Analistas de Investigación de Mercado
Negocios y FinanzasExposición a la IA
- Fuente de datos: BLSPublicado: '26.08
Muy 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
0.648
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
0.55
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 12% 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 33 tareas ocultas| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Develop transactional Web applications, using Web programming software and knowledge of programming languages, such as hypertext markup language (HTML) and extensible markup language (XML).13-1161 | 0.170031.5 | 0.06008.3 |
Gather data on competitors and analyze their prices, sales, and method of marketing and distribution.13-1161 | 0.090016.7 | 0.04005.6 |
Implement online customer service processes to ensure positive and consistent user experiences.13-1161 | 0.080014.8 | 0.390054.2 |
Prepare reports of findings, illustrating data graphically and translating complex findings into written text.13-1161 | 0.05009.3 | 0.02002.8 |
Conduct market research analysis to identify search query trends, real-time search and news media activity, popular social media topics, electronic commerce trends, market opportunities, or competitor performance.13-1161 | 0.02003.7 | 0.06008.3 |
Collect and analyze data on customer demographics, preferences, needs, and buying habits to identify potential markets and factors affecting product demand.13-1161 | 0.02003.7 | 0.04005.6 |
Forecast and track marketing and sales trends, analyzing collected data.13-1161 | 0.02003.7 | 0.01001.4 |
Prepare electronic commerce designs or prototypes, such as storyboards, mock-ups, or other content, using graphics design software.13-1161 | 0.02003.7 | 0.01001.4 |
Identify and develop commercial or technical specifications, such as usability, pricing, checkout, or data security, to promote transactional internet-enabled commerce functionality.13-1161 | 0.02003.7 | 0.00000.0 |
Optimize Web site exposure by analyzing search engine patterns to direct online placement of keywords or other content.13-1161 | 0.01001.9 | 0.02002.8 |
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 |
|---|---|
Collect and analyze data on customer demographics, preferences, needs, and buying habits to identify potential markets and factors affecting product demand.O*NET Task ID 5433 | 0.5 |
Prepare reports of findings, illustrating data graphically and translating complex findings into written text.O*NET Task ID 5434 | 0.5 |
Measure and assess customer and employee satisfaction.O*NET Task ID 5435 | 0.5 |
Forecast and track marketing and sales trends, analyzing collected data.O*NET Task ID 5436 | 0.5 |
Seek and provide information to help companies determine their position in the marketplace.O*NET Task ID 5437 | 0.5 |
Measure the effectiveness of marketing, advertising, and communications programs and strategies.O*NET Task ID 5438 | 0.5 |
Conduct research on consumer opinions and marketing strategies, collaborating with marketing professionals, statisticians, pollsters, and other professionals.O*NET Task ID 5439 | 0.5 |
Attend staff conferences to provide management with information and proposals concerning the promotion, distribution, design, and pricing of company products or services.O*NET Task ID 5440 | 0.5 |
Gather data on competitors and analyze their prices, sales, and method of marketing and distribution.O*NET Task ID 5441 | 0.5 |
Monitor industry statistics and follow trends in trade literature.O*NET Task ID 5442 | 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: ATE 0.43 by 2027 in SF Bay Tier 1, in the SOC 13 Financial category (91 occupations analyzed). Crosses moderate-risk threshold ahead of Tier 2 and Tier 3 metros.
[Fuente: arXiv 2604.00186 (Gupta & Kumar, 2026)]mar 2026: Published evergreen blog post analyzing AI impact. 55% exposure, 38% risk, BLS +8% growth.
[Fuente: AI Changing Work Blog]mar 2026: New blog post: market research faces 60% exposure, 42% risk. 905K workforce.
[Fuente: ACW Blog]