Occupation score change
IMPACT 20medical transcriptionist exposure increased 2.0 points
AI Exposure Score moved from a previous calculation to 54/100 under methodology v1.0. 1 evidence item(s) contributed.
54/100
increased by +2.0 vs last
Moderate exposure
3 Oct 2026
19 hours ago · sources: BLS OES (approx) · O*NET
1 sources
13 core tasks shown · 2 secondary hidden
Medical Transcriptionists High exposure: 8 of 13 core tasks show high task automation potential : exposure 54/100 (moderate exposure).
1 model with published evidence against this job. Strongest: Whisper large-v3 (92/100 capability).
Score breakdown
Why this score?
Every component is stored with the score row and can be recomputed from the evidence table.
AI Exposure (composite)54/100
Methodology 2026-09-a · score v1.0 · input hash 931632217ce03231
AI capability exposure79/100
Strength of current models on the capabilities this job's tasks require.
Task automation potential86/100
Task-level exposure, weighted by task importance. A component of the headline, not the headline itself.
Observed AI adoption0/100
Evidence that AI is actually being used for this work.
Labour-market signal0/100
Observed changes in postings, employment or earnings.
Evidence strength45/100
Quantity and source quality of the evidence behind the score.
1 evidence item(s) contribute. Calculated 19 hours ago. 3 Oct 2026 UTC.
Overview
Transcribe medical reports recorded by physicians and other healthcare practitioners using various electronic devices, covering office visits, emergency room visits, diagnostic imaging studies, operations, chart reviews, and final summaries. Transcribe dictated reports and translate abbreviations into fully understandable form. Edit as necessary and return reports in either printed or electronic form for review and signature, or correction.
Employment
≈30,000
approx. BLS OES
Median wage
≈$38,000
approx. BLS OES
Tasks tracked
15
linked to this occupation
Employment and wage values are approximate reference figures from the BLS Occupational Employment and Wage Statistics programme, stored with an approximation flag. Verify against the O*NET record and BLS before quoting them.
Tasks
Task-level automation exposure
Core tasks only. Exposure describes how much of the task output current AI can produce or substantially assist - not whether the task disappears. Secondary shared-baseline edges are hidden until per-occupation curation is complete.
core task · importance 4.9/5
core task · importance 4.8/5
core task · importance 4.8/5
core task · importance 4.7/5
core task · importance 4.7/5
core task · importance 4.6/5
core task · importance 4.6/5
core task · importance 4.6/5
core task · importance 4.5/5
core task · importance 4.5/5
core task · importance 4.3/5
core task · importance 4.3/5
core task · importance 4.2/5
Killers
Which models affect this job most
Ranked by strongest demonstrated capability. Task and evidence counts come from the attributed evidence trail below.
- 01Whisper large-v392/100
OpenAI · 1 evidence item
Evidence
Evidence trail
1 attributed item(s). Confidence reflects study design: randomised and production deployments score higher than platform observations, which score higher than projections.
- model releaseincreasesconfidence 94/100 · magnitude 886 Nov 2023
Whisper large-v3 provides open-weight multilingual speech recognition, allowing transcription to be run at scale for the cost of compute alone.
The clearest direct capability match in this index: manual transcription and captioning are technically substitutable today. Adoption is therefore the binding constraint, not capability.
Source: OpenAI via Hugging Face Hub · Updated 6 Nov 2023
Historical trend
Exposure over time
Backcast series: recomputed at quarterly checkpoints using only the models and evidence published by each date.
Reconstruction, not measurement. 5 observed daily snapshot(s) exist for this occupation; the earlier part of the curve is derived by applying the current methodology to the model releases and published evidence available at each past date.
Recent events
Signals affecting this occupation
- Research publishedIMPACT 40
Improving OCR Faithfulness via Gated and Attenuated On-Policy Distillation
arXiv:2609.38282v1 Announce Type: new Abstract: Vision-language models may rewrite anomalous text in images into linguistically plausible expressions, compromising OCR transcription faithfulness. Sequence-level task rewards and local teacher guidance are complementary, but guidance from the same teacher may not remain equally effective as the student improves. Offline analysis shows that supervision from a fixed teacher becomes progressively less favorable as the student improves, both across training checkpoints and across response groups with different task rewards. Motivated by this observa
- New modelIMPACT 88
Whisper large-v3 made accurate transcription freely self-hostable
Whisper large-v3 provides open-weight multilingual speech recognition, allowing transcription to be run at scale for the cost of compute alone.
Related
Related Occupations
Occupations sharing major SOC group (31) with Medical Transcriptionists.
faq
Frequently Asked Questions
Common questions regarding Medical Transcriptionists and AI exposure.
Will AI replace Medical Transcriptionists?
Current AI models show an exposure score of 54/100 for Medical Transcriptionists. This measures technical capability to assist or automate specific tasks rather than predicted immediate job loss. Moderate exposure reflects assistance in routine information-handling while core responsibilities require human judgment.
Which tasks in Medical Transcriptionists have the highest AI exposure?
The most exposed tasks for Medical Transcriptionists include "Transcribe dictation for a variety of medical reports, such as patient histories, physical examinations, emergency room…" (95% exposure) and "Translate medical jargon and abbreviations into their expanded forms to ensure the accuracy of patient and health care…" (85% exposure).
What aspects of Medical Transcriptionists can AI not do yet?
Tasks with the lowest AI exposure for Medical Transcriptionists include "Receive and screen telephone calls and visitors." (10% exposure) and "Decide which information should be included or excluded in reports." (25% exposure). These responsibilities typically require physical dexterity, licensed human accountability, or complex interpersonal navigation.
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Notice: All ratings shown are AI-estimated technical exposure scores measuring technical capabilities across O*NET task statements, not predicted job loss. Contains information from O*NET 31.0 by the U.S. Department of Labor, ETA, used under CC BY 4.0.