AI in EHR

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AI Dictation and Ambient Scribes in Healthcare — How AI is Transforming Clinical Documentation

Clinical documentation is the silent burden of modern medicine. Physicians spend 44% of their clinical time on documentation and only 24% on direct patient interaction. An athenahealth survey found that 57% of providers cite excessive EHR documentation as the primary driver of clinician burnout. Doctors take notes home, miss family time, and lose the joy of practising medicine — all because of paperwork.

AI-powered dictation and ambient scribes are changing this. They listen to the doctor-patient conversation, understand the clinical context, and generate structured notes automatically. No typing. No clicking through templates. Just medicine.

How Ambient AI Scribes Work

The technology follows a simple but powerful workflow:

  1. Listening — The AI passively captures the natural conversation between clinician and patient during the encounter
  2. Transcribing — Speech recognition converts audio into text, handling medical terminology, abbreviations, acronyms, and dialect variations
  3. Structuring — Natural Language Processing (NLP) organises the transcript into structured clinical notes (SOAP, H&P, progress notes)
  4. Coding — Some platforms auto-suggest ICD-10, CPT, E/M, and HCC codes based on the encounter
  5. Reviewing — The clinician reviews, edits if needed, and signs off. The note flows into the EHR

The key difference from traditional dictation: ambient scribes don’t require the doctor to dictate anything. They work silently in the background, capturing the real conversation — not a rehearsed monologue.

The Impact on Healthcare

The numbers are compelling:

Metric Impact
Documentation time saved Up to 90 minutes per day per physician
Time saved per encounter 15 minutes on average
Burnout reduction 27% reduction reported (Nabla)
Patient throughput 1.5x more monthly appointments per clinician
Patient interaction quality 81% improvement in clinician-patient engagement
Market growth Medical scribe industry projected to reach $33.7 billion by 2028

For context, Robin Healthcare surveyed 300 orthopaedic physicians and found:

  • 80% say note-taking interferes with patient interaction
  • 90% want reduced documentation time
  • 71% view medical coding as disruptive to practice quality
  • 73% take work home to finish notes

Leading AI Scribe Platforms

Microsoft Dragon Copilot (formerly Nuance DAX)

The most established player. Originally Dragon Medical One — the gold standard in medical speech recognition — Microsoft acquired Nuance and evolved the product into Dragon Copilot, combining:

  • Advanced speech recognition for documentation workflows
  • Ambient clinical intelligence that captures encounters passively
  • Deep EHR integration (Epic, Cerner, and others)
  • PowerMic Mobile for smartphone-based dictation

Dragon was the pioneer. Every other ambient scribe is essentially trying to be a better, cheaper Dragon.

Nabla

A standout platform with impressive scale and outcomes:

  • 85,000 active clinicians across 150 health organisations
  • 20 million patient encounters processed annually
  • 55% of users save at least 1 hour of documentation time daily
  • Supports 50 medical specialties and multiple languages
  • Live transcript capability during consultations
  • Custom instructions and dot phrases
  • Integrates with Epic, athenahealth, Oracle Health, NextGen, Greenway Health
  • HIPAA, GDPR, SOC 2 Type 2, and ISO 27001 certified
  • No audio stored by default — user data not used for model training

Nabla is particularly strong in paediatrics — Children’s Hospital Los Angeles reported improved patient-family experience.

Augmedix

One of the earliest players, founded in 2013 as the first to deliver ambient medical documentation:

  • Generated over 10 million notes across healthcare organisations
  • Offers a range from self-service to full-service (AI only to AI human review)
  • Custom solutions for emergency medicine and oncology
  • Handles complex workflows and noisy environments
  • Integrates with Epic, athenahealth, Oracle Cerner, Meditech, eClinicalWorks, NextGen
  • HITRUST certified, HIPAA compliant
  • Clinicians report life-changing impact: “I’m taking lunch breaks for the first time in years”

DeepScribe

Positions itself as an “ambient OS” for healthcare with a comprehensive approach:

  • AI Pre-charting — prepares visits with contextual patient info before appointments
  • AI Scribe — documents natural conversations using ambient capture
  • AI Coding — automates specialty-specific coding (E/M, HCC, ICD-10)
  • Customisation Studio — learns each provider’s style and workflows
  • DeepScribe Assist — real-time clinical insights during encounters
  • Captures 3.1 million cancer care visits annually
  • 80% clinician adoption rate
  • KLAS Spotlight Report score: 98.8 out of 100
  • Partnerships with Stanford Health Care, Texas Medical Center, Hartford HealthCare
  • EHR setup in under 24 hours

Tali.ai

A voice-enabled virtual assistant with a practical approach:

  • Compatible with all web-based EHR systems
  • Uses NLP and machine learning for accurate speech detection
  • Automated SOAP note generation
  • Understands various dialects and medical terminology
  • Non-intrusive integration — works within existing workflows
  • HIPAA and PHIPA compliant
  • Up to 3x faster than manual documentation

S10.ai

Markets itself as the “best ambient AI medical scribe for any EHR” — a lightweight, EHR-agnostic solution focused on simplicity and broad compatibility.

Robin Healthcare

Specialises in orthopaedics with notable results:

  • Processed over 1 million orthopaedic visits
  • Activated by voice command: “Hey, Robin”
  • Claims up to 90 minutes saved daily per physician
  • Founded in 2017, Berkeley-based

Amazon Comprehend Medical

Not a scribe per se, but a foundational NLP service from AWS that:

  • Extracts medical information from unstructured text
  • Identifies conditions, medications, dosages, procedures
  • Powers custom clinical documentation workflows
  • Used as a building block by other scribe platforms

eClinicalWorks

An affordable EHR with built-in AI scribe capabilities:

  • Adopted by Open Door Family Medical Center in New York during COVID when in-person scribes weren’t possible
  • Valued for cost-effectiveness and scalability
  • Integrated directly into their EHR platform

AI Scribes vs Human Scribes

Factor Human Scribe AI Scribe
Cost Salary, benefits, training, turnover Subscription fee
Availability Limited hours, staffing issues 24/7, every encounter
Consistency Variable, depends on individual Consistent, improves over time
Scalability Hard to scale Instant scaling
Accuracy Human errors, fatigue Algorithmic — no fatigue
Privacy Human sees everything Configurable, no audio stored
Setup Weeks of training Minutes to hours
Turnover High (often medical students) None

Human scribes still have an edge in complex, ambiguous clinical situations and in specialties where non-verbal cues matter. But for the vast majority of documentation, AI scribes are faster, cheaper, and more consistent.

What This Means for EHR Development

If you’re building an EHR, ambient AI documentation isn’t optional — it’s expected. Key considerations:

  1. API-first integration — Your EHR needs open APIs that ambient scribe platforms can plug into
  2. FHIR compatibility — Structured notes should map to FHIR resources (Encounter, Condition, Observation)
  3. Template flexibility — Support custom note templates that AI can populate
  4. Audio pipeline — Consider building native audio capture and transcription
  5. Coding automation — Integrate ICD-10, CPT, and SNOMED suggestion engines
  6. Review workflow — Build a sign-off workflow where clinicians can review and approve AI-generated notes
  7. Privacy by design — No audio storage by default, HIPAA/GDPR compliance baked in

The future EHR doesn’t have a text editor as its primary interface. It has a microphone.

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References

  1. EMR Finder. (2023). ‘AI Scribe Technology for EHR Documentation’. EMR Finder Blog. Available at: https://emrfinder.com/blog/ai-scribe-technology-for-ehr-documentation/ (Accessed: 22 April 2026).

  2. RYortho. (2022). ‘The Race to Apply AI to EHR and Medical Note-Taking’. RYortho. Available at: https://ryortho.com/2022/05/the-race-to-apply-ai-to-ehr-and-medical-note-taking/ (Accessed: 22 April 2026).

  3. Microsoft Corporation. (2025). ‘Dragon Copilot — AI-Powered Clinical Documentation’. Microsoft Health Solutions. Available at: https://www.microsoft.com/health-solutions (Accessed: 22 April 2026).

  4. Nabla. (2025). ‘Nabla — Ambient AI Assistant for Clinicians’. Nabla. Available at: https://www.nabla.com (Accessed: 22 April 2026).

  5. Augmedix. (2025). ‘Augmedix — Ambient AI Medical Documentation’. Augmedix. Available at: https://www.augmedix.com (Accessed: 22 April 2026).

  6. DeepScribe. (2025). ‘DeepScribe — The Ambient OS for Healthcare’. DeepScribe. Available at: https://www.deepscribe.ai (Accessed: 22 April 2026).

  7. S10.ai. (2025). ‘S10.ai — Ambient AI Medical Scribe for Any EHR’. S10.ai. Available at: https://s10.ai (Accessed: 22 April 2026).

  8. Tali AI. (2023). ‘Why Choose an AI-Assisted Medical Scribe Over a Human Scribe’. Tali AI Resources. Available at: https://tali.ai/resources/why-choose-an-ai-assisted-medical-scribe-over-a-human-scribe (Accessed: 22 April 2026).

  9. Amazon Web Services. (2025). ‘Amazon Comprehend Medical — Natural Language Processing for Healthcare’. AWS. Available at: https://aws.amazon.com/comprehend/medical/ (Accessed: 22 April 2026).

  10. athenahealth. (2022). ‘Physician Sentiment Survey: EHR Documentation and Clinician Burnout’. athenahealth Research. Cited in: EMR Finder (2023).

  11. Robin Healthcare. (2022). ‘Physician Survey: 300 Orthopaedic Physicians on Documentation Burden’. Robin Healthcare. Cited in: RYortho (2022).

  12. KLAS Research. (2024). ‘Ambient AI Scribe Spotlight Report — DeepScribe’. KLAS Research. Cited in: DeepScribe (2025).

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