Telemarketers

Sales & Marketing

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

    0.285

    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

    0.61

    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, 3% 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

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
Deliver prepared sales talks, reading from scripts that describe products or services, to persuade potential customers to purchase a product or service or to make a donation.

O*NET Task ID 4618

1.0
Obtain customer information such as name, address, and payment method, and enter orders into computers.

O*NET Task ID 4621

1.0
Record names, addresses, purchases, and reactions of prospects contacted.

O*NET Task ID 4622

1.0
Adjust sales scripts to better target the needs and interests of specific individuals.

O*NET Task ID 4623

1.0
Answer telephone calls from potential customers who have been solicited through advertisements.

O*NET Task ID 4625

1.0
Telephone or write letters to respond to correspondence from customers or to follow up initial sales contacts.

O*NET Task ID 4626

1.0
Maintain records of contacts, accounts, and orders.

O*NET Task ID 4627

1.0
Contact businesses or private individuals by telephone to solicit sales for goods or services, or to request donations for charitable causes.

O*NET Task ID 4619

0.5
Explain products or services and prices, and answer questions from customers.

O*NET Task ID 4620

0.5
Obtain names and telephone numbers of potential customers from sources such as telephone directories, magazine reply cards, and lists purchased from other organizations.

O*NET Task ID 4624

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