Appointment Schedulers

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

    0.434

    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

    0.57

    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, 7% 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 3 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
Perform administrative support tasks, such as proofreading, transcribing handwritten information, or operating calculators or computers to work with pay records, invoices, balance sheets, or other documents.

O*NET Task ID 746

1.0
Analyze data to determine answers to questions from customers or members of the public.

O*NET Task ID 752

1.0
Calculate and quote rates for tours, stocks, insurance policies, or other products or services.

O*NET Task ID 756

1.0
Process and prepare memos, correspondence, travel vouchers, or other documents.

O*NET Task ID 758

1.0
Operate telephone switchboard to answer, screen, or forward calls, providing information, taking messages, or scheduling appointments.

O*NET Task ID 744

0.5
Receive payment and record receipts for services.

O*NET Task ID 745

0.5
Greet persons entering establishment, determine nature and purpose of visit, and direct or escort them to specific destinations.

O*NET Task ID 747

0.5
Hear and resolve complaints from customers or the public.

O*NET Task ID 748

0.5
File and maintain records.

O*NET Task ID 749

0.5
Transmit information or documents to customers, using computer, mail, or facsimile machine.

O*NET Task ID 750

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

Recent Changes Related to This Occupation

Mar 2026: ILO confirms receptionists among occupations driving gender AI gap; 88% of countries analyzed show women face higher generative AI risks than men

[Source: ILO: Gen AI, Occupational Segregation and Gender Equality (Mar 2026)]

Mar 2026: ILO: business administration and clerical support nearly twice as likely to be exposed to GenAI.

[Source: ILO Research Brief, March 2026]

Jan 2026: Brookings study identifies 965,000 receptionists among workers with high AI exposure and low adaptive capacity. Vulnerability concentrated in smaller cities with shallow labor markets.

[Source: Brookings Institution — Measuring US workers capacity to adapt (2026-01)]

These summaries were written by AI Changing Work from the source linked with each one, and any figures in them are given as AI Changing Work summarised them; they can differ from the source's own wording and from figures shown elsewhere on this page, so check the source before relying on them. AI Changing Work matched this page's occupation to an O*NET occupation and chose, by its own judgment, case by case, which summaries relate to that O*NET occupation; a summary appearing here does not mean that its source names this occupation.