58
/100

SOC 49-9043

Maintenance Workers, Machinery

ElevatedFrey/Osborne: 86.0%

Risk Score

โš ๏ธ

58/100

Elevated

US Employment

๐Ÿ‘ฅ

56,540

Total workers

Median Wage

๐Ÿ’ฐ

$61K

$40K โ€“ $84K

Projected Growth

๐Ÿ“ˆ

-2.8%

2023-2033 (BLS)

GenAI Exposure

๐Ÿค–

24/100

Low exposure

How we calculate these numbers โ†’

๐Ÿ’ก Maintenance Workers, Machinery face a risk score of 58/100 โ€” 14 points above the national average of 44. With only 24/100 GenAI exposure, most core tasks remain resistant to current AI capabilities. See our methodology โ†’

๐Ÿ’ก Workers in this field earn $61K ($14K above the national median). The 3 recommended career transitions all maintain competitive wages while reducing automation exposure. Explore transition paths โ†’

๐Ÿ” AI Impact Analysis

With a risk score of 58/100, Maintenance Workers, Machinery faces moderate automation pressure. While tasks like augmented reality-guided remote diagnostics are increasingly handled by AI, the role retains significant human elements. The 56,540 workers in this occupation should focus on strengthening skills in adapting repairs to non-standard or legacy equipment and customer communication about technical issues to stay ahead. The role will likely evolve rather than disappear.

Will AI Replace Maintenance Workers, Machinery?

Read our full analysis with verdict, risk factors, safe tasks, and career transition paths โ†’

โš ๏ธ Top Risk Factors

1

Augmented reality-guided remote diagnostics

2

Predictive maintenance AI reducing reactive repair needs

3

AI parts inventory and supply chain optimization

4

Automated fault detection via IoT sensor networks

๐Ÿ›ก๏ธ Tasks Safe from Automation

โœ“

Adapting repairs to non-standard or legacy equipment

โœ“

Customer communication about technical issues

โœ“

Working in confined, elevated, or hazardous spaces

โœ“

Diagnosing novel equipment failures through physical inspection

๐Ÿ“Š Task Automation Breakdown

Based on O*NET task analysis and GenAI exposure scoring. Shows the estimated proportion of this occupation's core tasks that are automatable by current AI, augmented by AI tools, or require essential human skills.

๐Ÿ“‹ O*NET Task Profile

โ€ข

Dismantle machines and remove parts for repair, using hand tools, chain falls, jacks, cranes, or hoists.

โ€ข

Reassemble machines after the completion of repair or maintenance work.

โ€ข

Record production, repair, and machine maintenance information.

โ€ข

Lubricate or apply adhesives or other materials to machines, machine parts, or other equipment according to specified procedures.

โ€ข

Install, replace, or change machine parts and attachments, according to production specifications.

๐Ÿ’ป Technology Skills

โ€ข

Facilities management software

โ€ข

Data base user interface and query software

โ€ข

Enterprise resource planning ERP software

โ€ข

Spreadsheet software

โ€ข

Office suite software

๐ŸŽ“ Key Knowledge Areas

โ€ข

Mechanical

โ€ข

Production and Processing

โ€ข

Administration and Management

โ€ข

English Language

โ€ข

Design

๐Ÿ“Š vs National Average

Median Wage$61K
+$14K

National avg: $46K

Risk Score58/100
+14

National avg: 44/100

GenAI Exposure24/100
-14

National avg: 38/100

Projected Growth-2.8%
-6.5%

National avg: 3.7%

๐Ÿ”„ Career Transition Paths

OccupationRiskWageOverlap
Engineers20$106K61%
Electrical Power-Line Installers and Repairers28$93K75%
Supervisors of Installation, Maintenance, and Repair Workers33$78K80%