AI Automation Index

Will AI Replace Calibration Technologists and Technicians?

Task-level automation exposure for Calibration Technologists and Technicians: 14 O*NET tasks scored against their work activities, plus the simulator.

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Automation Exposure

45% weighted task index

14 of 14 tasks scored

Median Salary

$67,820 / year

BLS OEWS, May 2025 — this exact occupation

Employment Level

Low

16,540 people hold this job — size, not growth

Projected 2025–35

+4.8% employment change

1,500 openings a year · BLS line item

Pay by state

BLS OEWS publishes 37 state estimates for this occupation. Each is its own survey estimate, not the national median adjusted for local prices.

$38,460 – $93,880

Highest medians

Washington $93,880

Oklahoma $80,920

Louisiana $80,670

California $79,010

Vermont $77,950

Lowest medians

Puerto Rico $38,460

Kentucky $55,650

Illinois $59,590

Florida $59,770

Minnesota $60,360

State figures come from the 17-3028 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 45%

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

Physical work 23%

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

Judgment & influence 24%

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

Routine administration 8%

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 18/100 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

14 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) 49%

7 tasks

Medium exposure (≥ 35%) 4%

1 tasks

Low exposure (below 35%) 47%

6 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

#22095 · Core · 13% automatable

Maintain or repair measurement devices or equipment used for calibration testing.

physical manipulation — Physical calibration and upkeep of test equipment

Repair precision devices or workpieces. Maintain test equipment.

#22100 · Core · 25% automatable

Verify part dimensions or clearances using precision measuring instruments to ensure conformance to specifications.

visual inspection — Flaw location on physical products needs presence

Inspect finished products to locate flaws.

#22091 · Core · 30% automatable

Conduct calibration tests to determine performance or reliability of mechanical, structural, or electromechanical equipment.

data analysis — AI interprets results; human runs physical tests

Test performance of electrical, electronic, mechanical, or integrated systems or equipment.

#22099 · Core · 70% automatable

Read blueprints, schematics, diagrams, or technical orders.

visual inspection — Specs reading aided, human validates requirements

Review blueprints or specifications to determine work requirements.

#22101 · Core · 20% automatable

Visually inspect equipment to detect surface defects.

visual inspection — Physical condition/function check needs hands-on access

Inspect condition or functioning of facilities or equipment.

#22090 · Core · 18% automatable

Calibrate devices by comparing measurements of pressure, temperature, humidity, or other environmental conditions to known standards.

physical manipulation — Physical calibration of instruments requires hands

Calibrate scientific or technical equipment.

#22102 · Core · 72% automatable

Write and submit reports about the results of calibration tests.

text generation — Reports/evaluations drafted; human owns judgment

Write reports or evaluations.

#22093 · Core · 7% automatable

Disassemble and reassemble equipment for inspection.

physical manipulation — Physical disassembly for inspection is manual work

Reassemble equipment after repair. Disassemble equipment to inspect for deficiencies.

#22088 · Core · 64% automatable

Analyze test data to identify defects or determine calibration requirements.

data analysis — Derives specs from project data; human validates requirements

Evaluate characteristics of products. Analyze project data to determine specifications or requirements.

#22098 · Core · 72% automatable

Plan sequences of calibration tests according to equipment specifications and scientific principles.

text generation — Detailed work plans drafted from specifications

Prepare detailed work plans.

#22097 · Core · 75% automatable

Order replacement parts for malfunctioning equipment.

decision support — Ordering via systems automatable; human approves spend

Order materials, supplies, or equipment.

#22092 · Core · 60% automatable

Develop new calibration methods or techniques based on measurement science, analyses, or calibration requirements.

text generation — AI drafts technical methods; expert validates feasibility

Develop technical methods or processes.

#22089 · Core · 80% automatable

Attend conferences, workshops, or other training sessions to learn about new tools or methods.

information retrieval — AI tracks technical updates; human validates depth

Update technical knowledge.

#22094 · Supplemental · 45% automatable

Draw plans for developing jigs, fixtures, instruments, or other devices.

visual inspection — AI aids illustrations; precise technical drawing human

Draw detailed or technical illustrations.

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Community Sentiment

Do you agree?

Do you agree with the AI automation risk score calculated for this occupation?

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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