Will AI replace First-Line Supervisors of Mechanics, Installers, and Repairers?
Work in First-Line Supervisors of Mechanics, Installers, and Repairers sits in the in-between: AI reaches some of it (~41% in theory) but is only measured doing about 10% today — part human, part machine.
O*NET-SOC 49-1011
How your 17 core tasks split
Top = what GPT-4 judged AI could speed up. Bottom = how much AI was actually used for these tasks (Anthropic's March 2026 report, usage from Aug & Nov 2025). The gap is the real story.
Back in 2023, GPT-4 judged AI could, in theory, assist with a moderate share of this job's tasks (~41%). By late 2025, real-world AI use had reached about 10% of its task activity (growing but still limited). The gap between that 2023 forecast and today is the real story.
Where this job sits among 738 jobs
Each dot is one of 738 U.S. jobs. Right = AI can do more of it. Up = AI is actually used more.
The signals here line up
Theoretical reach (~41%), real-world use (~10%) and the task-level picture mostly agree — so this read is more reliable than for jobs where the signals contradict each other. Even so, AI-risk estimates shift by model (a 2026 study saw the "high-risk" share swing 2.7%–51.5%), so treat these as directional, not destiny.
See all 17 tasks, ratedBased on real task-level AI scores — click to collapse
- None — AI cannot fully do any core task alone yet.
- Interpret specifications, blueprints, or job orders to construct templates and lay out reference points for workers.
- Monitor employees' work levels and review work performance.
- Compute estimates and actual costs of factors such as materials, labor, or outside contractors.
- Monitor tool and part inventories and the condition and maintenance of shops to ensure adequate working conditions.
- Requisition materials and supplies, such as tools, equipment, or replacement parts.
- Determine schedules, sequences, and assignments for work activities, based on work priority, quantity of equipment, and skill of personnel.
- Examine objects, systems, or facilities and analyze information to determine needed installations, services, or repairs.
- Counsel employees about work-related issues and assist employees to correct job-skill deficiencies.
- Recommend or initiate personnel actions, such as hires, promotions, transfers, discharges, or disciplinary measures.
- Investigate accidents or injuries and prepare reports of findings.
- Conduct or arrange for worker training in safety, repair, or maintenance techniques, operational procedures, or equipment use.
- Develop, implement, or evaluate maintenance policies and procedures.
- Meet with vendors or suppliers to discuss products used in repair work.
- Inspect, test, and measure completed work, using devices such as hand tools or gauges to verify conformance to standards or repair requirements.
- 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.
- Perform skilled repair or maintenance operations, using equipment such as hand or power tools, hydraulic presses or shears, or welding equipment.
- Confer with personnel, such as management, engineering, quality control, customer, or union workers' representatives, to coordinate work activities, resolve employee grievances, or identify and review resource needs.
How we measured this — and how fresh it is
AI's theoretical reach data: 2023
From GPTs-are-GPTs (Eloundou et al.), where GPT-4 rated how much of each task an AI tool could meaningfully speed up. This is the most recent open, commercially-usable occupation-level potential dataset — it dates to 2023. Newer multi-model re-runs exist but swing wildly (one 2026 study saw "high-risk" jobs range 2.7%–51.5% by model) and aren't openly licensed, so we show the stable 2023 baseline and pair it with newer real-world data.
Real-world AI use 2026 report
From the Anthropic Economic Index, which observes how real Claude conversations map onto each occupation's tasks. Published in Anthropic's March 2026 labor-market report, based on usage measured in Aug & Nov 2025 (Sonnet 4 / 4.5).
Task list & ratings O*NET 30.3
Tasks come from O*NET 30.3. Each task's "AI can do / speeds up / still on you" tier uses the real task-level exposure scores from GPTs-are-GPTs (E1 / E2 / E0) — not a guess from keywords.
Sources: O*NET 30.3 (CC BY 4.0) · GPTs-are-GPTs (MIT, 2023) · Anthropic Economic Index (CC BY, Aug & Nov 2025). Page compiled June 2026. "O*NET" is a trademark of the U.S. Department of Labor.
This page is for general informational purposes only and is not career, financial, or employment advice. AI exposure reflects research estimates of task overlap, not predictions about any individual's job, employer, or future employment.