Door-to-Door Fundraisers
Sales & MarketingAI exposure
- Data source: BLSPublished: 2026-08
Very high· relative
LowFour relative bandsVery highGroup-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
- Data source: AnthropicPublished: 2026-03
0.176
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: 2025
0.20
0.09Range of values carried here0.70Group-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.
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| Task | Claude.aiRaw / share % |
|---|---|
Answer questions about product features and benefits.41-9091 | 0.011861.2 |
Explain products or services and prices and demonstrate use of products.41-9091 | 0.004623.9 |
Contact customers to persuade them to purchase merchandise or services.41-9091 | 0.002914.9 |
| Not observed on any surface — 9 task(s) — These tasks have no row in the source for this release. The 0 in the share row is a display-stage composition ratio; absence is what the — in the raw row states. | |
Deliver merchandise and collect payment. | —0 |
Write and record orders for merchandise or enter orders into computers. | —0 |
Arrange buying parties and solicit sponsorship of such parties to sell merchandise. | —0 |
Circulate among potential customers or travel by foot, truck, automobile, or bicycle to deliver or sell merchandise or services. | —0 |
Develop prospect lists. | —0 |
Distribute product samples or literature that details products or services. | —0 |
Order or purchase supplies. | —0 |
Set up and display sample merchandise at parties or stands. | —0 |
Stock carts or stands. | —0 |
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.
| Task | βE1 + 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®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page