Top 50 AI Scribes: The Brutal Truth [Part 3 of 4]

I ask the actual users—clinicians—why they hate or love AI scribes.

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All right, Part 3. We’re almost there. 😉

Part 3 is all about real users sharing their experiences about AI scribes. Straightforward. No bullshit.

To reiterate, I never summarize AI scribe press releases or VC presentations with cherry-picked stories of their "portfolio companies." Never ever would I do that. If you want that marketing bullshit, please unsubscribe right now and go read popular media or pay $3,000 to hear a V-necked VC on a big conference stage, patting themselves on the back about their so-called "successes.”

I steer clear of biased stuff. I go straight to the source—the product itself and, most importantly, its users. Simple as that.

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Here's what I’ve covered in the first two parts of this 4-part series, and what I’m about to discuss here in Part 3:

• In Part 1 two weeks ago, I explored the broader AI scribe landscape, analyzed adoption rates, and investigated why some clinicians enthusiastically embrace AI scribes while others remain deeply skeptical.

• In Part 2 last week, I unpacked the fiery discussion from the recent Digital Health Inside Out episode titled “Why the Hell Do We Need 126 Medical AI Scribes?” featuring Brendan Keeler, Alex Lebrun, Bobby Guelich, my co-host Alex Koshykov, and yours truly. Notably, Brendan Keeler and I engaged in a vigorous yet respectful debate regarding the commoditization of AI scribes and the role—good, bad, and ugly—of venture capital.

• In this Part 3, I go directly to the source—clinician-users—to figure out critical questions head-on. Do AI scribes genuinely represent innovations in value-based care, or are they just Revenue Cycle Management (RCM) tools disguised as clinical support? Additionally, I assess their real-world integration success within EHR systems and scrutinize claims of saving clinicians time and money.

• In the upcoming Part 4, I’ll finally look at the data, presenting a head-to-head comparison of the 50 most popular AI scribe tools. This evaluation is strictly from a user’s practical standpoint—no marketing bullshit allowed. Specifically, I compare:

  • Pricing

  • Note Accuracy & Quality

  • Editing Burden (time and effort required for revisions)

  • Integration & Workflow (ease of practical use within EHR systems)

  • Specialty Fit & User Trust

Here’s TL;DR:

1. Foundational LLMs Already Solve Transcription—So Do We Really Need 126+ AI Scribes?

2. Your iPhone Makes a Terrible Doctor: When Will AI Scribe Hardware Finally Catch Up?

3. Ambient AI Scribes: The Great Workflow Lie

4. Physicians’ Wish List: Make AI Scribes Invisible, Not Intrusive

5. “Pop-up Fatigue": I get 50 useless pop ups per day… WTF!?!

6. When Will AI Scribes Start Interviewing Patients Without Doctors?

7. When Will Your AI Scribe Finally Move Out of Your Basement and Start Acting Like a Real Doctor?

8. AI Scribes: Value-Based Care (VBC) vs. Fee-for-Service (FFS)

9. AI Scribes: Clinical Saviors or Revenue Cycle Machines? Just Ask Suki.

10. AI Scribes’ Impact on Population Health and Precision Medicine

11. All AI Scribes Will Die—Unless They Become Copilots. WTF?

12. AI Scribes: Commoditization or Consolidation—or Just Plain Extinction?

13. Brutally Honest Clinician Feedback on AI Scribes