A new gold rush is underway.

Nearly every health tech company now offers what it calls an “AI Copilot.”

From scribe apps that clean up your visit notes to full-stack EHRs promising real-time reasoning, everyone claims to be your digital sidekick. But most of what’s marketed as “AI-powered” today still amounts to automated clerical work.

It’s useful—but it’s not intelligence.

The real copilot stack is just starting to take shape.

A#1: The Scribe

More and more tools save time (though not necessarily judgment):

Some capture conversations, extract structured notes, and fill the chart. Others can create multiple documents from a single transcript, including SOAP notes, after-visit summaries, care coordination letters to the patient’s care team, medical leave of absence letters, referrals, and more. 

That’s a huge win for efficiency, but the insight layer is still lacking.

Use it for: Reclaiming 2–3 hours per day from documentation.

Don’t expect it to: Summarize trends or connect data across patients. These tools also won’t “hear” the clinical reasoning in your head. You still have to dictate what you want in the note. 

Platforms are bridging from clerical to cognitive in a few categories. 

Data dashboards:

Clinical decision support tools:

Non-clinical LLMs:

*Vibrant provides a combination of data dashboard functionality and clinical decision support. 

These synthesizers ingest notes, labs, and wearable data, then surface what matters: a rise in insulin resistance, a low ferritin trend, or early inflammation signals.

Think of this as your “pattern-recognition layer.”

It doesn’t make the call, but it does tell you where to look.

Use it for: Reducing cognitive load and prepping smarter before each visit.

Don’t expect it to: Make clinical decisions for you or replace root-cause reasoning.

This is where it gets interesting. Clinicians can watch as AI’s capabilities advance with platforms like:

The true copilots are starting to act: updating follow-ups, generating orders, triggering patient messages, and learning your preferences over time. They can query data, draft patient updates, and schedule follow-ups without leaving the chart.

They live inside your workflow, not beside it.

Use it for: Automating context-aware tasks that don’t need your brain but still need your oversight.

Don’t expect it to: Run the clinic on autopilot—yet.

With these three types of copilots in play, clinicians are seeing some major gains, particularly in efficiencies. These tools still can’t replace the medical practitioner’s expertise, though, as is evidenced by:

That doesn’t mean people in the medical field should wait for AI tools to be perfect. Instead, you can start to realize the benefits of these copilots by using them in proven areas. Deploying an AI scribe absolutely expands your cognitive bandwidth, for example. 

As you get more comfortable with AI tools, you can build your copilot stack. Two best practices here:

The sooner you start familiarizing yourself with copilot capabilities, the faster you’ll see where AI can go next.

You can test out a number of copilot tools before you leap into the full operator mode. First, you just need clarity on where AI adds leverage.

Try this simple audit:

Within weeks, you’ll have the early blueprint of your own AI-native clinical workflow—built not on hype, but on daily reality.

The Modern Clinician is written for functional, integrative, and longevity-focused physicians who want to scale their impact and deliver cutting-edge care.

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To learn more about the why behind this newsletter, start with our first post introducing The Modern Clinician.