AI Automation Index

Will AI Replace Computer Numerically Controlled Tool Programmers?

Task-level automation exposure for Computer Numerically Controlled Tool Programmers: 16 O*NET tasks scored against their work activities, plus the simulator.

E-E-A-T Verified

Developed & audited by Gini Loh

Automation Exposure

52% weighted task index

16 of 16 tasks scored

Median Salary

$68,120 / year

BLS OEWS, May 2025 — this exact occupation

Employment Level

Medium

28,500 people hold this job — size, not growth

Projected 2025–35

+5.9% employment change

2,700 openings a year · BLS line item

Pay by state

BLS OEWS publishes 43 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.

$50,190 – $86,390

Highest medians

Connecticut $86,390

California $82,090

Massachusetts $81,670

Washington $81,420

Missouri $78,130

Lowest medians

Mississippi $50,190

Arkansas $56,390

Nevada $57,210

Iowa $57,780

Ohio $60,080

State figures come from the 51-9162 row in the May 2025 state panel. States where the estimate was suppressed or too small to publish are absent.

What the score is made of

Each task is mapped to its work activities, scored for AI automation potential, and weighted by how important those activities are to the job. These are the components.

Automation potential 52%

Importance-weighted mean of the scored tasks. This is the headline index.

Physical work 10%

Share of weighted tasks in hands-on or machine-operating work activities.

Judgment & influence 33%

Share in analysis, decisions, teaching, directing, advising, or caring for others.

Routine administration 0%

Share in documenting, recording, and administrative activities.

Rewritten by O*NET 0%

Share of weighted tasks O*NET rewrote in a recent update. Reported, not folded into the score.

Consequence of error 13/100 Low

O*NET's own rating of how serious an uncorrectable mistake would be here — respondents, not us. Deliberately not in the index: the score measures what AI can do with the task content, and multiplying it by stakes would be our judgment dressed as data.

Constituent Task Mix

16 tasks for this occupation, weighted by work-activity importance. Shares below are of total task weight, not task count.

High exposure (≥ 60% of the task is automatable) 24%

4 tasks

Medium exposure (≥ 35%) 59%

9 tasks

Low exposure (below 35%) 17%

3 tasks

How would you survive?

Move your week away from the high-exposure tasks and toward the ones that need judgment. The simulator recalculates the index as you shift the mix.

Simulate Upskilling →

Constituent Tasks

#11959 · Core · 48% automatable

Determine the sequence of machine operations, and select the proper cutting tools needed to machine workpieces into the desired shapes.

decision support — Equipment selection against specs; human verifies fit

Determine production equipment settings. Select production equipment according to product specifications.

#11961 · Core · 66% automatable

Analyze job orders, drawings, blueprints, specifications, printed circuit board pattern films, and design data to calculate dimensions, tool selection, machine speeds, and feed rates.

visual inspection — Blueprint setup reading partial, human confirms

Study blueprints or other instructions to determine equipment setup requirements.

#11963 · Core · 30% automatable

Observe machines on trial runs or conduct computer simulations to ensure that programs and machinery will function properly and produce items that meet specifications.

physical manipulation — Operating production equipment physically on site

Conduct test runs of production equipment.

#11966 · Core · 55% automatable

Write programs in the language of a machine's controller and store programs on media, such as punch tapes, magnetic tapes, or disks.

decision support — Programming production equipment needs physical setup and verification

Program equipment to perform production tasks.

#11962 · Core · 56% automatable

Determine reference points, machine cutting paths, or hole locations, and compute angular and linear dimensions, radii, and curvatures.

data analysis — Dimension calculations from given specs

Calculate dimensions of workpieces, products, or equipment. Determine production equipment settings.

#11968 · Core · 55% automatable

Enter computer commands to store or retrieve parts patterns, graphic displays, or programs that transfer data to other media.

physical manipulation — Command entry often needs physical equipment interface

Enter commands, instructions, or specifications into equipment.

#11960 · Core · 55% automatable

Revise programs or tapes to eliminate errors, and retest programs to check that problems have been solved.

decision support — Programming production equipment needs physical setup and verification

Program equipment to perform production tasks.

#11967 · Core · 55% automatable

Modify existing programs to enhance efficiency.

decision support — Programming production equipment needs physical setup and verification

Program equipment to perform production tasks.

#11965 · Core · 55% automatable

Enter coordinates of hole locations into program memories by depressing pedals or buttons of programmers.

physical manipulation — Command entry often needs physical equipment interface

Enter commands, instructions, or specifications into equipment.

#11971 · Core · 60% automatable

Sort shop orders into groups to maximize materials utilization and minimize machine setup time.

decision support — Sequence planning aided; production constraints human-verified

Plan production or operational procedures or sequences.

#11964 · Core · 80% automatable

Compare encoded tapes or computer printouts with original part specifications and blueprints to verify accuracy of instructions.

information retrieval — Spec verification against references, human confirms edge cases

Verify information or specifications.

#11969 · Core · 50% automatable

Prepare geometric layouts from graphic displays, using computer-assisted drafting software or drafting instruments and graph paper.

visual inspection — AI drafts blueprints; manufacturability and tolerances human

Create diagrams or blueprints for workpieces or products.

#20922 · Core · 15% automatable

Perform preventative maintenance or minor repairs on machines.

physical manipulation — Basic equipment maintenance requires hands-on work

Perform basic equipment maintenance.

#24013 · Core · 68% automatable

Order tooling for jobs.

decision support — Ordering via systems automatable; human approves spend

Order materials, supplies, or equipment. Purchase products or services.

#11970 · Supplemental · 55% automatable

Write instruction sheets and cutter lists for a machine's controller to guide setup and encode numerical control tapes.

decision support — Programming production equipment needs physical setup and verification

Program equipment to perform production tasks.

#11973 · Supplemental · 14% automatable

Align and secure pattern film on reference tables of optical programmers, and observe enlarger scope views of printed circuit boards.

visual inspection — Installation inspection requires on-site physical check

Inspect completed work to ensure proper installation. Align equipment or machinery.

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Community Sentiment

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Method

How this was scored

1. Tasks. O*NET task statements for this occupation, from a release whose newest record is dated 08/2026.
2. Work activities. Each task maps to 1–5 Detailed Work Activities; each activity belongs to one of 41 Generalized Work Activities that O*NET rates for importance (1–5) in this occupation.
3. Automation potential. Every work activity carries one score for how far current AI can perform it end-to-end. Tasks inherit the mean of their activities.
4. Weighting. Task weight = 0.35 + 0.65 × (importance − 1)/4, scaled by how often the task is performed and by 0.7 for Supplemental tasks. Importance is the task's own O*NET rating where it exists (18,369 of 18,838 tasks); the rest inherit their work activities' importance. The index is the weighted mean.

Check: across the 910 occupations where O*NET also rates how far machine speed sets the pace, this index moves opposite to it (Spearman ρ = -0.49). The more a job is paced by equipment, the less of its task content AI can address — the relationship you would expect if the scoring is working.

Sources · O*NET 31.0 (task records to 08/2026) · BLS OEWS May 2025 · BLS projections 2025-2035 · rubric v2.1 · tasks for O*NET, not a forecast

See the full method →

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