Heavy and Tractor-Trailer Truck Drivers
Transportation and Material Moving Occupations- O*NET-SOC code
- 53-3032.00
Drive a tractor-trailer combination or a truck with a capacity of at least 26,001 pounds Gross Vehicle Weight (GVW). May be required to unload truck. Requires commercial drivers' license. Includes tow truck drivers.
AI exposure
- Data source: BLSPublished: 2026-08
Moderate· relative
LowFour relative bandsVery highGroup-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
- Data source: AnthropicPublished: 2026-03
0.000
0.000Range of values carried here0.745Scale, basis and source
Observed exposure index, 0–1 as published
Mapped onto O*NET tasks
Published per SOC 2018 occupation; every O*NET occupation with the same SOC 2018 code carries this value
- Data source: ILOPublished: 2025
0.24
0.09Range of values carried here0.70Group-level value
Scale, basis and source
Generative AI exposure index, 0–1 as published
Published per ISCO-08 unit group. Linked to this occupation, wholly or in part, by applying U.S. Bureau of Labor Statistics crosswalks (ISCO-08 to 2010 SOC, 2010 SOC to 2018 SOC) as published
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.
AI exposure (OpenAI rubric)
31 rated tasks · 10 tasks with β ≥ 0.5 (32.3%)
β = direct exposure (E1) + 0.5 × exposure when tools are available (E2), per the source repository's definition.
- Source unit: O*NET 27.2 tasks → O*NET 31.0 occupation code
- 2 rated tasks are not in the O*NET 31.0 task list; their scores are kept as published for O*NET 27.2.
- Source
- OpenAI "GPTs are GPTs" exposure rubric
- Release
- gh-main-0471612
- License
- MIT License, Copyright (c) 2024 OpenAI
Tasks
Task statements from the O*NET® 31.0 Database, core tasks first.
| Task | Type | β (OpenAI) |
|---|---|---|
| Check vehicles to ensure that mechanical, safety, and emergency equipment is in good working order. | Core | 0 |
| Maintain logs of working hours or of vehicle service or repair status, following applicable state and federal regulations. | Core | 1 |
| Obtain receipts or signatures for delivered goods and collect payment for services when required. | Core | 0 |
| Maneuver trucks into loading or unloading positions, following signals from loading crew and checking that vehicle and loading equipment are properly positioned. | Core | 0 |
| Drive trucks with capacities greater than 13 tons, including tractor-trailer combinations, to transport and deliver products, livestock, or other materials. | Core | 0 |
| Read bills of lading to determine assignment details. | Core | 1 |
| Report vehicle defects, accidents, traffic violations, or damage to the vehicles. | Core | 1 |
| Read and interpret maps to determine vehicle routes. | Core | 0.5 |
| Couple or uncouple trailers by changing trailer jack positions, connecting or disconnecting air or electrical lines, or manipulating fifth-wheel locks. | Core | 0 |
| Collect delivery instructions from appropriate sources, verifying instructions and routes. | Core | 0.5 |
| Check conditions of trailers after contents have been unloaded to ensure that there has been no damage. | Core | 0.5 |
| Crank trailer landing gear up or down to safely secure vehicles. | Core | 0 |
| Perform basic vehicle maintenance tasks, such as adding oil, fuel, or radiator fluid, performing minor repairs, or washing trucks. | Core | 0 |
| Remove debris from loaded trailers. | Core | 0 |
| Perform emergency roadside repairs, such as changing tires or installing light bulbs, tire chains, or spark plugs. | Core | 0 |
| Plan or adjust routes based on changing conditions, using computer equipment, global positioning systems (GPS) equipment, or other navigation devices, to minimize fuel consumption and carbon emissions. | Core | 0.5 |
| Inspect loads to ensure that cargo is secure. | Core | 0 |
| Check all load-related documentation for completeness and accuracy. | Core | 1 |
| Drive trucks to weigh stations before and after loading and along routes in compliance with state regulations. | Core | 0 |
| Operate equipment, such as truck cab computers, CB radios, phones, or global positioning systems (GPS) equipment to exchange necessary information with bases, supervisors, or other drivers. | Core | 1 |
| Load or unload trucks or help others with loading or unloading, using special loading-related equipment or other equipment as necessary. | Core | 0 |
| Follow appropriate safety procedures for transporting dangerous goods. | Supplemental | 0 |
| Secure cargo for transport, using ropes, blocks, chain, binders, or covers. | Supplemental | 0 |
| Inventory and inspect goods to be moved to determine quantities and conditions. | Supplemental | 0.5 |
| Follow special cargo-related procedures, such as checking refrigeration systems for frozen foods or providing food or water for livestock. | Supplemental | 0 |
| Give directions to laborers who are packing goods and moving them onto trailers. | Supplemental | 0 |
| Install or remove special equipment, such as tire chains, grader blades, plow blades, or sanders. | Supplemental | 0 |
| Operate idle reduction systems or auxiliary power systems to generate power from alternative sources, such as fuel cells, to reduce idling time, to heat or cool truck cabins, or to provide power for other equipment. | Supplemental | 0 |
| Wrap and secure goods using pads, packing paper, containers, or straps. | Supplemental | 0 |
Occupation information
Sources and attribution
This page includes information from the O*NET® 31.0 Database (https://www.onetcenter.org/database.html) by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA). Used under the CC BY 4.0 license (https://creativecommons.org/licenses/by/4.0/). O*NET® is a trademark of USDOL/ETA. AI Changing Work has modified all or some of this information: the O*NET-SOC code, title and task statements are reproduced in English without change; task-type labels are shown in the page's language and tasks are listed core first; any Korean occupation title shown on the Korean-language page is AI Changing Work's translation; any KSCO-8 unit groups linked to this occupation were paired with it by AI Changing Work's judgment, and the relation labels and statuses are AI Changing Work's additions. USDOL/ETA has not approved, endorsed, or tested these modifications.
Any AI exposure figures on this page are published by third parties, not by AI Changing Work, and none is part of the O*NET information. OpenAI publishes task-level scores (MIT License) for O*NET 27.2 task statements; each is shown next to the O*NET 31.0 task statement with the same task ID, whose wording can differ from the 27.2 statement that was scored. OpenAI also publishes occupation-level scores for O*NET-SOC codes in the same release, and any such score is shown on the O*NET occupation with the same code. Anthropic publishes an observed exposure index in the Anthropic Economic Index (CC-BY), and the U.S. Bureau of Labor Statistics publishes relative AI exposure categories (public domain); both are published per SOC code, and each value is shown on every O*NET occupation with that code. The International Labour Organization publishes a generative AI exposure index in ILO Working Paper 140 (CC BY 4.0) for ISCO-08 unit groups; AI Changing Work links those groups to O*NET occupations by applying the U.S. Bureau of Labor Statistics ISCO-08 to 2010 SOC and 2010 SOC to 2018 SOC crosswalks as published, without case-by-case selection, and these crosswalks match many groups only in part. Where several unit groups are linked, each group's published value is listed, and any summary shows only the lowest and highest of those values with the number of groups; no exposure figure is averaged or recalculated. Any employment figures are published by the U.S. Bureau of Labor Statistics for the SOC group containing this occupation. Each source is credited where its figures are shown.
O*NET OnLine: 53-3032.00 Heavy and Tractor-Trailer Truck Drivers
KSCO 코드·명칭: 한국표준직업분류(제8차 개정) — 통계청 고시 제2024-328호 (2024-07-01 고시, 2025-01-01 시행). 저작권법 제7조 제2호의 고시 항목이다. 명칭 표기(가운뎃점·띄어쓰기)는 해설서 2차 정오 반영판의 표기를 따랐으며, 고시 항목표와는 18개 명칭에서 가운뎃점 글리프나 띄어쓰기만 다르다. 통계청은 2025년 10월 국가데이터처로 개편되었다. 이 페이지의 KSCO 연결은 통계청·국가데이터처의 공식 연계표가 아니다.