The Companies Behind Nursing’s AI: The Vendor Landscape

Part of Nurse.org’s Nursing AI Watch, our ongoing investigation into how artificial intelligence is reshaping nursing practice. In this piece we look at the companies actually supplying that AI — and the finding that the market appears to be consolidating around a very small group of vendors, most of them running inside one electronic health record.

AI is everywhere in healthcare, but the AI showing up in nursing workflows comes from a surprisingly small group of companies. We tracked who they are, which vendors appear to lead, and why the concentration matters for the nurses who have to use these tools every shift.

Of the 127 deployments we could confirm across 106 large health systems, the picture that emerges isn’t a crowded, competitive market. Instead, it’s a short list with two names at the top, most of it running inside a single electronic health record, and a long tail of smaller vendors splitting what’s left. That concentration has real consequences, such as if (and how) nurses get consulted about tools, who sets the terms when something goes wrong, and whether the market is moving toward nurses or just toward hospitals.

Want to see more Nurse.org articles in your Google results? Add us as a preferred source.

We identified 127 AI deployments across 106 large health systems. 

Abridge anchors the list with 40 deployments. Microsoft’s Dragon Copilot follows with 28. Together, those two companies account for at least 68 of the deployments we could confirm, totalling over half of what we found.

After the top two, the numbers drop off fast. Here’s how the vendors stack up by deployment count in our dataset:

Source: Nurse.org’s Nursing AI Watch database

The pattern is clear. Most of the existing AI deployments that nurses touch are aimed at charting. Of the 127 deployments, 76 are ambient documentation tools, the scribes that listen to a visit and draft the chart. We’ve covered how these tools work with our look inside Epic’s AI nursing charting tools, and the same vendors keep coming up.

A Closer Look at the Two Dominant AI Vendors

Because these two companies sit behind most of the deployments we found, they’re worth understanding in a little more detail.

• Abridge is a clinical AI company focused on ambient documentation; its tool listens to a patient conversation and drafts a structured clinical note for the clinician to review and sign. It integrates directly with Epic and has been adopted across a number of large health systems in our dataset, including academic medical centers. Its concentration in our data is heaviest in the ambient-scribe category, which is also the fastest-growing use case overall.
• Microsoft Dragon Copilot is Microsoft’s ambient clinical documentation tool, built on the long-running Dragon voice-recognition line and Nuance’s healthcare technology (Microsoft acquired Nuance in 2021). Like Abridge, it drafts notes from a recorded encounter and plugs into the major EHRs. Its 28 deployments in our dataset make it the second most common AI tool we found in nursing settings.

A note on what these counts do and don’t say: they reflect deployments we could confirm from the public record, in the systems we track. They are not a measure of total contracts signed or national market share, and the “deployment” label covers a range of scopes, from enterprise-wide rollouts to single-facility pilots.

A market with two dominant vendors isn’t unusual in healthcare technology. But it has real consequences for nurses.

When a handful of companies supply most of the tools, they also tend to set most of the terms. Pricing, feature roadmaps, accuracy standards, and how the tool handles your documentation are shaped by a few vendors, not by the nurses entering the data.

Concentration also shapes bargaining power. A health system negotiating with one of two market leaders has less leverage than one shopping a crowded field. That pressure can flow downhill to staff, in how much say nurses get over which tool lands in their workflow and how it’s rolled out.

The flip side is consistency. A smaller set of vendors means clearer comparisons and a more predictable set of risks to watch. But consistency only helps if the dominant tools are actually good, and that’s a question worth asking before, not after, a system signs.

“As someone who has worked in both clinical practice and healthcare technology leadership, I believe the future of AI in healthcare depends on maintaining a balance between innovation and evidence-based, patient-centered care,” notes Danielle K. Miller, DNP, RN, a healthcare consultant and nurse executive from Chicago, Illinois. 

The leaders are also racing to go deeper into nursing specifically. In June 2026, Ambience Healthcare announced an AI-native inpatient nursing suite — described as the first inpatient nurse-specific ambient documentation suite — adding nurse-shift summaries and ambient flowsheet documentation to its existing nursing tools.

The shift is a sign that the top vendors are building for nurses directly, not just physicians, which, in a concentrated market, means a handful of companies increasingly shape the nursing-specific tools too.

The vendor story doesn’t stop at the AI companies. It runs through the EHR underneath them.

Of the 106 systems we track, 95 run on Epic. Four use Oracle Health, one uses Meditech, one runs Oracle Health/VistA, one runs both Epic and Oracle, and four are unconfirmed. That means nearly all of the AI we found is being deployed inside a single electronic health record ecosystem.

It’s important to be precise about what that 95 means. It describes the systems we track, which skew toward large and academic health systems, where Epic’s footprint is especially heavy. Nationally, Epic’s share of the acute-care hospital EHR market is smaller: KLAS Research data reported by Becker’s Hospital Review put it at roughly 43.7% in 2025. So the right read is not “Epic owns 94% of the market”;  it’s “95 of the 106 systems we happened to track run on Epic, so Epic is the clear national leader.”

Even with that caveat, the dependency is real for the systems we track. When most ambient scribes and clinical tools plug into one EHR, that platform effectively gatekeeps which AI gets deployed, how it integrates, and how data moves. A change in Epic’s strategy or partnerships could ripple across most of those systems at once.

>>Listen to The Latest Nurse News Podcast

Here’s where the vendor landscape needs an honesty section, because not every “deployment” you read about is actually confirmed.

Vendors have every reason to publicize wins. A press release announcing a marquee health system is good marketing. But a marketing announcement isn’t the same as independent evidence that a tool is deployed in real, clinical use. In our tracking, a deployment counts only when there’s public evidence — ideally from a source independent of the vendor — that the tool is actually being used somewhere in the system.

Two specific examples show why that standard matters:

• UPMC and Abridge. You may see UPMC named alongside Abridge, but we do not currently count it as a confirmed deployment. The strongest public evidence we found traced back to vendor-affiliated sourcing rather than an independent confirmation that the tool is in active clinical use, so it failed our independence check and sits as unconfirmed pending better evidence. It may well be real — we just won’t count what we can’t independently verify.
• Henry Ford and care.ai (not Abridge). Henry Ford Health’s virtual-nursing work runs on care.ai, a Stryker company, not Abridge. The two get conflated in some coverage because both are healthcare-AI vendors active in the same systems, but attributing Henry Ford’s deployment to Abridge would be wrong. We tie each deployment to the vendor the evidence actually supports.

The takeaway for nurses and leaders: when you see a headline that “System X deployed Vendor Y,” ask whether that’s an independent report or a vendor announcement. The gap between the two is where a lot of AI hype lives.

If you’re a nurse leader or informaticist with a seat at the vendor table, the landscape turns into a checklist of questions:

• Ask who actually verified the vendor’s accuracy claims, and on what patient population.
• Ask how the tool handles accents, complex cases, and the kind of documentation your unit really produces.
• Ask what happens to your data, who owns the model’s training inputs, and how errors get caught and corrected.

Then ask the governance questions. Who in your system signs off on this tool? Is a nurse in that room? How will the deployment be monitored after go-live, not just at the pilot? These are exactly the oversight gaps we dig into in our analysis of nursing’s AI governance gap, and they’re the questions a concentrated market makes easy to skip.

A short vendor list makes buying simpler. It does not make the diligence optional.

The companies behind nursing’s AI are few. Two vendors appear to supply most of the tools, most of it runs inside Epic, and a meaningful share of the “deployments” you’ll read about are vendor claims rather than confirmed use.

Knowing which vendors actually have deployed AI systems within clinical practice is the first step toward choosing AI on nurses’ terms instead of the vendors’.

Related Nursing AI Watch Analysis:

🤔 Which AI vendor’s tools are running on your unit, and did anyone ask the nurses before it arrived? Tell us about the rollout in the comments below.

About the data: Nurse.org’s Nursing AI Watch is built from a structured dataset of AI deployments across 106 large health systems. We count only what we can document from the public record — company announcements, peer-reviewed research, news coverage, union and regulatory filings, and official disclosures — and we favor sources independent of the vendor. That means our counts are conservative floors, not exhaustive totals, and figures like “95 of 106 systems run on Epic” describe the systems we track, not national market share. We update the dataset each reporting cycle and scope every claim to what the evidence supports.

Nurse.org Analysis