AI exposure: Milling and Planing Machine Setters, Operators, and Tenders, Metal and Plastic
Set up, operate, or tend milling or planing machines to mill, plane, shape, groove, or profile metal or plastic work pieces.
Reading this score
computedAt 22.7% of weighted task load, Milling and Planing Machine Setters, Operators, and Tenders, Metal and Plastic sits at the 42th percentile, below the point where a job's centre of gravity has moved. 66.3% 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 15 tasks it averages 2.23 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 Record production output, at 73.3%. The least is Mount attachments and tools, at 0.0%. A gap of 73.3% 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 production occupations, this one is more exposed than most. The median across the 107 roles in the group is 16.1%, and only 15 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 15 tasks, 7 are currently banded exposed, 0 assisted and 8 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 | 1.36 | 0-4 |
| Embodiment | 2.23 | 0-3 |
| Presence | 0.29 | 0-3 |
| Accountability | 0.36 | 0-3 |
| Context | 0.87 | 0-3 |
| Verification cost | 0.84 | 0-3 |
Task by task
15 tasks, O*NET 31.0| Task | Exposed | Assisted | Untouched | Importance | Band |
|---|---|---|---|---|---|
| Record production output. | 73.3% | 26.7% | 0.0% | 3.90 | exposed |
| Compute dimensions, tolerances, and angles of workpieces or machines according to specifications and knowledge of metal properties and shop mathematics. | 55.0% | 20.0% | 25.0% | 4.15 | exposed |
| Study blueprints, layouts, sketches, or work orders to assess workpiece specifications and to determine tooling instructions, tools and materials needed, and sequences of operations. | 41.7% | 20.8% | 37.5% | 4.20 | exposed |
| Move controls to set cutting specifications, to position cutting tools and workpieces in relation to each other, and to start machines. | 33.3% | 16.7% | 50.0% | 4.35 | exposed |
| Turn valves or pull levers to start and regulate the flow of coolant or lubricant to work areas. | 33.3% | 16.7% | 50.0% | 3.72 | exposed |
| Observe milling or planing machine operation, and adjust controls to ensure conformance with specified tolerances. | 30.0% | 20.0% | 50.0% | 4.33 | exposed |
| Select cutting speeds, feed rates, and depths of cuts, applying knowledge of metal properties and shop mathematics. | 28.3% | 21.7% | 50.0% | 4.05 | exposed |
| Select and install cutting tools and other accessories according to specifications, using hand tools or power tools. | 25.0% | 12.5% | 62.5% | 4.32 | untouched |
| Make templates or cutting tools. | 16.7% | 8.3% | 75.0% | 3.86 | untouched |
| Replace worn tools, using hand tools, and sharpen dull tools, using bench grinders. | 5.4% | 3.0% | 91.7% | 4.20 | untouched |
| Remove workpieces from machines, and check to ensure that they conform to specifications, using measuring instruments such as microscopes, gauges, calipers, and micrometers. | 0.0% | 0.0% | 100.0% | 4.45 | untouched |
| Verify alignment of workpieces on machines, using measuring instruments such as rules, gauges, or calipers. | 0.0% | 0.0% | 100.0% | 4.37 | untouched |
| Position and secure workpieces on machines, using holding devices, measuring instruments, hand tools, and hoists. | 0.0% | 0.0% | 100.0% | 4.29 | untouched |
| Move cutters or material manually or by turning handwheels, or engage automatic feeding mechanisms to mill workpieces to specifications. | 0.0% | 0.0% | 100.0% | 4.08 | untouched |
| Mount attachments and tools, such as pantographs, engravers, or routers, to perform other operations, such as drilling or boring. | 0.0% | 0.0% | 100.0% | 4.08 | untouched |
Task text and importance ratings sourced from O*NET 31.0. Shares computed. The occupation score is the importance-weighted mean.
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.