46
/100

SOC 49-3042

Mobile Heavy Equipment Mechanics, Except Engines

ElevatedFrey/Osborne: 40.0%

Risk Score

โš ๏ธ

46/100

Elevated

US Employment

๐Ÿ‘ฅ

180,270

Total workers

Median Wage

๐Ÿ’ฐ

$64K

$45K โ€“ $92K

Projected Growth

๐Ÿ“ˆ

+5.8%

2023-2033 (BLS)

GenAI Exposure

๐Ÿค–

45/100

Moderate exposure

How we calculate these numbers โ†’

๐Ÿ’ก Mobile Heavy Equipment Mechanics, Except Engines face a risk score of 46/100 โ€” 2 points above the national average of 44. With only 45/100 GenAI exposure, most core tasks remain resistant to current AI capabilities. See our methodology โ†’

๐Ÿ’ก Workers in this field earn $64K ($18K 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 46/100, Mobile Heavy Equipment Mechanics, Except Engines faces moderate automation pressure. While tasks like predictive maintenance ai reducing reactive repair needs are increasingly handled by AI, the role retains significant human elements. The 180,270 workers in this occupation should focus on strengthening skills in customer communication about technical issues and working in confined, elevated, or hazardous spaces to stay ahead. The role will likely evolve rather than disappear.

Will AI Replace Mobile Heavy Equipment Mechanics, Except Engines?

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

โš ๏ธ Top Risk Factors

1

Predictive maintenance AI reducing reactive repair needs

2

Augmented reality-guided remote diagnostics

3

Automated fault detection via IoT sensor networks

4

Robotic inspection of hard-to-reach equipment

๐Ÿ›ก๏ธ Tasks Safe from Automation

โœ“

Customer communication about technical issues

โœ“

Working in confined, elevated, or hazardous spaces

โœ“

Hands-on fine motor work in intricate machinery

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

Repair and replace damaged or worn parts.

โ€ข

Test mechanical products and equipment after repair or assembly to ensure proper performance and compliance with manufacturers' specifications.

โ€ข

Operate and inspect machines or heavy equipment to diagnose defects.

โ€ข

Read and understand operating manuals, blueprints, and technical drawings.

โ€ข

Dismantle and reassemble heavy equipment using hoists and hand tools.

๐Ÿ’ป Technology Skills

โ€ข

Data base user interface and query software

โ€ข

Materials requirements planning logistics and supply chain software

โ€ข

Facilities management software

โ€ข

Spreadsheet software

โ€ข

Office suite software

๐ŸŽ“ Key Knowledge Areas

โ€ข

Mechanical

โ€ข

Customer and Personal Service

โ€ข

Mathematics

โ€ข

Computers and Electronics

โ€ข

Public Safety and Security

๐Ÿ“Š vs National Average

Median Wage$64K
+$18K

National avg: $46K

Risk Score46/100
+2

National avg: 44/100

GenAI Exposure45/100
+7

National avg: 38/100

Projected Growth5.8%
+2.1%

National avg: 3.7%

๐Ÿ”„ Career Transition Paths

OccupationRiskWageOverlap
Engineers20$106K57%
Electrical Power-Line Installers and Repairers28$93K81%
Supervisors of Installation, Maintenance, and Repair Workers33$78K71%