Medical appliance technicians
SOC Code: 51-9082
Medical appliance technicians carries a 24% AI exposure score (Medium automation risk), with a median annual wage of $47,060 and +3.7% projected employment growth from 2024 to 2034 (BLS), affecting approximately 12,000 workers. Full task breakdown, skills, and employer data are below.
Proportion of tasks susceptible to AI automation (O*NET analysis)
At 24% AI exposure, Medical appliance technicians sits 13 points below the 37.2% average across 832 U.S. occupations - more exposed than 13% of them. It ranks among the more AI-resilient roles in the dataset.
Career outlook score
58/100
Medical appliance technicians, weighted across 3 of 3 tracked dimensions
A weighted composite of median wage, projected growth, and AI-automation security (inverted exposure), each benchmarked against every other tracked occupation. It describes this occupation's standing across those three dimensions, not a guarantee of future outcomes.
- Median wage F $47,060
Annual median wage, percentile rank vs all tracked occupations
- Projected growth C+ +3.7%
Projected employment change, 2024-2034, BLS Employment Projections
- AI exposure (inverted) A 24% exposure
Lower O*NET task-automability scores lower risk; this dimension scores security, not exposure
Home health and personal care aides is #1 of 832 occupations by employment (4.3M, AI exposure rank #392 at 35%) vs. Bookkeeping, accounting, and auditing clerks #1 by AI task exposure (95%, employment rank #17 at 1.6M).
Automation-risk inventory
Exclusive cut of 832 occupations by PlainWorkforce automation-risk band. Orthogonal to the continuous AI-exposure distribution chart below and to this occupation's single risk badge, this is the corpus band mix, with Medical appliance technicians in the Medium band.
Credential × growth standing
Open entry with non-declining BLS pace
Medical appliance technicians keeps an HS / some college bar (333 of 832) and sits in Average (378 of 832). Lower formal gates with a non-shrinking employment line - skill and AI desks matter more than credentials here.
Where Medical appliance technicians sits among all occupations
AI-exposure score distribution across 832 U.S. occupations (O*NET task analysis). This occupation is marked in rose.
Where Medical appliance technicians sits by AI exposure
AI-exposure score distribution across U.S. occupations (O*NET task analysis)
24% Among the lowest lower than 87% of 832 occupations
Occupations, banded by AI-exposure score
Each bar is a band; taller bars hold more occupations. The dashed line + filled bar mark this entry. Hover or tap any bar for its full count and share, and where it sits relative to this entry.
Source O*NET task data (U.S. Department of Labor) · BLS 2024–2034
Source: O*NET task data (U.S. Department of Labor); AI-exposure scores are PlainWorkforce's analysis. As of BLS 2024–2034.
Medical appliance technicians vs. its occupational neighbors
AI exposure (horizontal) vs projected 2024–2034 growth (vertical) for occupations in the same SOC group. Medical appliance technicians is marked in rose; the top-left corner is the most future-proof.
Source: BLS Employment Projections 2024–2034 (growth) and O*NET (AI-exposure analysis by PlainWorkforce).
Employment Projections
Where This Score Comes From
Medical appliance technicians's Medium automation-risk tier is computed from O*NET Database 30.0 task-level analysis, where each documented task the occupation performs is evaluated against current generative AI, robotic process automation, and machine-learning capabilities. A score below 40% reflects tasks anchored in physical dexterity, unstructured environments, or high-touch human interaction that current AI cannot reliably replicate.
The employment, wage, and education figures above come from a second, separate federal source: BLS Employment Projections 2024–2034, matched to the O*NET task data by Standard Occupational Classification (SOC 51-9082) code, with the wage figure cross-validated against the BLS Occupational Employment and Wage Statistics (OEWS) May 2024 survey. BLS figures are presented exactly as published, with no adjustment on our part; the SOC-code match is what lets Medical appliance technicians be compared directly against every other tracked occupation on the same basis, not just roles that happen to share a job title.
For career planners, this profile should be read alongside the task, skill, and knowledge breakdowns below and the list of employers whose workforce composition includes Medical appliance technicians. Adjacent occupations shown further down offer lateral moves that preserve industry knowledge while potentially reducing exposure.
Education & Entry Requirements
Top Tasks (O*NET)
- 1. Drill and tap holes for rivets, and glue, weld, bolt, or rivet parts together to form prosthetic or orthotic devices.
- 2. Read prescriptions or specifications to determine the type of product or device to be fabricated and the materials and tools required.
- 3. Make orthotic or prosthetic devices, using materials such as thermoplastic and thermosetting materials, metal alloys and leather, and hand or power tools.
- 4. Bend, form, and shape fabric or material to conform to prescribed contours of structural components.
- 5. Construct or receive casts or impressions of patients' torsos or limbs for use as cutting and fabrication patterns.
- 6. Repair, modify, or maintain medical supportive devices, such as artificial limbs, braces, or surgical supports, according to specifications.
- 7. Cover or pad metal or plastic structures or devices, using coverings such as rubber, leather, felt, plastic, or fiberglass.
- 8. Test medical supportive devices for proper alignment, movement, or biomechanical stability, using meters and alignment fixtures.
- 9. Lay out and mark dimensions of parts, using templates and precision measuring instruments.
- 10. Fit appliances onto patients, and make any necessary adjustments.
Key Skills Required
- Active Listening
- Critical Thinking
- Quality Control Analysis
- Reading Comprehension
- Speaking
- Troubleshooting
- Social Perceptiveness
- Operations Monitoring
- Complex Problem Solving
- Monitoring
Knowledge Areas
- Production and Processing
- Customer and Personal Service
- English Language
- Mechanical
- Design
- Education and Training
- Mathematics
- Administration and Management
- Administrative
- Engineering and Technology
Frequently Asked Questions
Will AI replace Medical appliance technicians?
Medical appliance technicians has an AI exposure score of 24%, indicating a medium level of automation risk. The majority of tasks in this role require human judgment, creativity, or physical presence that AI cannot easily replicate.
What is the job outlook for Medical appliance technicians?
According to BLS Employment Projections 2024-2034, Medical appliance technicians is projected to grow by 3.7% over the decade. Current employment stands at approximately 12,000 workers.
What skills are needed for Medical appliance technicians?
Key skills for Medical appliance technicians include Active Listening, Critical Thinking, Quality Control Analysis, and others. Typical entry-level education is High school diploma or equivalent.
How much do Medical appliance technicians earn?
The median annual wage for Medical appliance technicians is $47,060, according to BLS Occupational Employment and Wage Statistics (May 2024). Actual earnings vary by location, experience, industry, and employer. The BLS publishes detailed wage percentiles by region in its Occupational Employment and Wage Statistics program.
What education is required for Medical appliance technicians?
The typical entry-level education for Medical appliance technicians is High school diploma or equivalent. Employers generally expect None of related work experience. On-the-job training typically involves Moderate-term on-the-job training. Requirements can vary by employer and specialization.
Which companies employ Medical appliance technicians?
Medical appliance technicians roles exist across many industries and employers. Workforce composition is estimated from BLS industry-occupation employment distributions matched to SEC-registered public companies.
AI Exposure Rating
Medium automation risk based on 10 analyzed tasks. Most tasks require human judgment and are resistant to automation.
Nationwide occupations with similar workforce profiles
Two data-derived peer sets for Medical appliance technicians: AI-exposure neighbors and BLS 2034 growth neighbors (distinct comparison neighborhoods, cross-occupation).
Similar AI exposure score
Nearest O*NET task-automability scores nationwide (24% here).
- Audiologists · AI exposure 24%
- Brickmasons and blockmasons · AI exposure 24%
- Dental laboratory technicians · AI exposure 24%
- Extruding and drawing machine setters, operators, and tenders, metal and plastic · AI exposure 24%
Similar projected growth (2024–2034)
Nearest BLS employment change rates nationwide (+3.7% here).
- Chemical technicians · growth +3.7%
- First-line supervisors of transportation and material moving workers, except aircraft cargo handling supervisors · growth +3.7%
- Hotel, motel, and resort desk clerks · growth +3.7%
- Insurance sales agents · growth +3.7%
Peers are nearest-neighbor matches on published BLS + O*NET metrics among occupations with ≥10,000 workers in 2024; corpus ranks above sort the full tracked set.
Related Occupations
Showing 6 of 81 occupations with a comparable automation-risk profile.
What to do with this
Use Medical appliance technicians' numbers above to compare, not just read in isolation.
- Compare Medical appliance technicians side by side against another occupation on wage, growth, and AI exposure. Workforce comparison tool
- Understand how the AI exposure score above is actually calculated before treating it as a verdict. Reading AI exposure scores
- See the full ranked list of occupations with the lowest automation exposure nationwide. Safest occupations from AI
AI exposure scores estimate task automatability from O*NET data; they are not a certainty of job loss, and BLS growth projections are estimates, not guarantees.
Data sources: Bureau of Labor Statistics Employment Projections 2024–2034 and O*NET Database 30.0. Employment figures are rounded. Wage data from BLS Occupational Employment Statistics (OES).