医療秘書および事務アシスタント
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
0.362
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
0.53
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14%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 12 件を表示| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Compile and record medical charts, reports, or correspondence, using typewriter or personal computer.43-6013 | 0.00000.0 | 0.020050.0 |
Transcribe recorded messages or practitioners' diagnoses or recommendations into patients' medical records.43-6013 | 0.00000.0 | 0.010025.0 |
Answer telephones and direct calls to appropriate staff. | —0 | 0.010025.0 |
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 |
|---|---|
Compile and record medical charts, reports, or correspondence, using typewriter or personal computer.O*NET Task ID 776 | 1.0 |
Operate office equipment, such as voice mail messaging systems, and use word processing, spreadsheet, or other software applications to prepare reports, invoices, financial statements, letters, case histories, or medical records.O*NET Task ID 782 | 1.0 |
Transmit correspondence or medical records by mail, e-mail, or fax.O*NET Task ID 783 | 1.0 |
Transcribe recorded messages or practitioners' diagnoses or recommendations into patients' medical records.O*NET Task ID 786 | 1.0 |
Complete insurance or other claim forms.O*NET Task ID 788 | 1.0 |
Prepare correspondence or assist physicians or medical scientists with preparation of reports, speeches, articles, or conference proceedings.O*NET Task ID 789 | 1.0 |
Schedule and confirm patient diagnostic appointments, surgeries, or medical consultations.O*NET Task ID 775 | 0.5 |
Answer telephones and direct calls to appropriate staff.O*NET Task ID 777 | 0.5 |
Receive and route messages or documents, such as laboratory results, to appropriate staff.O*NET Task ID 778 | 0.5 |
Greet visitors, ascertain purpose of visit, and direct them to appropriate staff.O*NET Task ID 779 | 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
職業情報
この職業に関わる最近の変化
2026年1月: Brookings study identifies 831,000 medical secretaries among workers with high AI exposure and low adaptive capacity. Skills in this role have low transferability to growing occupations.
[出典: Brookings Institution — Measuring US workers capacity to adapt (2026-01)]These summaries were written by AI Changing Work from the source linked with each one, and any figures in them are given as AI Changing Work summarised them; they can differ from the source's own wording and from figures shown elsewhere on this page, so check the source before relying on them. AI Changing Work matched this page's occupation to an O*NET occupation and chose, by its own judgment, case by case, which summaries relate to that O*NET occupation; a summary appearing here does not mean that its source names this occupation.