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AI exposure Production

Will AI replace multiple machine tool setters?

Multiple Machine Tool Setters, Operators, and Tenders, Metal and Plastic. US occupation 51-4081.

0.0%

of the time multiple machine tool setters spend on their work goes on tasks where AI is already being used to do that work.of multiple machine tool setters' working hours go on tasks AI has already started taking off their plate.

Ranked 346 of 756 US occupations. No AI use seen in the work yet, along with 410 other occupations.No handover started yet, along with 410 other occupations.

Average US job 7.7%

Among the least exposed jobs there are.Still waiting for liberation.

What AI already does for multiple machine tool settersWhat multiple machine tool setters no longer do alone

O*NET lists 21 tasks for multiple machine tool setters. None of them shows meaningful AI use at work yet.

What it does not touch, yetWhat still needs a human

21 of the 21 tasks show no AI use at work in the data.

  • Change worn machine accessories, such as cutting tools or brushes, using hand tools.Core task
  • Compute data, such as gear dimensions or machine settings, applying knowledge of shop mathematics.Core task
  • Extract or lift jammed pieces from machines, using fingers, wire hooks, or lift bars.Core task
  • Inspect workpieces for defects, and measure workpieces to determine accuracy of machine operation, using rules, templates, or other measuring instruments.Core task
  • Instruct other workers in machine set-up and operation.Core task
  • Make minor electrical and mechanical repairs and adjustments to machines and notify supervisors when major service is required.Core task
Show the other 15
  • Move controls or mount gears, cams, or templates in machines to set feed rates and cutting speeds, depths, and angles.Core task
  • Observe machine operation to detect workpiece defects or machine malfunctions, adjusting machines as necessary.Core task
  • Perform minor machine maintenance, such as oiling or cleaning machines, dies, or workpieces, or adding coolant to machine reservoirs.Core task
  • Position, adjust, and secure stock material or workpieces against stops, on arbors, or in chucks, fixtures, or automatic feeding mechanisms, manually or using hoists.Core task
  • Read blueprints or job orders to determine product specifications and tooling instructions and to plan operational sequences.Core task
  • Record operational data, such as pressure readings, lengths of strokes, feed rates, or speeds.Core task
  • Remove burrs, sharp edges, rust, or scale from workpieces, using files, hand grinders, wire brushes, or power tools.Core task
  • Select the proper coolants and lubricants and start their flow.Core task
  • Select, install, and adjust alignment of drills, cutters, dies, guides, and holding devices, using templates, measuring instruments, and hand tools.Core task
  • Set machine stops or guides to specified lengths as indicated by scales, rules, or templates.Core task
  • Set up and operate machines, such as lathes, cutters, shears, borers, millers, grinders, presses, drills, or auxiliary machines, to make metallic and plastic workpieces.Core task
  • Start machines and turn handwheels or valves to engage feeding, cooling, and lubricating mechanisms.Core task
  • Align layout marks with dies or blades.
  • Measure and mark reference points and cutting lines on workpieces, using traced templates, compasses, and rules.
  • Write programs for computer numerical control (CNC) machines to cut metal and plastic materials.

How that compares

Among the 98 production occupations, multiple machine tool setters rank 65. The group averages 0.8%, and its most exposed job is Computer Numerically Controlled Tool Programmers at 12.1%. The average US occupation sits at 7.7%.

All 756 occupations, ranked

Level with 0.0%

  1. 346Motorboat Mechanics and Service Technicians 0.0%
  2. 346Motorboat Operators 0.0%
  3. 346Motorcycle Mechanics 0.0%

What this does and does not mean

Exposure is observed use, not a forecast. Anthropic maps work conversations with Claude onto the tasks O*NET lists for each job and asks, of the tasks AI could speed up, which are actually being used for at work. A use that does the task outright counts in full and a use that assists a person counts half. The task scores are averaged into the occupation figure by the share of time spent on each task.

A high figure means AI is already part of how this work gets done. It does not mean anyone has been replaced. Anthropic's own reading of the labour market finds no systematic rise in unemployment among exposed workers so far, and about 14% fewer 22 to 25 year olds starting exposed jobs.No measurable rise in unemployment among exposed workers so far, and about 14% fewer 22 to 25 year olds starting these jobs. Gap years for everyone. Labor market impacts, 5 March 2026.

Task list and titles from O*NET 31.0 by the US Department of Labor, Employment and Training Administration, used under the CC BY 4.0 licence. Scores from the Anthropic Economic Index (CC BY). Checked 1 November 2026. How the ranking works.