Automotive Service Attendants
Transportation & Material MovingAI exposure
- Data source: BLSPublished: 2026-08
Low· 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
- 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
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
Exposed tasks onlyValues 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 |
|---|---|
Prepare daily reports of fuel, oil, and accessory sales.O*NET Task ID 10714 | 1.0 |
Provide customers with information about local roads or highways.O*NET Task ID 10718 | 1.0 |
Maintain customer records and follow up periodically with telephone, mail, or personal reminders of services due.O*NET Task ID 10723 | 1.0 |
Collect cash payments from customers, and make change or charge purchases to customers' credit cards, providing customers with receipts.O*NET Task ID 10712 | 0.0 |
Activate fuel pumps and fill fuel tanks of vehicles with gasoline or diesel fuel to specified levels.O*NET Task ID 10713 | 0.0 |
Clean parking areas, offices, restrooms, or equipment, and remove trash.O*NET Task ID 10715 | 0.0 |
Perform minor repairs, such as adjusting brakes, replacing spark plugs, or changing engine oil or filters.O*NET Task ID 10719 | 0.0 |
Order stock, and price and shelve incoming goods.O*NET Task ID 10720 | 0.0 |
Rotate, test, and repair or replace tires.O*NET Task ID 10721 | 0.0 |
Grease and lubricate vehicles or specified units, such as springs, universal joints, or steering knuckles, using grease guns or spray lubricants.O*NET Task ID 10724 | 0.0 |
Sell and install accessories, such as batteries, windshield wiper blades, fan belts, bulbs, or headlamps.O*NET Task ID 10725 | 0.0 |
Test and charge batteries.O*NET Task ID 10726 | 0.0 |
Operate car washes.O*NET Task ID 10727 | 0.0 |
Check tire pressure and levels of fuel, motor oil, transmission, radiator, battery, or other fluids, adding air or fluids as required.O*NET Task ID 20936 | 0.0 |
Clean windshields.O*NET Task ID 20937 | 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