juice left to squeeze after EHRs start bringing them in-house (and prior auths just so happen to be the last thing Oracle wants to get its hands dirty with).

The Takeaway

Native scribing is (very likely) on its way to Epic, Abridge is giving patients the gift of time with instant prior auths, and Oracle is banking on voice for the future of EHR navigation. What a week for digital health.

Doximity Ramps Up AI With Pathway Acquisition

Posted on by Jason Barry

Doximity is setting out to prove that it’s more than “LinkedIn for doctors” after snapping up clinical reference AI startup Pathway for $63M. 

Clinical workflows are the new social media… or at least that’s the plot of Doximity’s growth story.

  • Act 1: Doximity’s newsfeed and networking features set the stage for pharma advertising by attracting physicians to the platform.
  • Act 2: Complementary workflow tools like scheduling, telehealth, and Doximity Dialer gave physicians a reason to stick around longer than their news sweep.
  • Act 3: The AI suite took engagement a step further with Doximity GPT and Doximity Scribe, which helped drive quarterly active users to a record 1M physicians in Q1.

Enter Pathway. The Montreal-based startup’s AI helps physicians answer questions at the bedside using information from Pathway Corpus, “one of the largest structured datasets in medicine” that spans nearly every guideline, journal, and landmark trial.

  • Pathway’s cross-linked structure reportedly allows it to understand complex drug interactions and score the strength of medical evidence, such as weighing validated clinical trials more than case studies.
  • The acquisition will bring that same “robustness” to the back-end of Doximity GPT, and the integration is already live for thousands of physician beta testers.

If you can’t beat ‘em, buy ‘em. It’s tough for physicians to see your pharma ads if they’re not using your platform, so Doximity is acquiring its own workflow solutions to keep users from venturing off to use competing products from OpenEvidence or Wolters Kluwer. 

  • Clinicians have also apparently been using Doximity GPT outside of office hours more than Doximity’s other tools, which helps with serving ads around the clock.
  • Doximity’s AI suite and workflow modules already account for over 20% of its ad revenue, and it now expects that share to overtake its newsfeed in the next few years.

The Takeaway

Doximity is looking to make AI the star of its next act, and if OpenEvidence doesn’t want to share its script, then Pathway will have to steal the show.

The Generalist-Specialist Paradox of Medical AI

Posted on by Jason Barry

Technological advances have ushered in an era where many AI models outperform specialists on specific tasks, but AI still lags far behind experts in less controlled settings.

That’s the Generalist-Specialist Paradox of Medical AI laid out in a recent NEJM AI editorial, which paints a picture of a world where AI might soon start redrawing the boundaries of medical specialties as they exist today.

  • AI is already delivering great results on well-defined tasks like interpreting EEGs or CT scans, but it’s still consistently struggling on generalist tasks with less clear boundaries.
  • If that trend continues, the article argues that tasks that used to be in the hands of specialists will be at the fingertips of primary care (just as tasks that used to belong to primary care will now belong to patients).

LLMs don’t care what specialty a case belongs to. They can ingest the full clinical context across visit notes, labs, and imaging to come up with the most probable diagnosis.

  • Breyer Capital Partner Dr. Morgan Cheatham recently made the case that this feature of AI could lead to the collapse of traditional medical specialties as we know them.
  • “Some domains will converge. Others will splinter into new subspecialties defined not by organ systems, but by data fluency, workflow design, or model supervision.”

Not so fast. There’s no doubt that AI will reshape roles, but that doesn’t mean that specialists are about to start offloading everything onto generalists.

  • High-quality care requires more than following AI-friendly guidelines, and specialists incorporate judgment earned through years of experience to deliver effective treatments. LLMs are also still a ways away from replacing anyone’s hip.
  • Primary care providers also aren’t exactly sitting around looking for extra work, and it’s far-fetched to think that they can start taking on specialty care for their ever-growing patient panels.

The Takeaway

AI might be great at well-defined tasks like many seen in specialty care, but we’re still a ways away from having primary care physicians replacing cardiologists.

Ambience Healthcare Joins Unicorn Club With Series C Raise

Posted on by Jason Barry

Another week, another ambient AI mega-round – this time from none other than Ambience Healthcare and its massive $243M Series C.

Welcome to the unicorn club. The round vaulted Ambience’s valuation to $1.25B, making it the second-highest valued startup in the ambient arena behind Abridge, which was valued at an eye-popping $5.3B during its recent $300M Series E.

  • Funnily enough, a16z led both rounds. We don’t usually see VCs cut a check for a startup then turn around and fund their biggest competitor, but playing both sides is a great way to not lose a race.

Ambience isn’t just a scribe. It’s an ambient AI platform for documentation, coding, and clinical documentation integrity.

  • The platform was “architected with the understanding that health systems are not monolithic enterprises” and adapts to the unique context of different care settings.

If you ain’t first, you’re last. Ambience was one of the only ambient AI players to lean in on the revenue cycle component right out of the gate, and the head start is reflected in the results from head-to-head pilots.

  • During a six month bake-off at Cleveland Clinic (now a happy customer), Ambience saw 80% clinician utilization and an NPS of 60, both the highest by a wide margin.
  • Ambience Co-Founder Nikhil Buduma told us that the secret sauce is the platform’s ability to make clinicians feel like “it’s almost reading their minds,” which is made possible by continuous fine-tuning the model for individual specialties.

Where do we go from here? If the launch of Doximity’s free scribe taught us anything, it’s that documentation is officially a commodity. Ambience’s new funds will help it do everything else.

  • That includes diving deeper into the revenue cycle and clinical trials, as well as moving upstream into taking care of patients outside of the four walls of the clinic.
  • It also includes scaling up operations, and Ambience has already begun hiring dozens of former startup founders to lead its new verticals.

The Takeaway

We’re now in a world where perfect transcripts are table stakes, which means the winners of the ambient AI race will be the companies that can help carry the tasks happening after the clinical conversation. Ambience just bulked up to do some heavy lifting.

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