Heavy vehicle and mobile equipment service technicians
Physical, social, or oversight-heavy work that AI augments rather than replaces.
SOC 49-3040 · Installation Maintenance And Repair
Signal composition
how the 0-100 score is assembled
By seniority
multiplicative adjustment from category curve
Entry-level roles carry the brunt because they concentrate the most automatable subset of tasks. Senior work is insulated by judgment, relationships, and accountability.
Task-level analysis
scored 0-100 for current-generation AI feasibility, weighted by BLS-stated importance
Maintain logs of equipment condition and work performed
AI can auto-populate logs from diagnostic data, structure maintenance records, and generate reports from technician inputs with minimal oversight—much of the documentation burden can be automated, though technicians must still verify accuracy of captured work details.
BLS evidence: The duties section lists 'Maintain logs of equipment condition and work performed,' and organizational skills are noted for maintaining accurate service records.
Consult equipment operating manuals, blueprints, and technical drawings
AI can parse technical documents, extract relevant specifications, and cross-reference manuals effectively, but technicians must still interpret these in context of physical equipment state and translate into hands-on action—AI provides substantial assistance but human integration remains essential.
BLS evidence: The first item in the duties list is 'Consult equipment operating manuals, blueprints, and drawings.'
Recalibrate components and make adjustments through onboard computer programs
AI can suggest calibration parameters and guide adjustment sequences through software interfaces, but requires physical connection to equipment computers, validation against mechanical behavior, and judgment about whether adjustments resolve real-world performance issues—significant AI assistance with human execution.
BLS evidence: The page mentions technicians 'repair, replace, and recalibrate components' and may make 'adjustments through an onboard computer program.'
Diagnose and identify malfunctions using computerized diagnostic tools and equipment
AI can interpret diagnostic codes and suggest likely causes, but physical connection to equipment, navigating unpredictable failure modes in heavy machinery, and validating diagnoses in situ requires substantial human judgment and physical presence that current AI+robotics cannot replicate autonomously.
BLS evidence: Service technicians use diagnostic computers and equipment to identify problems, and the page emphasizes troubleshooting skills as important for finding the source of malfunctions.
Perform scheduled maintenance such as cleaning and lubricating parts
While routine, this task requires physical access to diverse equipment geometries, manual application of lubricants in hard-to-reach areas, and tactile assessment of part condition—fine motor skills and environmental adaptability that current robotics cannot match across varied heavy equipment.
BLS evidence: The duties section explicitly includes 'Perform scheduled maintenance, such as cleaning and lubricating parts' as a regular task.
Overhaul and test major components including engines, hydraulic systems, and electrical systems
Overhauling engines and hydraulic systems demands complex physical manipulation, heavy lifting, precise torque application, and testing under load in variable conditions—tasks requiring human strength, dexterity, and judgment that AI-enabled robotics cannot perform in typical service settings.
BLS evidence: The page states technicians 'Overhaul and test major components, such as engines, hydraulic systems, and electrical systems' and emphasizes they repair and maintain these critical systems.
Inspect, repair, and replace defective or worn parts such as bearings, pistons, and gears
Requires precise manual dexterity, significant physical strength, work in confined/awkward spaces within heavy equipment, and real-time tactile feedback to handle worn parts safely—capabilities far beyond current robotics in unstructured field environments.
BLS evidence: The duties section explicitly lists 'Inspect, repair, and replace defective or worn parts, such as bearings, pistons, and gears' as a primary task.
Disassemble and reassemble heavy equipment and major components
Disassembly and reassembly of heavy equipment involves managing components weighing hundreds of pounds, working in non-standardized configurations, and applying mechanical intuition about fit and wear—physical and cognitive demands well beyond current automation capabilities.
BLS evidence: The duties section lists 'Disassemble and reassemble heavy equipment and components,' and the page notes this may involve disassembling and reassembling major equipment.
Travel to worksites to repair large equipment in the field
Requires physical travel to unpredictable outdoor worksites, transporting tools and parts, and performing repairs in uncontrolled field conditions with variable weather, terrain, and equipment positioning—fundamentally a physical human activity with no AI substitute.
BLS evidence: The page states 'Travel to worksites to repair large equipment, such as cranes' and notes that more experienced technicians specialize in field service.
Task heatmap
automation score by task, sorted by weighted contribution
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External signals and sources
category-level priors and BLS fields that feed the four non-task signals
- Karpathy/BLS Digital AI Exposure (0-10 scale rescaled to 0-100)
- BLS projected outlook: Faster than average (6%)
- Indeed demand signal (monthly refresh pending)
- BLS typical entry-level education: High school diploma or equivalent
- Credential trend signal (annual refresh)
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