Mensajeros y Repartidores
Oficina y Apoyo AdministrativoExposición a la IA
- Fuente de datos: BLSPublicado: 2026-08
Moderado· 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: 2026-03
0.041
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: 2025
0.41
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 36% 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
Solo tareas expuestas| Task | Claude.aiRaw / share % |
|---|---|
Plan and follow the most efficient routes for delivering goods.43-5021 | 0.0284100.0 |
| Not observed on any surface — 15 task(s) — These tasks have no row in the source for this release. The 0 in the share row is a display-stage composition ratio; absence is what the — in the raw row states. | |
Walk, ride bicycles, drive vehicles, or use public conveyances to reach destinations to deliver messages or materials. | —0 |
Load vehicles with listed goods, ensuring goods are loaded correctly and taking precautions with hazardous goods. | —0 |
Unload and sort items collected along delivery routes. | —0 |
Receive messages or materials to be delivered, and information on recipients, such as names, addresses, telephone numbers, and delivery instructions, communicated via telephone, two-way radio, or in person. | —0 |
Deliver messages and items, such as newspapers, documents, and packages, between establishment departments, and to other establishments and private homes. | —0 |
Sort items to be delivered according to the delivery route. | —0 |
Obtain signatures and payments, or arrange for recipients to make payments. | —0 |
Record information, such as items received and delivered and recipients' responses to messages. | —0 |
Check with home offices after completed deliveries to confirm deliveries and collections and to receive instructions for other deliveries. | —0 |
Perform routine maintenance on delivery vehicles, such as monitoring fluid levels and replenishing fuel. | —0 |
Call by telephone to deliver verbal messages. | —0 |
Open, sort, and distribute incoming mail. | —0 |
Perform general office or clerical work such as filing materials, operating duplicating machines, or running errands. | —0 |
Collect, seal, and stamp outgoing mail, using postage meters and envelope sealers. | —0 |
Unload goods from large trucks, and load them onto smaller delivery vehicles. | —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 |
|---|---|
Receive messages or materials to be delivered, and information on recipients, such as names, addresses, telephone numbers, and delivery instructions, communicated via telephone, two-way radio, or in person.O*NET Task ID 7013 | 1.0 |
Record information, such as items received and delivered and recipients' responses to messages.O*NET Task ID 7018 | 1.0 |
Check with home offices after completed deliveries to confirm deliveries and collections and to receive instructions for other deliveries.O*NET Task ID 7019 | 1.0 |
Use telephone to deliver verbal messages.O*NET Task ID 7021 | 1.0 |
Plan and follow the most efficient routes for delivering goods.O*NET Task ID 7014 | 0.5 |
Sort items to be delivered according to the delivery route.O*NET Task ID 7016 | 0.5 |
Walk, ride bicycles, drive vehicles, or use public conveyances to reach destinations to deliver messages or materials.O*NET Task ID 7010 | 0.0 |
Load vehicles with listed goods, ensuring goods are loaded correctly and taking precautions with hazardous goods.O*NET Task ID 7011 | 0.0 |
Unload and sort items collected along delivery routes.O*NET Task ID 7012 | 0.0 |
Deliver messages and items, such as newspapers, documents, and packages, between establishment departments and to other establishments and private homes.O*NET Task ID 7015 | 0.0 |
Obtain signatures and payments, or arrange for recipients to make payments.O*NET Task ID 7017 | 0.0 |
Perform routine maintenance on delivery vehicles, such as monitoring fluid levels and replenishing fuel.O*NET Task ID 7020 | 0.0 |
Open, sort, and distribute incoming mail.O*NET Task ID 7022 | 0.0 |
Perform general office or clerical work, such as filing materials, operating duplicating machines, or running errands.O*NET Task ID 7023 | 0.0 |
Collect, seal, and stamp outgoing mail, using postage meters and envelope sealers.O*NET Task ID 7024 | 0.0 |
Unload goods from large trucks, and load them onto smaller delivery vehicles.O*NET Task ID 7025 | 0.0 |
Deliver and pick up medical records, lab specimens, and medications to and from hospitals and other medical facilities.O*NET Task ID 20903 | 0.0 |
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