Compradores Minoristas
Ventas y MarketingEstados Unidos · Proyecciones de empleo BLS 2025–35: este código SOC no figura entre las partidas publicadas.
Exposición a la IA
- Fuente de datos: ILOPublicado: 2025
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.
- Fuente de datos: OpenAIPublicado: 2023
0.400
0.000Rango de los valores aquí recogidos0.844Escala, base y fuente
β de evaluadores humanos, 0–1 tal como se publica
Mapeado sobre tareas de O*NET
Task-level exposure
Ver 12 tareas ocultas| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Monitor and analyze sales records, trends, or economic conditions to anticipate consumer buying patterns and determine what the company will sell and how much inventory is needed.13-1022 | 0.002525.8 | 0.005119.8 |
Provide clerks with information to print on price tags, such as price, mark-ups or mark-downs, manufacturer number, season code, or style number.13-1022 | 0.002020.6 | 0.002810.7 |
Buy merchandise or commodities for resale to wholesale or retail consumers.13-1022 | 0.001919.6 | 0.00156.0 |
Obtain information about customer needs or preferences by conferring with sales or purchasing personnel.13-1022 | 0.001818.6 | 0.006826.2 |
Recommend mark-up rates, markdown rates, or merchandise selling prices.13-1022 | 0.001515.5 | —0 |
Monitor competitors' sales activities by following their advertisements in newspapers or other media. | —0 | 0.004015.5 |
Determine which products should be featured in advertising, the advertising medium to be used, or when the ads should be run. | —0 | 0.003011.5 |
Analyze environmental aspects of competing merchandise when making buying decisions. | —0 | 0.002710.3 |
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 |
|---|---|
Provide clerks with information to print on price tags, such as price, mark-ups or mark-downs, manufacturer number, season code, or style number.O*NET Task ID 77 | 1.0 |
Monitor and analyze sales records, trends, or economic conditions to anticipate consumer buying patterns, company sales, and needed inventory.O*NET Task ID 66 | 0.5 |
Authorize payment of invoices or return of merchandise.O*NET Task ID 68 | 0.5 |
Consult with store or merchandise managers about budgets or goods to be purchased.O*NET Task ID 72 | 0.5 |
Determine which products should be featured in advertising, the advertising medium to be used, or when the ads should be run.O*NET Task ID 78 | 0.5 |
Monitor competitors' sales activities by following their advertisements in newspapers or other media.O*NET Task ID 79 | 0.5 |
Analyze environmental aspects of competing merchandise when making buying decisions.O*NET Task ID 19547 | 0.5 |
Compare transportation options to determine the most energy-efficient options.O*NET Task ID 19548 | 0.5 |
Develop strategies to advertise green products or merchandise to consumers.O*NET Task ID 19549 | 0.5 |
Identify opportunities to buy green commodities, such as alternative energy, water, or carbon-neutral products for resale to consumers.O*NET Task ID 19550 | 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