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AI for health services

Forty percent of your doctors' time never reaches the patient.

Physicians spend up to 40% of their working hours on administrative tasks. Inside the exam room, 37% of their time goes to EHR clicks instead of clinical conversation. AI reduces that operational drag, surfaces diagnostic patterns across complex patient histories, and handles visit logistics so clinicians focus on the medicine.

~15,800

physician hrs saved in year one

2–12

weeks to first value

40%

of physician time is admin, not care

The forces working against care teams right now

Clinical burnout, diagnostic complexity, and administrative overload are compounding, and the pressure only grows from here.

Documentation burden drives burnout

Charting follows clinicians home. After-hours "pajama time" is the leading contributor to physician exhaustion and the top reason cited for leaving practice.

Diagnostic complexity keeps growing

Medical knowledge now doubles every 73 days. Diagnostic errors affect roughly 1 in 5 patients, and premature closure is a factor in 47% of those errors. No single clinician can hold the full picture across every patient history, lab trend, and emerging guideline. AI can surface correlations and patterns across large datasets as a decision-support layer, but the clinical judgment stays with the physician.

Uneven gains across clinicians

Benefits vary by specialty and workflow. A large-scale study found modest and inconsistent per-clinician time savings even as aggregate hours and burnout metrics improved.

Administrative friction at the front door

Waiting-room intake, triage forms, and insurance verification still run on clipboards and manual entry, delaying the visit before it starts.

What we hear

AI scribes saved our group 15,000 hours and brought the human side of medicine back.

I finish my notes at home after the kids are in bed.

The waiting room fills up while we do paperwork.

Six ways to give clinicians their time back

Each targets a real drain on your care team, from front-desk intake to diagnostic support and post-visit documentation, plotted by the impact it creates against the effort to stand it up. Upper-left is the most return for the least lift.

Business impact
Quick winsDifferentiatorsNice to haveLater
1Medical triage in waiting room
2Patient diagnosis assistant
3Document generation
4Ambient AI scribe for clinical notes
5After-visit summary drafting
6Coding and claims support
Lower effortHigher effort
1Medical triage in waiting roomQuick win
2Patient diagnosis assistantDifferentiator
3Document generationQuick win
4Ambient AI scribe for clinical notesDifferentiator
5After-visit summary draftingNice to have
6Coding and claims supportLater
1
Quick win

Medical triage in waiting room

The work today

Patients wait while staff manually collect symptoms and history on paper forms.

How it works
1
Patient completes a guided intake on a tablet or phone
2
AI structures symptoms, flags urgency, and pre-populates the chart
3
Clinician walks in with context instead of starting from scratch
Expected impact
40%
less intake processing time
Time to first value
2–4 wks
from kickoff, on your existing stack

Where a person stays. Clinical staff review every triage flag before it influences care decisions.

Time-to-value estimates draw on published deployments and are indicative only. Every organization's data, systems, and starting point are different.

What would your care team do with documentation off their plate?

The largest reductions land on high-volume administrative tasks. Clinical judgment work stays with the clinician, and per-clinician documentation savings remain modest and variable.

25%less time

Clinical documentation

Visit notes and charting

20%less time

EHR time

Clicks, navigation, data entry

45%less time

After-visit summaries

Patient-facing recaps

40%less time

Intake paperwork

Forms, triage, pre-visit prep

Most practices channel reclaimed hours into patient face time and same-day appointments, the work that improves outcomes and retention.

What tends to move

~15,791

Physician hours saved in year one

Aggregate hours reclaimed across a large physician group deploying ambient AI scribes at scale.

source
Documented

Burnout reductions

Clinicians report lower documentation-related burnout after ambient scribe adoption.

source
Improved

Patient-physician interaction

Less screen time during visits leads to more eye contact and conversational engagement.

source
Variable

Note-level time savings

Per-clinician time savings vary by specialty and workflow. Aggregate gains compound, but individual results are inconsistent.

source

Ranges from published clinical studies. Individual time savings vary by clinician, specialty, and existing workflow.

The Permanente Medical Group

Deployed ambient AI scribes at scale with 2.5M+ uses in the first year, reclaiming roughly 15,791 physician hours and reducing documentation burden across the group.

~15,791 hrs

physician hours saved in the first year of deployment

2.5M+

ambient scribe uses in year one across the physician group

What would your clinicians do with their evenings back?

Tell us how your practice runs today and we'll map where AI actually fits, and where it honestly doesn't, for your setup.

Let's talk