Fence Erectors

Construction, Maintenance & Repair

AI exposure

  • Data source: BLSPublished: 2026-08

    Low· 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

    0.000

    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

    0.09

    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, 100% 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.

TaskβE1 + 0.5 × E2
Discuss fencing needs with customers, and estimate and quote prices.

O*NET Task ID 13628

1.0
Establish the location for a fence, and gather information needed to ensure that there are no electric cables or water lines in the area.

O*NET Task ID 13623

0.0
Align posts, by lines or sighting, and verify vertical alignment of posts, using plumb bobs or spirit levels.

O*NET Task ID 13624

0.0
Measure and lay out fence lines and mark posthole positions, following instructions, drawings, or specifications.

O*NET Task ID 13625

0.0
Dig postholes, using spades, posthole diggers, or power-driven augers.

O*NET Task ID 13626

0.0
Set metal or wooden posts in upright positions in postholes.

O*NET Task ID 13627

0.0
Mix and pour concrete around bases of posts, or tamp soil into postholes to embed posts.

O*NET Task ID 13629

0.0
Make rails for fences, by sawing lumber or by cutting metal tubing to required lengths.

O*NET Task ID 13630

0.0
Nail top and bottom rails to fence posts, or insert them in slots on posts.

O*NET Task ID 13631

0.0
Stretch wire, wire mesh, or chain link fencing between posts, and attach fencing to frames.

O*NET Task ID 13632

0.0
Attach fence rail supports to posts, using hammers and pliers.

O*NET Task ID 13633

0.0
Assemble gates, and fasten gates into position, using hand tools.

O*NET Task ID 13634

0.0
Complete top fence rails of metal fences by connecting tube sections, using metal sleeves.

O*NET Task ID 13635

0.0
Insert metal tubing through rail supports.

O*NET Task ID 13636

0.0
Attach rails or tension wire along bottoms of posts to form fencing frames.

O*NET Task ID 13637

0.0
Nail pointed slats to rails to construct picket fences.

O*NET Task ID 13638

0.0
Construct and repair barriers, retaining walls, trellises, and other types of fences, walls, and gates.

O*NET Task ID 13639

0.0
Weld metal parts together, using portable gas welding equipment.

O*NET Task ID 13640

0.0
Erect alternate panel, basket weave, and louvered fences.

O*NET Task ID 13641

0.0
Blast rock formations and rocky areas with dynamite to facilitate posthole digging.

O*NET Task ID 13642

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