Your health system signs a contract for a new AI point solution. The business case is solid, and the pilot goes well. But eight months later, your core EHR vendor ships a native feature that does most of the same thing.
This isn't a story about a bad decision. It's happening across the industry right now, for a simple reason: EHR vendors are moving fast on native AI, and the capabilities that used to require a specialized point solution are increasingly becoming standard functionality. Health IT leaders aren't missing something obvious. They're making reasonable decisions in a market that's shifting faster than most procurement cycles can track.
Why This Keeps Happening
Inside Epic's own partner ecosystem, including at events like Open@Epic, this is one of the most common conversations happening right now. CIOs aren't asking which AI vendor to pick first. They're asking whether the feature they're evaluating externally is already on their core vendor's near-term roadmap.
That question is hard to answer well. Vendor roadmaps shift. Release timelines slip or accelerate. A capability that's 18 months out in one quarter's roadmap conversation can ship in the next release. Evaluating a point solution against a moving target is a difficult problem, not a due-diligence failure.
The Real Question Isn't What Your Vendor Will Ship
The more useful question isn't, "Will my EHR vendor build this AI feature?" It's, "Does our data infrastructure work no matter what they build next?"
That's what vendor-agnostic actually means in practice.
The Hart Platform connects to more than 150 EHRs through open standards, with no proprietary lock-in, which means that the data foundation underneath an AI initiative keeps working, whether the capability on top of it comes from the EHR vendor, a specialized point solution, or a model the health system builds internally. It also means the foundation works with whatever a health system already has in place, rather than requiring a rebuild to fit one vendor's ecosystem. The infrastructure question and the vendor-roadmap question become separate decisions instead of one bet riding on the other.
This is not a matter of evaluating more carefully before you sign. It's an architectural consideration: Build the data layer so it doesn't matter as much which vendor ships which feature when.
What a Connected Foundation Actually Changes
Inspira Health retired 30 years of legacy EHRs and transformed more than 70 million documents over an 8-year partnership with Hart. Vitruvian Health's Bradley Medical Center migrated 21 million records for 500,000 patients to Epic, on budget, in under 12 weeks.
Neither story is about picking the right point solution. Both are about a data foundation that remained usable and complete through a transition that, for many health systems, leaves records fragmented across both the old and new environments.
That consistency matters more as AI enters the picture. Normalized, validated data at the source is what makes any AI initiative, whether native or third-party, actually trustworthy. Across Hart's work with health systems, that validation runs to 99.7 percent data fidelity and 100 percent tier-1 QA accuracy, the kind of consistency that doesn't change based on which vendor's AI feature is reading the data.
A model trained on clean, connected, complete records produces something a clinician can actually act on. A model layered on top of fragments sounds confident even when it’s wrong.
A Simple Gut Check Before You Sign
None of this means slowing down on AI, or treating every single-purpose tool as a risk. It means running a quick check against four questions before signing the next contract:.
- Can your team already get to the data a new AI tool would need?
- Is the platform clean, connected, and structured well enough to trust?
- Would the model train on your own patient population, not someone else's?
- Could your EHR vendor already be building this same capability into next year's release?
None of those questions are really about the AI tool itself. They're about whether your data infrastructure holds up, regardless of what any one vendor does next. A point solution that clears all four criteria is a genuine addition to the stack. Technology that only makes sense if your EHR vendor never catches up is a bet, not a decision.
Where Hart Fits
The Hart Platform connects migration, archiving, integration, and analytics across more than 150 EHRs on open standards. With the infrastructure question already settled, a health system can then judge each AI tool on what it actually delivers.
If you want a clear-eyed look at where your organization's data infrastructure stands today, we offer a complimentary data assessment. No pitch, no slide deck, just a straightforward look at your data and where the gaps are. Reach out at hart.com/resources to get started.
