*This is the short version of a full article that’s published on our substack here.
Every write-up of the largest real-world study on AI scribes is telling the same underwhelming story: the technology barely moved the needle. I think that read is wrong — and the same data fueling the skepticism also explains why.
Across five academic health systems, 1,800 clinicians using ambient documentation saved about 16 minutes of charting and 13 minutes of total EHR time per day, compared to 6,770 peers who didn’t adopt the tool. Time outside work hours barely moved. If the promise you heard was “get your evenings back,” this study doesn’t deliver that on average.
But the same research group also found burnout falling sharply. At Mass General Brigham, the share of clinicians reporting burnout dropped from 52.6% to 30.7% in under three months. That’s a 22-point swing — not the kind of thing sixteen minutes a day explains.
So the “modest tool, modest results” take everyone’s settling on is measuring the wrong thing. Once you know where to look, the same data tells a very different story.
Two studies, one pattern
The time-savings numbers come from a new JAMA study — the largest and most rigorous of its kind, tracking 8,581 clinicians across five health systems using objective EHR audit-log data. The burnout numbers come from earlier, related research surveying more than 1,400 clinicians at Mass General Brigham and Emory Healthcare. Different instruments, same research lineage, and a consistent story: the value of an AI scribe doesn’t live primarily in the minutes it saves.
The number nobody led with
The 13-and-16-minute averages hide a massive split. Clinicians who ran the scribe on 50% or more of their visits saved two to three times the time of everyone else. Only about a third of adopters used it that heavily. Same software, wildly different outcomes — the gap is entirely explained by how the tool got used, not by the tool itself.
What burnout relief was actually measuring
If time savings scale with usage but burnout relief is dramatic regardless, burnout probably isn’t mainly about minutes. It’s about something closer to cognitive load — the toll of narrating a visit to a keyboard while trying to stay present with the patient in front of you. The minutes saved are a side effect. The relief from split attention is the real mechanism.
What the study doesn’t measure
A commentary published alongside the research made a sharp point: the field is good at measuring inputs — minutes, clicks, billing codes — and still limited at measuring what actually matters: patient experience, outcomes, equity of access. Worth remembering every time a “13 minutes saved” headline runs.
Here’s the part that should change how you think about rolling one of these tools into your own practice: buying the tool changes almost nothing on its own. The clinicians who benefited most weren’t using different software — they built a different habit. And that’s a solvable, specific, coachable problem, not a technology limitation.
Source: Rotenstein et al., JAMA (2026); You et al., JAMA Network Open (2025).
The Full Article Goes Further
Substack subscribers got the complete breakdown this past week — including the specific operating playbook I use to think about ambient AI rollouts: the usage threshold to set instead of a rollout date, why the “awkward middle” is the part that actually determines ROI, how to catch the silent group of clinicians who quietly never adopt it, and the actual pitch that gets someone through the hard first weeks.
If you’re a practice owner, clinic leader, or health tech operator making decisions about AI documentation tools this year, that playbook is the part worth having.
Read the full article here.
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