Industrial Machinery Mechanics

Construction, Maintenance & Repair

AI exposure

  • Data source: BLSPublished: 2026-08

    Moderate· relative

    LowFour relative bandsVery high

    Group-level value

    Scale, basis and source

    Four relative bands (Low / Moderate / High / Very high)

    831 detailed occupations in the BLS Employment Projections table. Assigned per National Employment Matrix (NEM) code, so occupations sharing a NEM code carry the same band

    Source dataset (XLSX download)

  • Data source: AnthropicPublished: 2026-03

    0.024

    0.000Range of values carried here0.745
    Scale, basis and source

    Observed exposure index, 0–1 as published

    Mapped onto O*NET tasks

    Source dataset

  • Data source: ILOPublished: 2025

    0.17

    0.09Range of values carried here0.70

    Group-level value

    Scale, basis and source

    Generative AI exposure index, 0–1 as published

    ISCO-08 unit group — every occupation sharing the code gets this value

    Computed by this site, not published by the ILO: of the 1,012 occupations this site links to the ILO dataset, 91% score at or above this value.

    Source dataset

What kind of figure this source publishes

The BLS category is a relative rank, not an absolute level, and it is not a first-hand measurement: it groups an occupation's percentile ranks across several published studies into four bands. It is not an employment or wage forecast, not a probability of adoption, and it does not separate automation from augmentation.

Task-level exposure

Exposed tasks only

Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.

TaskβE1 + 0.5 × E2
Record repairs and maintenance performed.

O*NET Task ID 11822

1.0
Record parts or materials used and order or requisition new parts or materials, as necessary.

O*NET Task ID 11824

1.0
Enter codes and instructions to program computer-controlled machinery.

O*NET Task ID 11827

1.0
Analyze test results, machine error messages, or information obtained from operators to diagnose equipment problems.

O*NET Task ID 11821

0.5
Study blueprints or manufacturers' manuals to determine correct installation or operation of machinery.

O*NET Task ID 11823

0.5
Assign schedules to work crews.

O*NET Task ID 23935

0.5
Disassemble machinery or equipment to remove parts and make repairs.

O*NET Task ID 11813

0.0
Repair or replace broken or malfunctioning components of machinery or equipment.

O*NET Task ID 11814

0.0
Repair or maintain the operating condition of industrial production or processing machinery or equipment.

O*NET Task ID 11815

0.0
Examine parts for defects, such as breakage or excessive wear.

O*NET Task ID 11816

0.0
Reassemble equipment after completion of inspections, testing, or repairs.

O*NET Task ID 11817

0.0
Observe and test the operation of machinery or equipment to diagnose malfunctions, using voltmeters or other testing devices.

O*NET Task ID 11818

0.0
Operate newly repaired machinery or equipment to verify the adequacy of repairs.

O*NET Task ID 11819

0.0
Clean, lubricate, or adjust parts, equipment, or machinery.

O*NET Task ID 11820

0.0
Cut and weld metal to repair broken metal parts, fabricate new parts, or assemble new equipment.

O*NET Task ID 11825

0.0
Demonstrate equipment functions and features to machine operators.

O*NET Task ID 11826

0.0

β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.

Data sources & licenses — O*NET®, Eloundou et al. (2023): see full notices on the Credits page

Occupation information