人事専門家
ビジネス・金融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
0.403
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
0.45
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25%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 13 件を表示| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Review employment applications and job orders to match applicants with job requirements.13-1071 | 0.009217.8 | 0.044520.0 |
Perform searches for qualified job candidates, using sources such as computer databases, networking, Internet recruiting resources, media advertisements, job fairs, recruiting firms, or employee referrals.13-1071 | 0.006713.0 | 0.041418.6 |
Interpret and explain human resources policies, procedures, laws, standards, or regulations.13-1071 | 0.006612.8 | 0.00512.3 |
Select qualified job applicants or refer them to managers, making hiring recommendations when appropriate.13-1071 | 0.006412.4 | 0.024911.2 |
Contact job applicants to inform them of the status of their applications.13-1071 | 0.006111.8 | 0.01617.2 |
Evaluate recruitment or selection criteria to ensure conformance to professional, statistical, or testing standards, recommending revisions, as needed.13-1071 | 0.00387.4 | 0.00954.3 |
Maintain and update human resources documents, such as organizational charts, employee handbooks or directories, or performance evaluation forms.13-1071 | 0.00295.6 | —0 |
Analyze employment-related data and prepare required reports.13-1071 | 0.00285.4 | —0 |
Interview job applicants to obtain information on work history, training, education, or job skills.13-1071 | 0.00265.0 | 0.079535.7 |
Advise management on organizing, preparing, or implementing recruiting or retention programs.13-1071 | 0.00254.8 | —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 |
|---|---|
Conduct exit interviews and ensure that necessary employment termination paperwork is completed.O*NET Task ID 18854 | 1.0 |
Contact job applicants to inform them of the status of their applications.O*NET Task ID 18857 | 1.0 |
Inform job applicants of details such as duties and responsibilities, compensation, benefits, schedules, working conditions, or promotion opportunities.O*NET Task ID 18860 | 1.0 |
Interpret and explain human resources policies, procedures, laws, standards, or regulations.O*NET Task ID 18861 | 1.0 |
Maintain and update human resources documents, such as organizational charts, employee handbooks or directories, or performance evaluation forms.O*NET Task ID 18863 | 1.0 |
Maintain current knowledge of Equal Employment Opportunity (EEO) and affirmative action guidelines and laws, such as the Americans with Disabilities Act (ADA).O*NET Task ID 18864 | 1.0 |
Prepare or maintain employment records related to events, such as hiring, termination, leaves, transfers, or promotions, using human resources management system software.O*NET Task ID 18866 | 1.0 |
Review and evaluate applicant qualifications or eligibility for specified licensing, according to established guidelines and designated licensing codes.O*NET Task ID 18876 | 1.0 |
Analyze employment-related data and prepare required reports.O*NET Task ID 18853 | 0.5 |
Conduct reference or background checks on job applicants.O*NET Task ID 18855 | 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