Asistentes Legales
LegalExposición a la IA
- Fuente de datos: BLSPublicado: '26.08
Alto· relativa
BajoCuatro bandas relativasMuy altoValor por grupo ocupacional
Escala, base y fuente
Cuatro bandas relativas (Bajo / Moderado / Alto / Muy alto)
831 ocupaciones detalladas de la tabla de proyecciones de empleo de BLS. El valor se asigna por código de la National Employment Matrix (NEM), de modo que las ocupaciones que comparten un código NEM reciben la misma banda
- Fuente de datos: AnthropicPublicado: '26.03
0.293
0.000Rango de los valores aquí recogidos0.745Escala, base y fuente
Índice de exposición observada, 0–1 tal como se publica
Mapeado sobre tareas de O*NET
- Fuente de datos: ILOPublicado: '25
0.39
0.09Rango de los valores aquí recogidos0.70Valor por grupo ocupacional
Escala, base y fuente
Índice de exposición a la IA generativa, 0–1 tal como se publica
Grupo primario de la CIUO-08 — todas las ocupaciones con ese código reciben este valor
Calculado por este sitio, no publicado por la OIT: de las 1012 ocupaciones que este sitio vincula al conjunto de datos de la OIT, un 44% alcanza o supera este valor.
Qué tipo de cifra publica esta fuente
La categoría de BLS es un rango relativo, no un nivel absoluto, y tampoco es una medición de primera mano: agrupa en cuatro bandas los rangos percentiles de la ocupación en varios estudios publicados. No es una previsión de empleo ni de salarios, no es una probabilidad de adopción y no distingue entre automatización y aumento.
Task-level exposure
Ver 10 tareas ocultas| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Prepare, edit, or review legal documents, including legislation, briefs, pleadings, appeals, wills, contracts, and real estate closing statements.23-2011 | 0.130086.7 | 0.020050.0 |
Gather and analyze research data, such as statutes, decisions, and legal articles, codes, and documents.23-2011 | 0.020013.3 | 0.020050.0 |
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 |
|---|---|
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
Cambios recientes que afectan a esta ocupación
abr 2026: 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.
[Fuente: OpenAI Jobs Transition Framework, April 2026]mar 2026: Brookings: regulated sectors (law) show constrained AI adoption due to privacy and liability concerns.
[Fuente: Brookings Institution]mar 2026: HBR: Paralegals classified as automation-vulnerable due to high text-processing task share. Job postings declining as AI handles document review and legal research.
[Fuente: HBR (Mar 2026)]