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The AI Resilience Report helps you understand how AI is likely to impact your current or future career. Drawing on data from over 1,500 occupations, it provides a clear snapshot to support informed career decisions.
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Mostly Resilient
Last Update: 4/23/2026
Your role’s AI Resilience Score is
60.5%
Median Score
Meaningful human contribution
Measures the parts of the occupation that still require a human touch. This score averages data from up to four AI exposure datasets, focusing on the role’s resilience against automation.
Med
Long-term employer demand
Predicts the health of the job market for this role through 2034. Using Bureau of Labor Statistics data, it balances projected annual job openings (60%) with overall employment growth (40%).
High
Sustained economic opportunity
Measures future earning potential and career flexibility. This score is a blend of total projected labor income (67%) and the role’s inherent ability to adapt to economic and technological shifts (33%).
Med
This reflects the reliability of your score based on the number of data sources available for this career and how closely those sources agree on the outlook. A higher confidence means more consistent evidence from labor experts and AI models.
Most data sources align, with only minor variation. This is a well-supported result.
Contributing sources
AI Resilience Report forMobile Heavy Equipment Mechanics, Except Engines
Mobile Heavy Equipment Mechanics, Except Engines are somewhat more resilient to AI impacts than most occupations, according to our analysis of 6 sources.
Mobile Heavy Equipment Mechanics are "Mostly Resilient" to AI impact because AI tools mainly help them by spotting issues early and providing guidance, but they still rely heavily on human skills like problem-solving and physical dexterity to fix machines. AI can predict breakdowns and offer instructions, but it doesn't replace the need for mechanics to use their hands and experience to make repairs.
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Mobile Heavy Equipment Mechanics are "Mostly Resilient" to AI impact because AI tools mainly help them by spotting issues early and providing guidance, but they still rely heavily on human skills like problem-solving and physical dexterity to fix machines. AI can predict breakdowns and offer instructions, but it doesn't replace the need for mechanics to use their hands and experience to make repairs.
Read full analysisAnalysis of Current AI Resilience
Mobile Heavy Equip Mechanic
Updated Quarterly • Last Update: 2/17/2026
How is AI changing Mobile Heavy Equip Mechanic jobs?
Heavy equipment mechanics use a mix of old and new tools. Today, AI mostly helps with planning and fault-finding. For example, machines often have sensors and AI systems that predict breakdowns and cut downtime by up to 50% [1].
Computer vision can scan parts for cracks or corrosion before it’s dangerous [2]. Augmented reality (AR) headsets and apps can overlay instructions on equipment, speeding training and reducing errors [3] [4]. In other words, AI is augmenting the mechanic’s work by giving more information.
Many key tasks are still done by hand. Mechanics must read manuals and then use tools to disassemble, fit parts, and fix machines. [5] [5]. Jobs like cleaning, lubricating, replacing bearings or rewiring electrical systems require careful human work [5] [5].
Even with AR guides, a person must do the actual repairs. Researchers note that AR helps navigation through complex repairs, but a human still performs the hands-on work [4] [3]. In short, AI today mostly assists the mechanic – it helps spot problems and suggest steps, but it does not replace the person turning the wrench.
Sources
How fast is AI adoption growing for Mobile Heavy Equip Mechanic?
Companies adopt AI tools when they see clear benefits. In construction and mining, firms use telematics and AI to prevent breakdowns, saving money and keeping projects on schedule [1] [2]. AR training tools are already available to help new mechanics learn quickly [3].
With many experienced mechanics retiring, businesses also use AI and AR to capture expert knowledge for younger workers [3] [2]. These factors make AI appealing.
At the same time, adoption can be slow. Installing and maintaining sensors or VR gear costs money, and older machines often need upgrades. Small shops may wait if tech costs more than hiring a person.
Heavy-equipment work often happens outdoors in rough conditions, so not every AI gadget works well. Also, people trust a skilled mechanic’s judgement — AI has to prove itself before teams rely on it fully.
Overall, AI in heavy equipment work is growing but mainly as a helper. It makes mechanics’ jobs better (for example, by flagging issues early [2] [3]), but the human skills of problem-solving, adaptability, and craftsmanship remain critical. Young learners can feel hopeful: tools like AI, AR, and diagnostics will be part of the job, but the core of being a mechanic—using hands, eyes, and experience to fix big machines—will still be needed [3] [2].
Sources
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More Career Info
Career: Mobile Heavy Equipment Mechanics, Except Engines
They fix and maintain large machines used in construction and farming to ensure they work safely and efficiently.
Parent Careers
Employment & Wage Data
Median Wage
$63,980
Jobs (2024)
188,700
Growth (2024-34)
+5.8%
Annual Openings
16,500
Education
High school diploma or equivalent
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2024-2034
Task-Level AI Resilience Scores
AI-generated estimates of task resilience over the next 3 years
1
Clean, lubricate, and perform other routine maintenance work on equipment and vehicles.
2
Fit bearings to adjust, repair, or overhaul mobile mechanical, hydraulic, and pneumatic equipment.
3
Weld or solder broken parts and structural members, using electric or gas welders and soldering tools.
4
Adjust and maintain industrial machinery, using control and regulating devices.
5
Repair and replace damaged or worn parts.
6
Clean parts by spraying them with grease solvent or immersing them in tanks of solvent.
7
Assemble gear systems, and align frames and gears.
Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.
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