Bus Drivers, Transit and Intercity

Transportation & Material Moving

AI exposure

  • Data source: BLSPublished: 2026-08

    Moderate· 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

    0.18

    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, 90% 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. 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
Report delays or accidents.

O*NET Task ID 3148

1.0
Record information, such as cash receipts and ticket fares, and maintain log book.

O*NET Task ID 18797

1.0
Announce stops to passengers.

O*NET Task ID 21085

1.0
Read maps to plan bus routes.

O*NET Task ID 21086

0.5
Inspect vehicles and check gas, oil, and water levels prior to departure.

O*NET Task ID 3144

0.0
Park vehicles at loading areas so that passengers can board.

O*NET Task ID 3146

0.0
Advise passengers to be seated and orderly while on vehicles.

O*NET Task ID 3149

0.0
Regulate heating, lighting, and ventilating systems for passenger comfort.

O*NET Task ID 3150

0.0
Load and unload baggage in baggage compartments.

O*NET Task ID 3151

0.0
Make minor repairs to vehicle and change tires.

O*NET Task ID 3153

0.0
Drive vehicles over specified routes or to specified destinations according to time schedules, complying with traffic regulations to ensure that passengers have a smooth and safe ride.

O*NET Task ID 18794

0.0
Assist passengers, such as elderly or disabled individuals, on and off bus, ensure they are seated properly, help carry baggage, and answer questions about bus schedules or routes.

O*NET Task ID 18795

0.0
Handle passenger emergencies or disruptions.

O*NET Task ID 18796

0.0
Collect tickets or cash fares from passengers.

O*NET Task ID 18798

0.0
Maintain cleanliness of bus or motor coach.

O*NET Task ID 18799

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