What is an AI-native EHR?
There is no standard, certification or regulatory definition of "AI-native EHR". The term is young, and it is used in marketing for very different products. So this page does what a buyer needs: it states a working definition and the criteria behind it, so you can test any product against them, including ours.
Working definition: an AI-native EHR (electronic health record, also called an EMR) is a system of record designed around AI from the start. The AI reads the structured chart, can prepare work on the record and not only answer questions, shows the chart source for what it says, takes instructions in plain language, and defers to the clinician before anything leaves the practice.
The common alternative is a legacy EHR whose vendor added AI later, usually as a scribe button, a summary panel or a separate module. Those features can be useful. They are a different design, and the criteria below are how you tell which one you are looking at.
A quick test: take the AI away and see what is left. In a legacy EHR with AI add-ons, you still have the EHR, minus some conveniences. In an AI-native EHR, much of the day-to-day workflow (asking the chart, drafting notes, preparing appeals) stops, because the AI is part of how the product works rather than an accessory.
A disclosure: these are the criteria Serelora uses, and Serelora sells software built to meet them. Weigh our framing accordingly and use the demo tests to check every claim.
What makes an AI-native EHR? Eight criteria you can test
Each criterion says what it means and how to test it in a demo. A product need not meet all eight to be useful, but the more it meets, the more it behaves like an AI-native EHR and the less like AI bolted onto a legacy one.
The AI works from the structured chart, not only a transcript
What it means: the AI reads problems, medications, labs, vitals and prior notes as structured data, not just the words said in the visit. How to test it: open a patient with a long history and ask something only the chart can answer, such as how a lab value has trended over a year. A tool that sees only a transcript cannot.
It can act on the record, not only answer
What it means: it prepares work, such as a draft note, a letter, a prior authorization or a scheduling change, instead of only giving advice. How to test it: ask the demo to draft an appeal from the chart, and see whether you get a finished draft inside the system or text you must retype somewhere else.
Every output traces to a chart source
What it means: each statement links back to the record it came from, so a clinician can verify it in one click. How to test it: ask for a summary, then click through every line. Anything you cannot trace is something you must re-check by hand, which is the cost AI medical charting is meant to remove.
You interact by asking or telling it
What it means: the main way to work is plain language, typed or spoken, rather than hunting through menus. Forms still exist where they help. How to test it: give one multi-step instruction (find the patient, pull the last labs, draft the follow-up letter) and count the clicks it takes.
One system instead of stitched add-ons
What it means: intake, charting, scheduling and billing share one record and one AI, rather than separate products linked by exports and re-entry. How to test it: follow one patient from the intake link to the bill, and note every place you re-enter data or switch tools.
The clinician approves before anything goes out
What it means: letters, appeals, prior authorizations and note edits wait for a person to approve them, and the AI never sends on its own. How to test it: ask the vendor to show the approval step, and ask what the AI is allowed to do without one. "Nothing leaves without approval" is the answer you want.
A tamper-evident audit trail
What it means: every access to a record and every action, human or AI, is logged so the log cannot be changed silently. HIPAA's Security Rule already requires audit controls that record and examine activity in systems holding electronic protected health information (45 CFR 164.312(b)); tamper-evident goes further by making changes to the log itself detectable. How to test it: ask to see one patient's audit log, whether AI actions appear in it, and how the vendor shows it has not been altered.
It fits a practice with no IT department
What it means: a small practice can try it, bring in its patient list and start charting without hiring IT help or sitting through a long sales process. How to test it: ask what going live with your own patient list takes, who does that work, and what you can try before you commit.
AI-native EHR vs legacy EHR with AI add-ons vs AI scribe
Three approaches all get called an "AI EHR". The table shows what each typically offers on the eight criteria. These are patterns, not verdicts on any one product: individual products vary, and many legacy EHRs are adding AI quickly. Check each product with the demo tests above.
| Criterion | Legacy EHR with AI add-ons | Standalone AI scribe | AI-native EHR |
|---|---|---|---|
| Works from the structured chart | Legacy EHR with AI add-ons: Varies; often one note or screen | Standalone AI scribe: Starts from the visit conversation | AI-native EHR: The whole chart is the context |
| Acts on the record | Legacy EHR with AI add-ons: Often suggests; staff still do the work | Standalone AI scribe: Drafts the note only | AI-native EHR: Prepares notes, letters and billing work for approval |
| Every output traces to a source | Legacy EHR with AI add-ons: Varies by feature | Standalone AI scribe: Note to transcript, at best | AI-native EHR: Each answer links to its chart record |
| You ask or tell it | Legacy EHR with AI add-ons: Menus and forms; AI in side panels | Standalone AI scribe: Record, then review | AI-native EHR: Chat is the main way to work |
| One system, not add-ons | Legacy EHR with AI add-ons: Core EHR plus add-ons, often from partners | Standalone AI scribe: No: sits beside an EHR | AI-native EHR: Intake, charting, scheduling and billing together |
| Clinician approves before anything goes out | Legacy EHR with AI add-ons: Varies by feature | Standalone AI scribe: You review and sign the note | AI-native EHR: Required for anything that leaves the practice |
| Tamper-evident audit trail | Legacy EHR with AI add-ons: Standard audit logs; ask about tamper evidence | Standalone AI scribe: Varies; ask | AI-native EHR: Includes AI actions; ask to see it |
| Fits a practice with no IT department | Legacy EHR with AI add-ons: Varies; ask what setup involves | Standalone AI scribe: Usually quick to start | AI-native EHR: A self-serve start is the sign to look for |
A standalone AI scribe is not a lesser product. It does one job, turning a visit into a note, and can be the right choice for a practice that is happy with its EHR (see AI scribes for independent practices). It is not an EHR, so it cannot meet criteria that depend on owning the record, such as acting on it or running intake through billing in one system.
How to evaluate the best AI-native EHR for your practice
The best AI-native EHR for your practice is the one that meets your must-have criteria in your own workflow. Evaluate with your patients and your paperwork, not a scripted demo. Work through this checklist.
- Run the eight demo tests above on a chart with a long history, not a clean sample patient.
- Ask the vendor to do one real task end to end: an intake link, a visit note, a charge, and an appeal or prior authorization draft.
- Check that anything leaving the practice (letters, appeals, prior authorizations) waits for a clinician's approval.
- Click through the citations. If a line does not link to a source, treat it as unverified.
- Ask to see the audit log, including the AI's actions.
- Confirm how your patient list gets in, and who does that work.
- Confirm a business associate agreement is signed before any patient record is read.
Then put these questions to every vendor and compare the answers in writing:
- What does your AI read: the structured chart, a transcript, or both?
- Which actions can the AI take on the record, and which wait for a clinician's approval?
- How is every AI output traced to its source?
- What does your audit trail record, and can it be altered without detection?
- What is your security and compliance status today? Ask for the exact wording: a SOC 2 Type II audit in progress is different from a completed report.
- What are your models and code sets, and how is the AI evaluated for clinical accuracy?
- How long does a practice our size take to go live, and what can we try first?
For the wider choice of EHR, see the best EHR for independent practices.
AI-native vs AI-powered vs AI-enabled: what the terms mean
No body defines these words, so vendors use them loosely. Here is how this page uses them. Read any vendor's claim with these definitions in mind.
- AI-enabled means the product includes at least one AI feature. It is the weakest claim: a single summary button qualifies.
- AI-powered means AI does a meaningful share of the work in one or more workflows, such as drafting notes. The EHR underneath may be unchanged. An AI-powered EHR or AI powered EMR is common today.
- AI-native means the product was designed around AI, so the AI works from the structured chart, acts on the record and sits in the core workflow. It is the strongest claim, which is why it needs the criteria above.
None of these is better by itself: a well-built AI-powered feature can beat a poorly built AI-native product. The words describe design, not quality, which is why this page gives tests instead of labels.
Regulation does not settle it either. The ONC HTI-1 final rule sets transparency requirements for AI and other predictive algorithms in certified health IT, but it addresses how algorithms are disclosed, not what a vendor may call its product. We know of no standard or certification that defines "AI-native EHR" as of October 2026.
"Agentic" is a neighboring term. It describes what the AI can do (carry out multi-step tasks), while "AI-native" describes how the product is built. The two ideas overlap; see what an agentic EHR is.
Why "AI EHR" and "EHR with AI" searches mean different things
People who search "AI EHR", "AI-powered EHR", "EHR with AI" or "AI EMR" usually want one of four different things. Decide which you need before you compare products.
- An AI scribe for the EHR you already use. Often searched as "EHR with AI scribe".
- A new EHR with AI built in. For a practice that is switching, or a physician opening one. This is where an AI-native EHR competes.
- AI features inside your current EHR. Ask what the AI can read and do, using the criteria above.
- AI for one job, such as prior authorization, billing or charting.
If you are opening a practice, an AI-native EHR avoids buying an EHR, a scribe and billing tools separately. See setting up a new practice.
Where Serelora fits
- Structured chart: Serelora reads the chart before the visit. You can ask the whole chart anything, and lab and vital trends are charted on request.
- Acts on the record: it handles billing and administrative work such as charges, appeals, prior authorizations and scheduling from the conversation, and drafts denial appeals and prior authorizations from the chart that supports them.
- Traceable: every answer links to the record it came from. The AI scribe drafts the visit note from the conversation with every line traced to it.
- Ask or tell: you tell it what you need.
- One system: intake, charting, scheduling and billing in one system, with AI handling the paperwork.
- Clinician approval: nothing goes out on its own. Letters, appeals and note edits wait for the clinician's approval, and the clinician reviews and signs the scribe's note.
- Audit trail and trust: Serelora is HIPAA-compliant, with a tamper-evident audit trail. A business associate agreement is signed online at signup, before any patient record is read. A SOC 2 Type II audit is in progress.
- No IT department needed: start free with a 7-day trial and no sales call. A practice can import its patient list from Office Ally itself, and payer connections are set up as the practice needs them. See the Serelora platform.
Is an AI-native EHR right for your practice?
An AI-native EHR pays off most where the paperwork is heavy and the team is small: an independent practice, or a physician opening one, with no IT department and no one whose job is to chase prior authorizations.
It is a weaker fit when:
- You are happy with your current EHR and only want faster notes. A standalone AI scribe, or the AI your EHR already includes, is the lighter step. A practice can also keep the scribe it already uses with Serelora.
- You need a connection to a specific named system. Ask each vendor for its exact integration list and do not assume.
- You are a large health system with enterprise requirements. That is a different buying process from the independent-practice one this page is written for.
- You expect the AI to make decisions. In an AI-native EHR as defined here, the AI prepares and the clinician decides.
This page is about software and practice operations. It is not medical advice.
Frequently asked questions
- What is an AI-native EHR?
- An AI-native EHR is an electronic health record (also called an EMR) designed around AI from the start rather than extended with AI later. The AI works from the structured chart, can prepare work on the record, links every output to its source, takes plain-language instructions and waits for clinician approval. The term has no formal standard, so this is a working definition.
- What is the difference between an AI-native EHR and an AI-powered EHR?
- AI-powered means AI does real work in some workflows, but the EHR underneath may be unchanged. AI-native means the product was designed around AI, so the AI reads the structured chart, acts on the record and sits in the core workflow. The words describe design, not quality, so test any product against the criteria instead of trusting the label.
- Is there an official definition or certification for AI-native EHR?
- Not that we know of as of October 2026. ONC's HTI-1 rule sets transparency requirements for AI and predictive algorithms in certified health IT, but it addresses disclosure, not what a vendor may call its product. Treat "AI-native" as marketing language until you have tested it, and use the criteria on this page as a checklist.
- How is an AI-native EHR different from an AI scribe?
- An AI scribe turns a visit into a draft note and sits beside your EHR. An AI-native EHR is the system of record itself, so the AI also reads the chart, answers questions with sources, and prepares billing and administrative work for approval. A scribe is a good fit if you are happy with your EHR and want faster notes.
- What is the best AI-native EHR for a small practice?
- It depends on your workflow, so there is no single best AI native EHR software for everyone. Run the eight demo tests on a chart with a long history, check what the AI can do without approval, and ask what going live takes without an IT team. Serelora is built for independent practices; compare it with any other vendor on these criteria.
- Can I get an EHR with AI without switching EHRs?
- Often yes. Many EHRs add AI features, and a standalone AI scribe can sit beside the EHR you have. Ask what the AI can read and do, whether outputs link to chart sources, and whether anything is sent without approval. If the answers fall short, an AI-native EHR is the switch to consider, especially when opening or restructuring a practice.
- Is Serelora an AI-native EHR?
- By the eight criteria on this page, Serelora is built to be one: it is all-in-one AI practice software and an EHR for independent practices, built around a chat, with answers linked to the chart and nothing sent without clinician approval. You can start free with a 7-day trial and no sales call to test each criterion yourself.
