Industrial Truck and Tractor Operators

Transportation & Material Moving

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

    0.20

    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, 86% 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
Weigh materials or products and record weight or other production data on tags or labels.

O*NET Task ID 3206

0.5
Move controls to drive gasoline- or electric-powered trucks, cars, or tractors and transport materials between loading, processing, and storage areas.

O*NET Task ID 3201

0.0
Move levers or controls that operate lifting devices, such as forklifts, lift beams with swivel-hooks, hoists, or elevating platforms, to load, unload, transport, or stack material.

O*NET Task ID 3202

0.0
Position lifting devices under, over, or around loaded pallets, skids, or boxes and secure material or products for transport to designated areas.

O*NET Task ID 3203

0.0
Perform routine maintenance on vehicles or auxiliary equipment, such as cleaning, lubricating, recharging batteries, fueling, or replacing liquefied-gas tank.

O*NET Task ID 3205

0.0
Operate or tend automatic stacking, loading, packaging, or cutting machines.

O*NET Task ID 3207

0.0
Signal workers to discharge, dump, or level materials.

O*NET Task ID 3208

0.0
Hook tow trucks to trailer hitches and fasten attachments, such as graders, plows, rollers, or winch cables to tractors, using hitchpins.

O*NET Task ID 3209

0.0
Turn valves and open chutes to dump, spray, or release materials from dump cars or storage bins into hoppers.

O*NET Task ID 3210

0.0
Inspect product load for accuracy and safely move it around the warehouse or facility to ensure timely and complete delivery.

O*NET Task ID 15265

0.0
Manually or mechanically load or unload materials from pallets, skids, platforms, cars, lifting devices, or other transport vehicles.

O*NET Task ID 15266

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