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AI Automation Index
Will AI Replace Medical Records Specialists?
Task-level automation exposure for Medical Records Specialists: 16 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
60%
weighted task index
16 of 16 tasks scored
Median Salary
$51,140 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
High
194,720 people hold this job — size, not growth
Projected 2025–35
+7.8%
employment change
14,000 openings a year · BLS line item
Pay by state
BLS OEWS publishes 53 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$27,990 – $72,040
Highest medians
District of Columbia $72,040
Rhode Island $63,960
Hawaii $63,180
Washington $62,270
California $61,810
Lowest medians
Puerto Rico $27,990
Guam $38,470
Mississippi $41,500
Arkansas $41,740
Alabama $43,810
State figures come from the 29-2072 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.
What the score is made of
Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.
Automation potential 60%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 9%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 9%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 56%
Share in documenting, recording, and administrative activities.
Rewritten by O*NET 0%
Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.
Consequence of error 2/100
Low
O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.
Constituent Task Mix
16 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.
High exposure (≥ 60% of the task is automatable) 73%
12 tasks
Medium exposure (≥ 35%) 19%
3 tasks
Low exposure (below 35%) 9%
1 tasks
How would you survive?
Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.
Simulate Upskilling →Constituent Tasks
#22886 · Core · 8% automatable
Protect the security of medical records to ensure that confidentiality is maintained.
situated mobility — Physical security presence in world
Maintain security.
#22890 · Core · 45% automatable
Review records for completeness, accuracy, and compliance with regulations.
visual inspection — AI reviews records; human observes facility activities
Monitor medical facility activities to ensure adherence to standards or regulations.
#22891 · Core · 65% automatable
Scan patients' health records into electronic formats.
text generation — Healthcare forms processed digitally; human verifies edge cases
Process healthcare paperwork. Perform clerical work in medical settings.
#22887 · Core · 60% automatable
Release information to persons or agencies according to regulations.
text generation — Clerical medical paperwork aided; compliance review human
Perform clerical work in medical settings.
#22880 · Core · 80% automatable
Enter data, such as demographic characteristics, history and extent of disease, diagnostic procedures, or treatment into computer.
data analysis — Patient data entry largely automatable with review
Enter patient or treatment data into computers.
#22882 · Core · 72% automatable
Maintain or operate a variety of health record indexes or storage and retrieval systems to collect, classify, store, or analyze information.
data analysis — Facility records need human verification and compliance
Maintain medical facility records.
#22885 · Core · 70% automatable
Process patient admission or discharge documents.
text generation — Healthcare forms processed digitally; human verifies edge cases
Process healthcare paperwork.
#22889 · Core · 60% automatable
Retrieve patient medical records for physicians, technicians, or other medical personnel.
text generation — Clerical medical paperwork aided; compliance review human
Perform clerical work in medical settings.
#22888 · Supplemental · 55% automatable
Resolve or clarify codes or diagnoses with conflicting, missing, or unclear information by consulting with doctors or others or by participating in the coding team's regular meetings.
interpersonal — Cross-staff problem resolution involves politics and trust
Communicate with management or other staff to resolve problems.
#22878 · Supplemental · 62% automatable
Compile and maintain patients' medical records to document condition and treatment and to provide data for research or cost control and care improvement efforts.
interpersonal — Patient history requires live elicitation and judgment
Record patient medical histories.
#22881 · Supplemental · 55% automatable
Identify, compile, abstract, and code patient data, using standard classification systems.
data analysis — Coding data automatable with human review
Collect medical information from patients, family members, or other medical professionals. Code data or other information.
#22877 · Supplemental · 82% automatable
Assign the patient to diagnosis-related groups (DRGs), using appropriate computer software.
text generation — Standard classification systems applied to text records
Classify materials according to standard systems.
#22884 · Supplemental · 69% automatable
Process and prepare business or government forms.
text generation — Healthcare forms processed digitally; human verifies edge cases
Prepare official health documents or records. Process healthcare paperwork.
#22879 · Supplemental · 75% automatable
Consult classification manuals to locate information about disease processes.
information retrieval — AI summarizes medical updates; human retains judgment
Maintain medical or professional knowledge.
#22893 · Supplemental · 60% automatable
Transcribe medical reports.
text generation — Clerical medical paperwork aided; compliance review human
Perform clerical work in medical settings.
#22892 · Supplemental · 71% automatable
Schedule medical appointments for patients.
decision support — Calendar scheduling automatable; exceptions need human judgment
Schedule appointments. Schedule patient procedures or appointments.
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How this was scored
- 1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
- 2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
- 3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
- 4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.
Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.
Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast
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