How much of this occupation’s work can be materially affected by current AI systems.
How likely exposure is to translate into reduced human demand.
Includes provisional estimates for AI adoption pressure and labour-market resilience. How this is measured
Confidence reflects task coverage, mapping and capability-evidence quality, and how much of the score rests on provisional inputs.
What is driving the score?
Occupation scores are built from the task mix—not a single prediction about a job title.
Where AI can do more
Routine, digitized, and highly repeatable tasks face the greatest pressure.
- File, grind, shim, and adjust different parts to properly fit them together.72
- Verify dimensions, alignments, and clearances of finished parts for conformance to specifications, using measuring instruments such as calipers, gauge blocks, micrometers, or dial indicators.71
- Visualize and compute dimensions, sizes, shapes, and tolerances of assemblies, based on specifications.71
- Select metals to be used from a range of metals and alloys, based on properties such as hardness or heat tolerance.71
Where people still matter
These tasks score lowest on automation feasibility—physical presence, judgement, accountability and real-world variability all resist end-to-end automation.
- Fit and assemble parts to make, repair, or modify dies, jigs, gauges, and tools, using machine tools, hand tools, or welders.01
- Cut, shape, and trim blanks or blocks to specified lengths or shapes, using power saws, power shears, rules, and hand tools.02
- Set up and operate conventional or computer numerically controlled machine tools such as lathes, milling machines, or grinders to cut, bore, grind, or otherwise shape parts to prescribed dimensions and finishes.03
- Inspect finished dies for smoothness, contour conformity, and defects.04
- Verify dimensions, alignments, and clearances of finished parts for conformance to specifications, using measuring instruments such as calipers, gauge blocks, micrometers, or dial indicators.05
Related occupations
Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.
Tool Grinders, Filers, and Sharpeners
Closely related work
Compare these careers →Model Makers, Metal and Plastic
Closely related work
Compare these careers →Grinding and Polishing Workers, Hand
Closely related work
Compare these careers →Milling and Planing Machine Setters, Operators, and Tenders, Metal and Plastic
Closely related work
Compare these careers →Multiple Machine Tool Setters, Operators, and Tenders, Metal and Plastic
Related work
Compare these careers →Woodworking Machine Setters, Operators, and Tenders, Except Sawing
Related work
Compare these careers →Adoption and labour-market outlook
Structural factors are kept separate from raw capability so you can see what actually resists automation. Adoption pressure and labour-market resilience are still provisional models—25% of this occupation’s replacement-risk weight rests on them.
O*NET 30.3 occupational data interpreted through the JobsVsAI capability, automation and structural-constraint models.
