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AI Automation Index
Will AI Replace Hearing Aid Specialists?
Task-level automation exposure for Hearing Aid Specialists: 11 O*NET tasks scored against their work activities, plus the simulator.
E-E-A-T Verified
Developed & audited by Gini Loh Automation Exposure
25%
weighted task index
11 of 11 tasks scored
Median Salary
$65,160 / year
BLS OEWS, May 2025 — this exact occupation
Employment Level
Low
11,270 people hold this job — size, not growth
Projected 2025–35
+19.4%
employment change
900 openings a year · BLS line item
Pay by state
BLS OEWS publishes 43 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.
$35,110 – $82,990
Highest medians
New York $82,990
Nevada $81,800
California $80,060
Tennessee $78,270
Colorado $77,540
Lowest medians
West Virginia $35,110
Nebraska $45,660
Alabama $46,530
Kansas $46,820
South Carolina $47,190
State figures come from the 29-2092 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 25%
Importance-weighted mean of the scored tasks. This is the headline index.
Physical work 31%
Share of weighted tasks in hands-on or machine-operating work activities.
Judgment & influence 48%
Share in analysis, decisions, teaching, directing, advising, or caring for others.
Routine administration 0%
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 0/100
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
11 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) 7%
1 tasks
Medium exposure (≥ 35%) 11%
1 tasks
Low exposure (below 35%) 82%
9 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
#17441 · Core · 30% automatable
Train clients to use hearing aids or other augmentative communication devices.
interpersonal — Patient assistive-equipment instruction is hands-on care
Instruct patients in the use of assistive equipment.
#21189 · Core · 43% automatable
Counsel patients and families on communication strategies and the effects of hearing loss.
decision support — Treatment-effect advice needs clinical tailoring
Advise patients on effects of health conditions or treatments. Counsel family members of clients or patients.
#17439 · Core · 15% automatable
Select and administer tests to evaluate hearing or related disabilities.
physical manipulation — Hearing tests require physical equipment operation
Test patient hearing.
#17440 · Core · 15% automatable
Administer basic hearing tests including air conduction, bone conduction, or speech audiometry tests.
physical manipulation — Hearing tests require physical equipment operation
Test patient hearing.
#17443 · Core · 9% automatable
Maintain or repair hearing aids or other communication devices.
physical manipulation — Hands-on fitting of prostheses to bodies
Adjust prostheses or other assistive devices. Repair medical facility equipment.
#17446 · Core · 18% automatable
Perform basic screening procedures, such as pure tone screening, otoacoustic screening, immittance screening, and screening of ear canal status using otoscope.
physical manipulation — Diagnostic instruments applied to patients by hand
Test patient hearing. Operate diagnostic or therapeutic medical instruments or equipment.
#17442 · Core · 10% automatable
Create or modify impressions for earmolds and hearing aid shells.
physical manipulation — Medical device fabrication is physical manufacturing
Fabricate medical devices.
#17448 · Core · 75% automatable
Read current literature, talk with colleagues, and participate in professional organizations or conferences to keep abreast of developments in audiology.
information retrieval — AI summarizes medical updates; human retains judgment
Maintain medical or professional knowledge.
#17444 · Core · 30% automatable
Demonstrate assistive listening devices (ALDs) to clients.
interpersonal — Patient assistive-equipment instruction is hands-on care
Instruct patients in the use of assistive equipment.
#17447 · Supplemental · 10% automatable
Assist audiologists in performing aural procedures, such as real ear measurements, speech audiometry, auditory brainstem responses, electronystagmography, and cochlear implant mapping.
physical manipulation — Hands-on assistance during examinations
Assist healthcare practitioners during examinations or treatments.
#17445 · Supplemental · 28% automatable
Diagnose and treat hearing or related disabilities under the direction of an audiologist.
decision support — AI suggests differentials; clinician examines and owns diagnosis
Diagnose medical conditions. Treat chronic diseases or disorders.
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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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