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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

    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

    出典データセット(XLSX ファイルのダウンロード)

  • データ出典: Anthropic公表時点: 2026-03

    0.079

    0.000ここに掲載された値の範囲0.745
    尺度・母数・出典

    観測エクスポージャー指数、公開されたまま0–1

    O*NETタスクへの対応づけが基準

    出典データセット

  • データ出典: ILO公表時点: 2025

    0.42

    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33%です。

    出典データセット

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

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
Prepare or alter presentation contents to target specific audiences.

O*NET Task ID 13200

1.0
Write articles or pamphlets about products.

O*NET Task ID 13213

1.0
Learn about competitors' products or consumers' interests or concerns to answer questions or provide more complete information.

O*NET Task ID 13201

0.5
Research or investigate products to be presented to prepare for demonstrations.

O*NET Task ID 13206

0.5
Recommend product or service improvements to employers.

O*NET Task ID 13207

0.5
Develop lists of prospective clients from sources such as newspaper items, company records, local merchants, or customers.

O*NET Task ID 13212

0.5
Demonstrate or explain products, methods, or services to persuade customers to purchase products or use services.

O*NET Task ID 13190

0.0
Provide product samples, coupons, informational brochures, or other incentives to persuade people to buy products.

O*NET Task ID 13191

0.0
Keep areas neat while working and return items to correct locations following demonstrations.

O*NET Task ID 13192

0.0
Record and report demonstration-related information, such as the number of questions asked by the audience or the number of coupons distributed.

O*NET Task ID 13193

0.0
Sell products being promoted and keep records of sales.

O*NET Task ID 13194

0.0
Set up and arrange displays or demonstration areas to attract the attention of prospective customers.

O*NET Task ID 13195

0.0
Suggest specific product purchases to meet customers' needs.

O*NET Task ID 13196

0.0
Transport, assemble, and disassemble materials used in presentations.

O*NET Task ID 13197

0.0
Identify interested and qualified customers to provide them with additional information.

O*NET Task ID 13198

0.0
Practice demonstrations to ensure that they will run smoothly.

O*NET Task ID 13199

0.0
Work as part of a team of demonstrators to accommodate large crowds.

O*NET Task ID 13202

0.0
Visit trade shows, stores, community organizations, or other venues to demonstrate products or services or to answer questions from potential customers.

O*NET Task ID 13203

0.0
Train demonstrators to present a company's products or services.

O*NET Task ID 13204

0.0
Instruct customers in alteration of products.

O*NET Task ID 13205

0.0
Provide product information, using lectures, films, charts, or slide shows.

O*NET Task ID 13208

0.0
Contact businesses or civic establishments to arrange to exhibit and sell merchandise.

O*NET Task ID 13209

0.0
Wear costumes or sign boards and walk in public to promote merchandise, services, or events.

O*NET Task ID 13210

0.0
Stock shelves with products.

O*NET Task ID 13211

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

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