人事アシスタント
事務・管理サポート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
0.405
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
0.60
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4%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 9 件を表示| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Process and review employment applications to evaluate qualifications or eligibility of applicants.43-4161 | 0.026941.1 | 0.134985.7 |
Arrange for advertising or posting of job vacancies and notify eligible workers of position availability.43-4161 | 0.019529.8 | 0.00583.7 |
Answer questions regarding examinations, eligibility, salaries, benefits, and other pertinent information.43-4161 | 0.006710.3 | 0.00231.5 |
Inform job applicants of their acceptance or rejection of employment.43-4161 | 0.00477.1 | —0 |
Process, verify, and maintain personnel related documentation, including staffing, recruitment, training, grievances, performance evaluations, classifications, and employee leaves of absence.43-4161 | 0.00335.1 | 0.00583.7 |
Compile and prepare reports and documents pertaining to personnel activities.43-4161 | 0.00264.0 | 0.00161.0 |
Explain company personnel policies, benefits, and procedures to employees or job applicants.43-4161 | 0.00172.5 | 0.00191.2 |
Select applicants meeting specified job requirements and refer them to hiring personnel. | —0 | 0.00322.0 |
Administer and score applicant and employee aptitude, personality, and interest assessment instruments. | —0 | 0.00181.1 |
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 |
|---|---|
Record data for each employee, including such information as addresses, weekly earnings, absences, amount of sales or production, supervisory reports on performance, and dates of and reasons for terminations.O*NET Task ID 2689 | 1.0 |
Answer questions regarding examinations, eligibility, salaries, benefits, and other pertinent information.O*NET Task ID 2691 | 1.0 |
Compile and prepare reports and documents pertaining to personnel activities.O*NET Task ID 2697 | 1.0 |
Inform job applicants of their acceptance or rejection of employment.O*NET Task ID 2698 | 1.0 |
Administer and score applicant and employee aptitude, personality, and interest assessment instruments.O*NET Task ID 2704 | 1.0 |
Explain company personnel policies, benefits, and procedures to employees or job applicants.O*NET Task ID 2687 | 0.5 |
Process and review employment applications to evaluate qualifications or eligibility of applicants.O*NET Task ID 2690 | 0.5 |
Examine employee files to answer inquiries and provide information for personnel actions.O*NET Task ID 2692 | 0.5 |
Gather personnel records from other departments or employees.O*NET Task ID 2693 | 0.5 |
Search employee files to obtain information for authorized persons and organizations, such as credit bureaus and finance companies.O*NET Task ID 2694 | 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