Clinical AI Adoption

DAX or Abridge went live. Adoption stayed low. Physicians stopped using it within 90 days and nobody can explain exactly why. The tool gets blamed. The real problem is almost never the tool.

For health systems and medical groups where ambient AI is installed but not delivering

Overview

What this is

Most ambient AI rollouts fail not because the technology is wrong but because the implementation treats a clinical change management problem like an IT deployment. Clinicians get one hour of training. Workflow design is an afterthought. Nobody measures whether the tool is actually saving time. Trust breaks early and never recovers.

This is a fixed-scope discovery engagement. We go in, find exactly where the adoption is breaking, and give you a findings report and remediation roadmap specific enough to act on. First engagement is two to three weeks. No ongoing commitment until you have seen the findings and decided they are worth acting on.

Scope

What we do

Interview physicians across the adoption spectrum: heavy users, light users, people who stopped, people who never started
Review how the workflow was designed and where it conflicts with how clinicians actually work
Audit the Epic integration and SmartPhrase configuration for the specific failure points that kill adoption
Assess compliance exposure against current state AI disclosure and consent requirements
Build a measurement framework so you can track improvement after the engagement closes

Deliverables

What you get

Adoption diagnostic A clear picture of where adoption stands across physician cohorts, why the gaps exist, and which ones are recoverable.

Workflow and Epic integration review An honest assessment of how the ambient AI tool was configured and where the setup is working against the clinicians using it.

Clinician interview findings Direct quotes and failure patterns from across the adoption spectrum. Not a survey. Actual conversations.

Compliance gap assessment Where your current deployment is exposed under California AB 3030, state recording consent laws, and the growing body of AI disclosure requirements.

Prioritized remediation roadmap What to fix, in what order, with effort and impact ratings. Specific enough to hand to your clinical informatics team and act on without us in the room.

Measurement framework Baseline metrics and tracking structure so the next 90 days produce numbers, not anecdotes.

Right fit?

Good fit & not a fit

Good fit

You deployed DAX or Abridge in the last one to three years and adoption is lower than expected
Physicians completed training and then stopped using the tool
You have no clear picture of why adoption failed or where the workflow broke
You are facing compliance questions about patient consent, recording disclosure, or state AI requirements and have no governance framework in place
You need an outside perspective with no vendor relationship to protect

Not a fit

You have not yet deployed an ambient AI scribe and are still in evaluation
You need technical EHR implementation or Epic build work
You are looking for vendor-certified training rather than independent assessment

Representative engagement

What this looks like in practice

A regional health system deployed DAX Copilot across two primary care clinics eighteen months ago. Initial training was one hour per provider. Six months later, fewer than a third of physicians were using it regularly. The clinical informatics team assumed the tool was the problem and began evaluating alternatives.

We would go in before that decision is made. Talk to the physicians who stopped using it. Talk to the two or three who are still using it every day. Look at how the Epic SmartPhrase fields were configured and whether the note output actually maps to how those physicians document. Nine times out of ten the configuration is generic, the training never addressed how to speak naturally for ambient capture, and trust broke after one or two hallucinated physical exam findings that nobody had a protocol for handling.

The findings report names the specific breaks. The remediation roadmap tells the clinical informatics team exactly what to fix. In most cases the tool does not need to be replaced. The implementation needs to be rebuilt around how the clinicians actually work.

If your ambient AI investment isn't performing, we can tell you why.

Fixed-scope discovery audit. Two to three weeks. Clear deliverables.

Fixed scope · No surprise hours
Remote by default
Findings report before any remediation commitment

Email us about fit and timing