Air Cargo Coordinators

Transportation & Material Moving

AI exposure

  • Data source: BLSPublished: 2026-08

    Very 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

    0.017

    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

    0.44

    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, 28% 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

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
Calculate weight, volume, or cost of goods to be moved.

O*NET Task ID 17686

1.0
Prepare shipping documentation, such as bills of lading, packing lists, dock receipts, or certificates of origin.

O*NET Task ID 17687

1.0
Keep records of goods dispatched or received.

O*NET Task ID 17690

1.0
Prepare invoices or cost quotations for freight transportation.

O*NET Task ID 17696

1.0
Complete customs paperwork.

O*NET Task ID 17701

1.0
Select shipment routes, based on nature of goods shipped, transit times, or security needs.

O*NET Task ID 17680

0.5
Determine efficient and cost-effective methods of moving goods from one location to another.

O*NET Task ID 17681

0.5
Reserve necessary space on ships, aircraft, trains, or trucks.

O*NET Task ID 17682

0.5
Arrange delivery or storage of goods at destinations.

O*NET Task ID 17683

0.5
Arrange for special transport of sensitive cargoes, such as livestock, food, or medical supplies.

O*NET Task ID 17684

0.5

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