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AI Automation Index
Will AI Replace Health Information Technologists and Medical Registrars?
Task-level automation exposure for Health Information Technologists and Medical Registrars: 16 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
58%
weighted task index
16 of 16 tasks scored
Median Salary
$68,020 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
Medium
38,100 people hold this job — size, not growth
Projected 2025–35
+15.9%
employment change
3,000 openings a year · BLS line item
Pay by state
BLS OEWS publishes 51 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$27,040 – $93,300
Highest medians
Arkansas $93,300
Minnesota $90,760
California $90,750
Wisconsin $89,260
Wyoming $88,560
Lowest medians
Puerto Rico $27,040
New Mexico $42,000
South Carolina $44,530
Oklahoma $45,210
Indiana $46,470
State figures come from the 29-9021 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 58%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 6%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 31%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 31%
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.
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) 56%
9 tasks
Medium exposure (≥ 35%) 25%
4 tasks
Low exposure (below 35%) 19%
3 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
#22894 · Core · 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.
#22895 · Core · 68% automatable
Compile medical care and census data for statistical reports on diseases treated, surgery performed, or use of hospital beds.
data analysis — Coding data automatable with human review
Gather medical information from patient histories. Code data or other information.
#22896 · Core · 75% automatable
Design databases to support healthcare applications, ensuring security, performance and reliability.
text generation — Database creation largely automatable; human reviews
Create databases to store electronic data.
#22897 · Core · 75% automatable
Develop in-service educational materials.
text generation — Draft healthcare training; clinician reviews accuracy
Prepare healthcare training materials.
#22898 · Core · 66% automatable
Evaluate and recommend upgrades or improvements to existing computerized healthcare systems.
data analysis — AI can run and analyze software performance tests
Test computer hardware performance. Test software performance. Recommend changes to improve computer or information systems.
#22899 · Core · 57% automatable
Facilitate and promote activities, such as lunches, seminars, or tours, to foster healthcare information privacy or security awareness within the organization.
text generation — Marketing content and plans drafted; human executes
Market products, services, or events. Promote educational institutions or programs.
#22900 · Core · 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.
#22901 · Core · 32% automatable
Manage the department or supervise clerical workers, directing or controlling activities of personnel in the medical records department.
interpersonal — Healthcare operations accountability and staffing are human
Supervise medical support personnel. Manage healthcare operations.
#22902 · Core · 72% automatable
Monitor changes in legislation and accreditation standards that affect information security or privacy in the computerized healthcare system.
information retrieval — AI monitors news and events affecting operations
Monitor external affairs or events affecting business operations. Evaluate applicable laws and regulations to determine impact on organizational activities.
#22903 · Core · 72% automatable
Plan, develop, 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.
#22904 · Core · 52% automatable
Prepare statistical reports, narrative reports, or graphic presentations of information, such as tumor registry data for use by hospital staff, researchers, or other users.
interpersonal — Medical research presentation needs human delivery
Present medical research reports.
#22905 · Core · 8% automatable
Protect the security of medical records to ensure that confidentiality is maintained.
situated mobility — Physical security presence in world
Maintain security.
#22906 · Core · 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.
#22907 · 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.
#22908 · Core · 32% automatable
Train medical records staff.
interpersonal — Caregiver training needs live modeling and supervision
Train caregivers or other non-medical personnel.
#22909 · Core · 72% automatable
Write or maintain archived procedures, procedural codes, or queries for applications.
text generation — AI drafts data management procedures; human approves
Develop procedures for data management.
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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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