Traffic Engineers

Transportation & Material Moving

AI exposure

  • Data source: BLSPublished: 2026-08

    High· 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

    0.008

    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

    0.30

    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, 67% 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
Develop or assist in the development of transportation-related computer software or computer processes.

O*NET Task ID 16308

1.0
Present data, maps, or other information at construction-related public hearings or meetings.

O*NET Task ID 16303

0.5
Review development plans to determine potential traffic impact.

O*NET Task ID 16304

0.5
Prepare administrative, technical, or statistical reports on traffic-operation matters, such as accidents, safety measures, or pedestrian volume or practices.

O*NET Task ID 16305

0.5
Evaluate transportation systems or traffic control devices or lighting systems to determine need for modification or expansion.

O*NET Task ID 16306

0.5
Evaluate traffic control devices or lighting systems to determine need for modification or expansion.

O*NET Task ID 16307

0.5
Prepare project budgets, schedules, or specifications for labor or materials.

O*NET Task ID 16309

0.5
Prepare final project layout drawings that include details such as stress calculations.

O*NET Task ID 16310

0.5
Plan alteration or modification of existing transportation structures to improve safety or function.

O*NET Task ID 16311

0.5
Participate in contract bidding, negotiation, or administration.

O*NET Task ID 16312

0.5
Supervise the maintenance or repair of transportation systems or system components.

O*NET Task ID 16322

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