訪問販売員
営業・マーケティングAI露出度
- データ出典: BLS公表時点: 2026-08
非常に高い· 相対
低い4段階の相対区分非常に高い職業群単位の値
尺度・母数・出典
4段階の相対区分（低い / 中程度 / 高い / 非常に高い）
BLS雇用見通し表の詳細職業831件が母数。値は NEM(全国雇用マトリクス)コード単位で付与されるため、同じ NEM コードの職業は同じバンドになります
- データ出典: Anthropic公表時点: 2026-03
0.176
0.000ここに掲載された値の範囲0.745尺度・母数・出典
- データ出典: ILO公表時点: 2025
0.20
0.09ここに掲載された値の範囲0.70職業群単位の値
尺度・母数・出典
生成AI露出度指数、公開されたまま0–1
ISCO-08の職業小分類単位 — 同じコードの職業はすべて同じ値
当サイトの算出であり、ILOが公表した数値ではありません。当サイトがILOデータセットに結び付けた職業1,012件のうち、この値以上のものは86%です。
この出典がどのような性格の値か
BLSの区分は絶対水準ではなく相対順位であり、一次測定でもありません。複数の既存研究が付けた職業別パーセンタイル順位を4段階にまとめた値です。雇用や賃金の予測でもなく、導入確率でもなく、自動化と増強を区別しません。
Task-level exposure
露出のある作業のみ| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Answer questions about product features and benefits.41-9091 | 0.122458.5 | 0.041747.5 |
Explain products or services and prices and demonstrate use of products.41-9091 | 0.071534.2 | 0.009711.1 |
Develop prospect lists.41-9091 | 0.01014.8 | —0 |
Contact customers to persuade them to purchase merchandise or services.41-9091 | 0.00291.4 | 0.013815.7 |
Write and record orders for merchandise or enter orders into computers.41-9091 | 0.00241.1 | 0.022525.7 |
| Not observed on any surface — 7 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 | —0 |
Arrange buying parties and solicit sponsorship of such parties to sell merchandise. | —0 | —0 |
Circulate among potential customers or travel by foot, truck, automobile, or bicycle to deliver or sell merchandise or services. | —0 | —0 |
Distribute product samples or literature that details products or services. | —0 | —0 |
Order or purchase supplies. | —0 | —0 |
Set up and display sample merchandise at parties or stands. | —0 | —0 |
Stock carts or stands. | —0 | —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