Motor Vehicle Dispatchers

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

    0.226

    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

    0.50

    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, 17% 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
Relay work orders, messages, or information to or from work crews, supervisors, or field inspectors, using telephones or two-way radios.

O*NET Task ID 2725

1.0
Receive or prepare work orders.

O*NET Task ID 2728

1.0
Record and maintain files or records of customer requests, work or services performed, charges, expenses, inventory, or other dispatch information.

O*NET Task ID 2731

1.0
Determine types or amounts of equipment, vehicles, materials, or personnel required, according to work orders or specifications.

O*NET Task ID 2732

1.0
Schedule or dispatch workers, work crews, equipment, or service vehicles to appropriate locations, according to customer requests, specifications, or needs, using radios or telephones.

O*NET Task ID 2723

0.5
Arrange for necessary repairs to restore service and schedules.

O*NET Task ID 2724

0.5
Confer with customers or supervising personnel to address questions, problems, or requests for service or equipment.

O*NET Task ID 2726

0.5
Prepare daily work and run schedules.

O*NET Task ID 2727

0.5
Oversee all communications within specifically assigned territories.

O*NET Task ID 2729

0.5
Monitor personnel or equipment locations and utilization to coordinate service and schedules.

O*NET Task ID 2730

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