Will AI replace electrical and electronic equipment assemblers?AI replacement risk 48% and how the work is changing

United States Manufacturing & Repair Confidence ★★★☆☆

Median annual pay

—

National statistics

Top pay (est.)

—

Top 10% —

Pay in 5 years

—est.

2031

Pay in 10 years

—est.

—

Outlook score

40/100

★★☆☆☆ Below average

AI replacement risk

48%

Moderate

Job growth (10 yr)

—

BLS projections

Will AI replace Electrical and Electronic Equipment Assemblers? AI replacement risk

48%

Moderate

Ranked #493 safest from AI among all U.S. occupations

Very lowLowModerateHighVery high

How AI is changing this job

A written analysis for this occupation is being prepared.

AI replacement risk compares the parts of a job that are easy to hand to AI or software (processing information, documentation, repetitive computer work) with the parts that are hard to automate (physical work, working closely with people, judgment in unpredictable settings), using O*NET work activities, work context, skills and knowledge. The result is a relative position among all occupations in the country, scaled to 0–100%. Methodology →

Skills, education and requirements for Electrical and Electronic Equipment Assemblers

Key skills

Operations Monitoring

3.0

Active Listening

3.0

Reading Comprehension

3.0

Critical Thinking

3.0

Monitoring

2.9

Coordination

2.9

Operation and Control

2.8

Time Management

2.8

O*NET skill level ratings (0–7).

Key knowledge areas

Production and Processing

3.2

Mechanical

2.5

English Language

2.2

Computers and Electronics

2.0

Education and Training

1.9

Administration and Management

1.9

Engineering and Technology

1.8

Design

1.3

What the work involves

Handling and Moving ObjectsControlling Machines and ProcessesUpdating and Using Relevant KnowledgeOrganizing, Planning, and Prioritizing WorkMonitoring Processes, Materials, or SurroundingsPerforming General Physical ActivitiesInspecting Equipment, Structures, or MaterialsEstablishing and Maintaining Interpersonal Relationships

Important abilities

Near VisionVisualizationFinger DexterityArm-Hand SteadinessOral ComprehensionManual Dexterity

Training before entry

None / short demo

49%

6–12 months

24%

1–2 years

Related work experience

None

51%

2–4 years

16%

Up to 1 month

1–3 months

4–6 years

6–12 months

Job Zone 2 — some preparation needed (O*NET)

Difficulty of entry: ★★☆☆☆ Fairly easy (from education, training, experience and Job Zone)

Related occupations

	Occupation	Pay	Outlook	AI risk
1	Maintenance and Repair Workers, General Perform work involving the skills of two or more maintenance or craft occupations to keep machines, mechanical equipment, or the structure of a building in repair.	$49,590	60/100	26%
2	Automotive Service Technicians and Mechanics Diagnose, adjust, repair, or overhaul automotive vehicles.	$50,620	61/100	27%
3	First-Line Supervisors of Production and Operating Workers Directly supervise and coordinate the activities of production and operating workers, such as inspectors, precision workers, machine setters and operators, assemblers, fabricators, and plant and system operators.	$74,450	50/100	47%
4	First-Line Supervisors of Mechanics, Installers, and Repairers Directly supervise and coordinate the activities of mechanics, installers, and repairers.	$79,860	58/100	38%
5	Inspectors, Testers, Sorters, Samplers, and Weighers Inspect, test, sort, sample, or weigh nonagricultural raw materials or processed, machined, fabricated, or assembled parts or products for defects, wear, and deviations from specifications.	$48,570	45/100	55%
6	Industrial Machinery Mechanics Repair, install, adjust, or maintain industrial production and processing machinery or refinery and pipeline distribution systems.	$64,520	74/100	26%

Pay and employment figures are national statistics. Projected pay, outlook scores and AI replacement risk are estimates from the Shigoto Zukan model, not guarantees. To request a correction, use the contact form. How to read the data

Sources: U.S. Bureau of Labor Statistics (OEWS; Employment Projections); O*NET 31.0 Database by USDOL/ETA (CC BY 4.0), modified by Shigoto Zukan. Pay ranges, projections and scores are Shigoto Zukan estimates.