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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

    0.176

    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

    0.20

    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, 86% 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
Write and record orders for merchandise or enter orders into computers.

O*NET Task ID 13232

1.0
Answer questions about product features and benefits.

O*NET Task ID 13236

1.0
Develop prospect lists.

O*NET Task ID 13238

0.5
Order or purchase supplies.

O*NET Task ID 13240

0.5
Deliver merchandise and collect payment.

O*NET Task ID 13231

0.0
Explain products or services and prices and demonstrate use of products.

O*NET Task ID 13233

0.0
Arrange buying parties and solicit sponsorship of such parties to sell merchandise.

O*NET Task ID 13235

0.0
Circulate among potential customers or travel by foot, truck, automobile, or bicycle to deliver or sell merchandise or services.

O*NET Task ID 13237

0.0
Distribute product samples or literature that details products or services.

O*NET Task ID 13239

0.0
Set up and display sample merchandise at parties or stands.

O*NET Task ID 13241

0.0
Stock carts or stands.

O*NET Task ID 13242

0.0
Persuade customers to purchase merchandise or services.

O*NET Task ID 21075

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