Will AI replace Coin, Vending, and Amusement Machine Servicers and Repairers?
Most of the work in Coin, Vending, and Amusement Machine Servicers and Repairers still leans on things AI struggles with — research rates its theoretical AI reach at only ~32%, and real-world use lower still.
O*NET-SOC 49-9091
How your 9 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 relatively low share of this job's tasks (~32%). By late 2025, real-world AI use had reached about 0% of its task activity (still rare). 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.
Don't trust a single AI-risk score here
For this job, the signals disagree sharply. AI's theoretical reach looks relatively low (~32%), but real-world use is only ~0%, and how much AI "can" do shifts wildly by model — one 2026 study found the share of "high-risk" jobs swung 2.7% to 51.5% just by changing which AI did the rating. This page shows the spread instead of pretending there's one number.
See all 9 tasks, ratedBased on real task-level AI scores — click to collapse
- Maintain records of machine maintenance and repair.
- Order parts needed for machine repairs.
- Record transaction information on forms or logs, and notify designated personnel of discrepancies.
- No tasks in this middle tier.
- Fill machines with products, ingredients, money, and other supplies.
- Inspect machines and meters to determine causes of malfunctions and fix minor problems such as jammed bills or stuck products.
- Test machines to determine proper functioning.
- Replace malfunctioning parts, such as worn magnetic heads on automatic teller machine (ATM) card readers.
- Clean and oil machine parts.
- Adjust and repair coin, vending, or amusement machines and meters and replace defective mechanical and electrical parts, using hand tools, soldering irons, and diagrams.
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.