パラリーガル
法律AI露出度
- データ出典: BLS公表時点: '26.08
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
- データ出典: Anthropic公表時点: '26.03
0.293
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
0.39
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44%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 10 件を表示| Task | Claude.aiRaw / share % |
|---|---|
Prepare legal documents, including briefs, pleadings, appeals, wills, contracts, and real estate closing statements.23-2011 | 0.048894.1 |
Gather and analyze research data, such as statutes, decisions, and legal articles, codes, and documents.23-2011 | 0.00315.9 |
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 |
|---|---|
Prepare legal documents, including briefs, pleadings, appeals, wills, contracts, and real estate closing statements.O*NET Task ID 1634 | 1.0 |
Prepare affidavits or other documents, such as legal correspondence, and organize and maintain documents in paper or electronic filing system.O*NET Task ID 18491 | 1.0 |
Gather and analyze research data, such as statutes, decisions, and legal articles, codes, and documents.O*NET Task ID 1636 | 0.5 |
Direct and coordinate law office activity, including delivery of subpoenas.O*NET Task ID 1639 | 0.5 |
Keep and monitor legal volumes to ensure that law library is up-to-date.O*NET Task ID 1641 | 0.5 |
Appraise and inventory real and personal property for estate planning.O*NET Task ID 1642 | 0.5 |
Prepare for trial by performing tasks such as organizing exhibits.O*NET Task ID 18492 | 0.5 |
File pleadings with court clerk.O*NET Task ID 18494 | 0.5 |
Arbitrate disputes between parties and assist in the real estate closing process, such as by reviewing title searches.O*NET Task ID 18496 | 0.5 |
Investigate facts and law of cases and search pertinent sources, such as public records and internet sources, to determine causes of action and to prepare cases.O*NET Task ID 21062 | 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: OpenAI Jobs Transition Framework (April 2026) classifies paralegals in the 18% high-risk cluster: heavy document review, citation checking, and templated drafting are core LLM strengths.
[出典: OpenAI Jobs Transition Framework, April 2026]2026年3月: Brookings: regulated sectors (law) show constrained AI adoption due to privacy and liability concerns.
[出典: Brookings Institution]2026年3月: HBR: Paralegals classified as automation-vulnerable due to high text-processing task share. Job postings declining as AI handles document review and legal research.
[出典: HBR (Mar 2026)]