Heavy and Tractor-Trailer Truck Drivers
Transportation & Material MovingAI exposure
- Data source: BLSPublished: '26.08
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: '26.03
0.000
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: '25
0.24
0.09Range of values carried here0.70Group-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, 79% score at or above this value.
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
Show 28 hidden tasks| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
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.53-3032 | 0.006255.4 | 0.002660.5 |
Read and interpret maps to determine vehicle routes.53-3032 | 0.005044.6 | —0 |
Read bills of lading to determine assignment details. | —0 | 0.001739.5 |
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.
| Task | βE1 + 0.5 × E2 |
|---|---|
Maintain logs of working hours or of vehicle service or repair status, following applicable state and federal regulations.O*NET Task ID 10637 | 1.0 |
Read bills of lading to determine assignment details.O*NET Task ID 10643 | 1.0 |
Report vehicle defects, accidents, traffic violations, or damage to the vehicles.O*NET Task ID 10644 | 1.0 |
Check all load-related documentation for completeness and accuracy.O*NET Task ID 20693 | 1.0 |
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.O*NET Task ID 20695 | 1.0 |
Read and interpret maps to determine vehicle routes.O*NET Task ID 10645 | 0.5 |
Collect delivery instructions from appropriate sources, verifying instructions and routes.O*NET Task ID 10647 | 0.5 |
Check conditions of trailers after contents have been unloaded to ensure that there has been no damage.O*NET Task ID 10650 | 0.5 |
Inventory and inspect goods to be moved to determine quantities and conditions.O*NET Task ID 10655 | 0.5 |
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.O*NET Task ID 19923 | 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®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page
Occupation information
Recent Changes Affecting This Occupation
Apr 2026: Transportation sector saw 32,241 Q1 2026 cuts — 703% increase YoY. Autonomous vehicle testing and AI logistics optimization driving displacement. AI was #1 March cut reason.
[Source: Challenger March 2026]Mar 2026: Challenger: transportation sector 31,702 cuts YTD (+872% YoY), largest sectoral increase in 2026.
[Source: Challenger Gray Feb 2026 Report]