Analistas de Pesquisa de Mercado
Negócios e FinançasExposição à IA
- Fonte dos dados: BLSPublicado: '26.08
Muito alto· relativa
BaixoQuatro faixas relativasMuito altoValor por grupo ocupacional
Escala, base e fonte
Quatro faixas relativas (Baixo / Moderado / Alto / Muito alto)
831 ocupações detalhadas da tabela de projeções de emprego do BLS. O valor é atribuído por código da National Employment Matrix (NEM), pelo que as ocupações que partilham um código NEM recebem a mesma banda
- Fonte dos dados: AnthropicPublicado: '26.03
0.648
0.000Intervalo dos valores aqui apresentados0.745Escala, base e fonte
Índice de exposição observada, 0–1 tal como publicado
Mapeado sobre tarefas O*NET
- Fonte dos dados: ILOPublicado: '25
0.55
0.09Intervalo dos valores aqui apresentados0.70Valor por grupo ocupacional
Escala, base e fonte
Índice de exposição à IA generativa, 0–1 tal como publicado
Grupo de base CITP-08 — todas as ocupações com o mesmo código recebem este valor
Calculado por este site, não publicado pela OIT: das 1.012 ocupações que este site liga ao conjunto de dados da OIT, 12% atingem ou superam este valor.
Que tipo de valor esta fonte publica
A categoria de BLS é uma posição relativa, não um nível absoluto, e também não é uma medição de primeira mão: agrupa em quatro faixas as posições percentis da ocupação em vários estudos publicados. Não é uma previsão de emprego ou de salários, não é uma probabilidade de adoção e não distingue automação de aumento.
Task-level exposure
Apenas tarefas expostas| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Collect and analyze data on customer demographics, preferences, needs, and buying habits to identify potential markets and factors affecting product demand.13-1161 | 0.070232.0 | 0.216340.1 |
Gather data on competitors and analyze their prices, sales, and method of marketing and distribution.13-1161 | 0.038317.4 | 0.071213.2 |
Measure the effectiveness of marketing, advertising, and communications programs and strategies.13-1161 | 0.033715.4 | 0.075914.1 |
Seek and provide information to help companies determine their position in the marketplace.13-1161 | 0.031214.2 | 0.126823.5 |
Prepare reports of findings, illustrating data graphically and translating complex findings into written text.13-1161 | 0.02099.5 | 0.01041.9 |
Conduct research on consumer opinions and marketing strategies, collaborating with marketing professionals, statisticians, pollsters, and other professionals.13-1161 | 0.01074.9 | 0.02614.9 |
Forecast and track marketing and sales trends, analyzing collected data.13-1161 | 0.00813.7 | 0.00841.6 |
Devise and evaluate methods and procedures for collecting data, such as surveys, opinion polls, or questionnaires, or arrange to obtain existing data.13-1161 | 0.00411.9 | 0.00360.7 |
Monitor industry statistics and follow trends in trade literature.13-1161 | 0.00231.0 | —0 |
| Not observed on any surface — 4 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. | ||
Measure and assess customer and employee satisfaction. | —0 | —0 |
Attend staff conferences to provide management with information and proposals concerning the promotion, distribution, design, and pricing of company products or services. | —0 | —0 |
Develop and implement procedures for identifying advertising needs. | —0 | —0 |
Direct trained survey interviewers. | —0 | —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 |
|---|---|
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
Alterações recentes que afetam esta ocupação
abr. de 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.
[Fonte: arXiv 2604.00186 (Gupta & Kumar, 2026)]mar. de 2026: Published evergreen blog post analyzing AI impact. 55% exposure, 38% risk, BLS +8% growth.
[Fonte: AI Changing Work Blog]mar. de 2026: New blog post: market research faces 60% exposure, 42% risk. 905K workforce.
[Fonte: ACW Blog]