Analistas de Mercado
Vendas e MarketingExposição à IA
- Fonte dos dados: BLSPublicado: 2026-08
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: 2026-03
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: 2025
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
Ver 33 tarefas 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
Informação ocupacional
Alterações recentes relacionadas com esta ocupação
mar. de 2026: Gupta & Kumar (arXiv, Mar 2026) give Market Research Analysts an Agentic Task Exposure (ATE) score of 0.43 by 2027 in the San Francisco Bay Area (Tier 1), rising to 0.47 by 2030. That crosses the moderate-risk threshold (0.35) in 2027, when Tier 2 metros (Seattle, Austin, Boston) have no crossings yet.
[Fonte: arXiv 2604.00186 (Gupta & Kumar, 2026)]These summaries were written by AI Changing Work from the source linked with each one, and any figures in them are given as AI Changing Work summarised them; they can differ from the source's own wording and from figures shown elsewhere on this page, so check the source before relying on them. AI Changing Work matched this page's occupation to an O*NET occupation and chose, by its own judgment, case by case, which summaries relate to that O*NET occupation; a summary appearing here does not mean that its source names this occupation.