Electric motor, power tool, and related repairers
SOC Code: 49-2092
Electric motor, power tool, and related repairers carries a 23% AI exposure score (Medium automation risk), with a median annual wage of $53,990 and +3.4% projected employment growth from 2024 to 2034 (BLS), affecting approximately 17,100 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
Electric motor, power tool, and related repairers (SOC 49-2092) carries an AI exposure score of 23%, 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 17,100 workers in this occupation in 2024, and projects a +3.4% change through 2034 — modest growth that keeps the occupation viable even as tasks evolve. Median annual compensation stands at $53,990, reflecting both skill scarcity and the value employers place on the tasks that remain difficult to automate. Entry typically requires High school diploma or equivalent, plus Less than 5 years 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 Electric motor, power tool, and related 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. Inspect and test equipment to locate damage or worn parts and diagnose malfunctions, or read work orders or schematic drawings to determine required repairs.
- 2. Verify and adjust alignments and dimensions of parts, using gauges and tracing lathes.
- 3. Reassemble repaired electric motors to specified requirements and ratings, using hand tools and electrical meters.
- 4. Measure velocity, horsepower, revolutions per minute (rpm), amperage, circuitry, and voltage of units or parts to diagnose problems, using ammeters, voltmeters, wattmeters, and other testing devices.
- 5. Repair and rebuild defective mechanical parts in electric motors, generators, and related equipment, using hand tools and power tools.
- 6. Lift units or parts such as motors or generators, using cranes or chain hoists, or signal crane operators to lift heavy parts or subassemblies.
- 7. Record repairs required, parts used, and labor time.
- 8. Disassemble defective equipment so that repairs can be made, using hand tools.
- 9. Adjust working parts, such as fan belts, contacts, and springs, using hand tools and gauges.
- 10. Steam-clean polishing and buffing wheels to remove abrasives and bonding materials, and spray, brush, or recoat surfaces as necessary.
Key Skills Required
- Repairing
- Equipment Maintenance
- Troubleshooting
- Critical Thinking
- Equipment Selection
- Quality Control Analysis
- Complex Problem Solving
- Operations Monitoring
- Operation and Control
- Active Listening
Knowledge Areas
- Mechanical
- Production and Processing
- English Language
- Administration and Management
- Customer and Personal Service
- Mathematics
- Education and Training
- Public Safety and Security
- Engineering and Technology
- Administrative
Frequently Asked Questions
Will AI replace Electric motor, power tool, and related repairers?
Electric motor, power tool, and related repairers has an AI exposure score of 23%, 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 Electric motor, power tool, and related repairers?
According to BLS Employment Projections 2024-2034, Electric motor, power tool, and related repairers is projected to grow by 3.4% over the decade. Current employment stands at approximately 17,100 workers.
What skills are needed for Electric motor, power tool, and related repairers?
Key skills for Electric motor, power tool, and related repairers include Repairing, Equipment Maintenance, Troubleshooting, and others. Typical entry-level education is High school diploma or equivalent.
How much do Electric motor, power tool, and related repairers earn?
The median annual wage for Electric motor, power tool, and related repairers is $53,990, 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 Electric motor, power tool, and related repairers?
The typical entry-level education for Electric motor, power tool, and related repairers is High school diploma or equivalent. Employers generally expect Less than 5 years 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 Electric motor, power tool, and related repairers?
Electric motor, power tool, and related 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).