Installation, Maintenance, and Repair · United States (national)
First-Line Supervisors of Mechanics, Installers, and Repairers
How exposed this work is to automation, shown as ranges with the reasoning and sources.
The short version: this role is moderately exposed to automation, and meaningful change looks likely over the next 5 to 10 years.
It is a sourced range, not a verdict, and the detail is below.
Built on O*NET tasks, BLS pay and projections, and peer-reviewed AI-exposure research. Sources shown.
Data snapshot SNAPSHOT-2026-11-06. How it works
AI / softwarerange 14.9 to 38.9
Physical / roboticsrange 35.2 to 59.2
When the change is likely
Partial, 5 to 10 yearslocal demand stable
What to do about it
Use AI to outpace AI.
Strategies to protect your livelihood, most important first.
1
Use your 5 to 10 year runway
Change here is gradual. Build resilient skills steadily and watch the signals rather than waiting for a shock.
2
Move up from the task to the system
Robotics targets the physical work. Shift toward supervising, maintaining, or programming the automation instead of competing with it.
3
Pivot toward First-Line Supervisors of Passenger Attendants
It is skill-adjacent and less exposed (31.6 vs 47). A lateral move now beats a forced one later.
4
Build a financial buffer
Keep 6 to 12 months of expenses and diversify your income, so a disruption is a setback rather than a catastrophe.
5
Add a recognised credential
A certification or license raises the bar against automation and signals value in a tightening market.
Keep the monitor on
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Which of my tasks are exposed
Inspect, test, and measure completed work, using devices such as hand tools or gauges to verify conformance to standards or repair requirements.
100.0
Inspect and monitor work areas, examine tools and equipment, and provide employee safety training to prevent, detect, and correct unsafe conditions or violations of procedures and safety rules.
100.0
Interpret specifications, blueprints, or job orders to construct templates and lay out reference points for workers.
50.0
Monitor employees' work levels and review work performance.
50.0
Perform skilled repair or maintenance operations, using equipment such as hand or power tools, hydraulic presses or shears, or welding equipment.
47.2
Compute estimates and actual costs of factors such as materials, labor, or outside contractors.
47.2
Monitor tool and part inventories and the condition and maintenance of shops to ensure adequate working conditions.
50.0
Requisition materials and supplies, such as tools, equipment, or replacement parts.
50.0
Longer, orange bars are more automatable; short green bars are resistant.
What is driving my result
lowers risk
raises risk
Task: Inspect, test, and measure completed work, using devices such as hand tools or gauges to verify conformance to standards or repair requirements.
Task: Inspect and monitor work areas, examine tools and equipment, and provide employee safety training to prevent, detect, and correct unsafe conditions or violations of procedures and safety rules.
Lower-risk adjacent roles
First-Line Supervisors of Passenger Attendants
31.6
First-Line Supervisors of Helpers, Laborers, and Material Movers, Hand
35.6
First-Line Supervisors of Material-Moving Machine and Vehicle Operators
47.1
A full, ranked mitigation plan is part of the paid tiers.
How this score is calculated
Map First-Line Supervisors of Mechanics, Installers, and Repairers to its standard O*NET task list (8 core tasks).
Score each task for AI/software exposure (Eloundou et al. 2023) and physical/robotics exposure (an O*NET work-context proxy), each 0 to 100.
The two axis scores are the task averages: AI 26.9, robotics 47.2.
The timeline comes from the higher axis (47.2), shifted for local demand (stable), and seniority. It is read against your remaining working years.
Ranges are about ±12 points. A backtest against real BLS employment change shows the risk ranking holds in aggregate, but individual outcomes are predicted weakly, so results are ranges, never a flat verdict.
Sources: O*NET, Eloundou et al. (2023), GPTs are GPTs, O*NET Work Context, BLS CPI-U, BLS OEWS.
Snapshot SNAPSHOT-2026-11-06. Full method and backtest on How it works.