Reservation and Ticket Agents

Office & Administrative Support

AI exposure

  • Data source: BLSPublished: 2026-08

    Very high· 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

    0.247

    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

    0.56

    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, 8% 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

Show 4 hidden tasks

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
Answer inquiries regarding information, such as schedules, accommodations, procedures, or policies.

O*NET Task ID 9752

1.0
Announce arrival and departure information, using public address systems.

O*NET Task ID 9761

1.0
Plan routes, itineraries, and accommodation details, and compute fares and fees, using schedules, rate books, and computers.

O*NET Task ID 9749

0.5
Make and confirm reservations for transportation and accommodations, using telephones, faxes, mail, and computers.

O*NET Task ID 9750

0.5
Prepare customer invoices and accept payment.

O*NET Task ID 9751

0.5
Assemble and issue required documentation, such as tickets, travel insurance policies, or itineraries.

O*NET Task ID 9753

0.5
Determine whether space is available on travel dates requested by customers, assigning requested spaces when available.

O*NET Task ID 9754

0.5
Inform clients of essential travel information, such as travel times, transportation connections, or medical and visa requirements.

O*NET Task ID 9755

0.5
Maintain computerized inventories of available passenger space and provide information on space reserved or available.

O*NET Task ID 9756

0.5
Confer with customers to determine their service requirements and travel preferences.

O*NET Task ID 9757

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®, Eloundou et al. (2023): see full notices on the Credits page

Occupation information