Medical equipment repairers
SOC Code: 49-9062
Medical equipment repairers carries a 33% AI exposure score (Medium automation risk), with a median annual wage of $62,630 and +12.9% projected employment growth from 2024 to 2034 (BLS), affecting approximately 68,000 workers. Full task breakdown, skills, and employer data are below.
Proportion of tasks susceptible to AI automation (O*NET analysis)
AI Exposure vs Industry Growth
Total occupations tracked
832
Covering all SOC major groups
Data currency
2024
BLS Employment Projections
AI exposure avg
40%
Fleet-wide median across all roles
Composite score weighing O*NET task data completeness, BLS projection methodology, and cross-validation with employer risk grades.
Employment Projections
Occupation Insight
Medical equipment repairers (SOC 49-9062) carries an AI exposure score of 33%, placing it in the Medium automation-risk tier. This score is computed from O*NET Database 30.0 task-level analysis, where each task an 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 economic context matters alongside the risk score. BLS counted approximately 68,000 workers in this occupation in 2024, and projects a +12.9% change through 2034 — a strong growth outlook that compensates meaningfully for automation risk. Median annual compensation stands at $62,630, reflecting both skill scarcity and the value employers place on the tasks that remain difficult to automate. Entry typically requires Associate's degree, plus None of related experience.
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 equipment repairers. Adjacent occupations shown further down offer lateral moves that preserve industry knowledge while potentially reducing exposure. Pair the AI exposure score with the BLS employment projection and wage percentiles above for a complete career assessment.
Education & Entry Requirements
Top Tasks (O*NET)
- 1. Test or calibrate components or equipment, following manufacturers' manuals and troubleshooting techniques, using hand tools, power tools, or measuring devices.
- 2. Perform preventive maintenance or service, such as cleaning, lubricating, or adjusting equipment.
- 3. Inspect, test, or troubleshoot malfunctioning medical or related equipment, following manufacturers' specifications and using test and analysis instruments.
- 4. Keep records of maintenance, repair, and required updates of equipment.
- 5. Disassemble malfunctioning equipment and remove, repair, or replace defective parts, such as motors, clutches, or transformers.
- 6. Examine medical equipment or facility's structural environment and check for proper use of equipment to protect patients and staff from electrical or mechanical hazards and to ensure compliance with safety regulations.
- 7. Install medical equipment.
- 8. Test, evaluate, and classify excess or in-use medical equipment and determine serviceability, condition, and disposition, in accordance with regulations.
- 9. Plan and carry out work assignments, using blueprints, schematic drawings, technical manuals, wiring diagrams, or liquid or air flow sheets, following prescribed regulations, directives, or other instructions as required.
- 10. Study technical manuals or attend training sessions provided by equipment manufacturers to maintain current knowledge.
Key Skills Required
- Repairing
- Equipment Maintenance
- Troubleshooting
- Operations Monitoring
- Quality Control Analysis
- Reading Comprehension
- Critical Thinking
- Active Listening
- Active Learning
- Complex Problem Solving
Knowledge Areas
- Mechanical
- Computers and Electronics
- Customer and Personal Service
- English Language
- Engineering and Technology
- Mathematics
- Public Safety and Security
- Education and Training
- Production and Processing
- Physics
Frequently Asked Questions
Will AI replace Medical equipment repairers?
Medical equipment repairers has an AI exposure score of 33%, 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 equipment repairers?
According to BLS Employment Projections 2024-2034, Medical equipment repairers is projected to grow by 12.9% over the decade. Current employment stands at approximately 68,000 workers.
What skills are needed for Medical equipment repairers?
Key skills for Medical equipment repairers include Repairing, Equipment Maintenance, Troubleshooting, and others. Typical entry-level education is Associate's degree.
How much do Medical equipment repairers earn?
The median annual wage for Medical equipment repairers is $62,630, 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 equipment repairers?
The typical entry-level education for Medical equipment repairers is Associate's degree. 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 equipment repairers?
Medical equipment repairers 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.
Related Occupations
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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).