AI exposure: Coin, Vending, and Amusement Machine Servicers and Repairers
Install, service, adjust, or repair coin, vending, or amusement machines including video games, juke boxes, pinball machines, or slot machines.
Reading this score
computedAt 23.2% of weighted task load, Coin, Vending, and Amusement Machine Servicers and Repairers sits at the 43th percentile, below the point where a job's centre of gravity has moved. 65.9% of what this role does is untouched, meaning current systems cannot produce that work at all, whatever the commercial incentive.
What holds the line here is embodiment. Across this occupation's 18 tasks it averages 2.11 out of 3, the highest of the five friction dimensions. In plain terms, the work has to happen in physical space. A language model cannot move matter. Until the robotics to do this work is both good enough and cheap enough to deploy widely, capability in software does not reach it.
The most exposed thing this job does is Order parts needed for machine repairs, at 80.0%. The least is Install machines, making the necessary water and electrical connections in compliance with codes, at 0.0%. A gap of 80.0% between two parts of the same job is the reason this index publishes at task level. An occupation-wide number would have hidden both.
Within installation, maintenance and repair occupations, this one is more exposed than most. The median across the 50 roles in the group is 12.8%, and only 7 of them score higher than this. Occupational families are not uniform, and the spread inside them is often wider than the gap between them.
What would move this score. Of 18 tasks, 7 are currently banded exposed, 0 assisted and 11 untouched. For that distribution to shift materially would take robotics cheap and reliable enough to deploy at scale, not a better language model. The score is re-computed every quarter against a fresh capability reference, and the change is published rather than quietly applied.
Where the score comes from
judgedEvery task is scored through the standardised work activities it maps to. These are this occupation’s averages on the six rubric dimensions. Capability is what AI can do; the other five are what stands in the way.
| Dimension | Mean | Scale |
|---|---|---|
| Capability | 1.58 | 0-4 |
| Embodiment | 2.11 | 0-3 |
| Presence | 0.53 | 0-3 |
| Accountability | 0.86 | 0-3 |
| Context | 1.25 | 0-3 |
| Verification cost | 1.14 | 0-3 |
Task by task
18 tasks, O*NET 31.0| Task | Exposed | Assisted | Untouched | Importance | Band |
|---|---|---|---|---|---|
| Order parts needed for machine repairs. | 80.0% | 20.0% | 0.0% | 3.88 | exposed |
| Maintain records of machine maintenance and repair. | 73.3% | 26.7% | 0.0% | 4.04 | exposed |
| Record transaction information on forms or logs, and notify designated personnel of discrepancies. | 73.3% | 26.7% | 0.0% | 3.76 | exposed |
| Keep records of merchandise distributed and money collected. | 73.3% | 26.7% | 0.0% | 4.47 | exposed |
| Refer to manuals and wiring diagrams to gather information needed to repair machines. | 55.0% | 20.0% | 25.0% | 3.52 | exposed |
| Collect coins and bills from machines, prepare invoices, and settle accounts with concessionaires. | 50.0% | 25.0% | 25.0% | 4.28 | exposed |
| Contact other repair personnel or make arrangements for the removal of machines in cases where major repairs are required. | 26.7% | 23.3% | 50.0% | 3.66 | exposed |
| Test machines to determine proper functioning. | 15.0% | 10.0% | 75.0% | 4.20 | untouched |
| Adjust machine pressure gauges and thermostats. | 15.0% | 10.0% | 75.0% | 4.07 | untouched |
| Inspect machines and meters to determine causes of malfunctions and fix minor problems such as jammed bills or stuck products. | 10.0% | 15.0% | 75.0% | 4.30 | untouched |
| Transport machines to installation sites. | 8.3% | 16.7% | 75.0% | 3.55 | untouched |
| Adjust and repair coin, vending, or amusement machines and meters and replace defective mechanical and electrical parts, using hand tools, soldering irons, and diagrams. | 7.1% | 5.4% | 87.5% | 3.79 | untouched |
| Fill machines with products, ingredients, money, and other supplies. | 0.0% | 0.0% | 100.0% | 4.42 | untouched |
| Replace malfunctioning parts, such as worn magnetic heads on automatic teller machine (ATM) card readers. | 0.0% | 0.0% | 100.0% | 4.08 | untouched |
| Clean and oil machine parts. | 0.0% | 0.0% | 100.0% | 3.96 | untouched |
| Make service calls to maintain and repair machines. | 0.0% | 0.0% | 100.0% | 4.10 | untouched |
| Disassemble and assemble machines, according to specifications and using hand and power tools. | 0.0% | 0.0% | 100.0% | 3.68 | untouched |
| Install machines, making the necessary water and electrical connections in compliance with codes. | 0.0% | 0.0% | 100.0% | 3.43 | untouched |
Task text and importance ratings sourced from O*NET 31.0. Shares computed. The occupation score is the importance-weighted mean. 1 task(s) lacked a usable O*NET weight and are shown but excluded from the weighting.
Occupations either side of this one
The four closest scores in the same occupational family, then the four closest anywhere in the index.
Read this carefully. Exposure is not displacement. A high score means current AI systems can produce this work, not that anyone will stop paying a person to do it. Adoption depends on economics, regulation and inertia that this index deliberately does not model. How the score is built.
What this means in practice
Most of this work is not reachable by current systems, so the immediate pressure is on the administrative edges of the role rather than its core: the scheduling, the reporting, the written records. That is where time is recovered.