市場調査アナリスト
ビジネス・金融AI露出度
- データ出典: BLS公表時点: '26.08
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: '26.03
0.648
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: '25
0.55
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12%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
非表示の作業 4 件を表示| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Collect and analyze data on customer demographics, preferences, needs, and buying habits to identify potential markets and factors affecting product demand.13-1161 | 0.094929.7 | 0.145031.7 |
Gather data on competitors and analyze their prices, sales, and method of marketing and distribution.13-1161 | 0.071122.3 | 0.062813.7 |
Seek and provide information to help companies determine their position in the marketplace.13-1161 | 0.050615.8 | 0.105723.1 |
Measure the effectiveness of marketing, advertising, and communications programs and strategies.13-1161 | 0.049915.6 | 0.080617.6 |
Prepare reports of findings, illustrating data graphically and translating complex findings into written text.13-1161 | 0.02026.3 | 0.01182.6 |
Forecast and track marketing and sales trends, analyzing collected data.13-1161 | 0.01534.8 | 0.01172.6 |
Conduct research on consumer opinions and marketing strategies, collaborating with marketing professionals, statisticians, pollsters, and other professionals.13-1161 | 0.00993.1 | 0.03467.6 |
Devise and evaluate methods and procedures for collecting data, such as surveys, opinion polls, or questionnaires, or arrange to obtain existing data.13-1161 | 0.00391.2 | 0.00541.2 |
Monitor industry statistics and follow trends in trade literature.13-1161 | 0.00371.2 | —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 |
|---|---|
Collect and analyze data on customer demographics, preferences, needs, and buying habits to identify potential markets and factors affecting product demand.O*NET Task ID 5433 | 0.5 |
Prepare reports of findings, illustrating data graphically and translating complex findings into written text.O*NET Task ID 5434 | 0.5 |
Measure and assess customer and employee satisfaction.O*NET Task ID 5435 | 0.5 |
Forecast and track marketing and sales trends, analyzing collected data.O*NET Task ID 5436 | 0.5 |
Seek and provide information to help companies determine their position in the marketplace.O*NET Task ID 5437 | 0.5 |
Measure the effectiveness of marketing, advertising, and communications programs and strategies.O*NET Task ID 5438 | 0.5 |
Conduct research on consumer opinions and marketing strategies, collaborating with marketing professionals, statisticians, pollsters, and other professionals.O*NET Task ID 5439 | 0.5 |
Attend staff conferences to provide management with information and proposals concerning the promotion, distribution, design, and pricing of company products or services.O*NET Task ID 5440 | 0.5 |
Gather data on competitors and analyze their prices, sales, and method of marketing and distribution.O*NET Task ID 5441 | 0.5 |
Monitor industry statistics and follow trends in trade literature.O*NET Task ID 5442 | 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®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page
Occupation information
この職業に関わる最近の変化
2026年4月: ATE 0.43 by 2027 in SF Bay Tier 1, in the SOC 13 Financial category (91 occupations analyzed). Crosses moderate-risk threshold ahead of Tier 2 and Tier 3 metros.
[出典: arXiv 2604.00186 (Gupta & Kumar, 2026)]2026年3月: Published evergreen blog post analyzing AI impact. 55% exposure, 38% risk, BLS +8% growth.
[出典: AI Changing Work Blog]2026年3月: New blog post: market research faces 60% exposure, 42% risk. 905K workforce.
[出典: ACW Blog]