Científicos de Datos
Informática y MatemáticasExposición 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
0.461
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
0.57
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 7% 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 26 tareas ocultas| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Create graphs, charts, or other visualizations to convey the results of data analysis using specialized software.15-2051 | 0.360026.7 | 0.06003.7 |
Generate standard or custom reports summarizing business, financial, or economic data for review by executives, managers, clients, and other stakeholders.15-2051 | 0.180013.3 | 0.330020.1 |
Maintain or update business intelligence tools, databases, dashboards, systems, or methods.15-2051 | 0.150011.1 | 0.230014.0 |
Write new functions or applications in programming languages to conduct analyses.15-2051 | 0.12008.9 | 0.10006.1 |
Prepare data analysis listings and activity, performance, or progress reports.15-2051 | 0.07005.2 | 0.14008.5 |
Synthesize current business intelligence or trend data to support recommendations for action.15-2051 | 0.06004.4 | 0.15009.1 |
Prepare appropriate formatting to data sets as requested.15-2051 | 0.06004.4 | 0.15009.1 |
Provide technical support for existing reports, dashboards, or other tools.15-2051 | 0.05003.7 | 0.02001.2 |
Evaluate processes and technologies, and suggest revisions to increase productivity and efficiency.15-2051 | 0.04003.0 | 0.01000.6 |
Propose solutions in engineering, the sciences, and other fields using mathematical theories and techniques.15-2051 | 0.04003.0 | 0.00000.0 |
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 |
|---|---|
Apply feature selection algorithms to models predicting outcomes of interest, such as sales, attrition, and healthcare use.O*NET Task ID 21824 | 1.0 |
Apply sampling techniques to determine groups to be surveyed or use complete enumeration methods.O*NET Task ID 21825 | 1.0 |
Clean and manipulate raw data using statistical software.O*NET Task ID 21826 | 1.0 |
Compare models using statistical performance metrics, such as loss functions or proportion of explained variance.O*NET Task ID 21827 | 1.0 |
Design surveys, opinion polls, or other instruments to collect data.O*NET Task ID 21830 | 1.0 |
Propose solutions in engineering, the sciences, and other fields using mathematical theories and techniques.O*NET Task ID 21834 | 1.0 |
Test, validate, and reformulate models to ensure accurate prediction of outcomes of interest.O*NET Task ID 21837 | 1.0 |
Write new functions or applications in programming languages to conduct analyses.O*NET Task ID 21838 | 1.0 |
Analyze, manipulate, or process large sets of data using statistical software.O*NET Task ID 21823 | 0.5 |
Create graphs, charts, or other visualizations to convey the results of data analysis using specialized software.O*NET Task ID 21828 | 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: Bank of Korea research shows junior knowledge workers (≤5 years experience) face 4.0% work hour reduction from AI vs 2.9% for 21+ year veterans. Youth jobs in AI-exposed sectors declined 98.6% of 2.11M total losses (2022-2025).
[Fuente: Bank of Korea Employment Research (2025)]mar 2026: BLS projects 36% growth in data scientist roles through 2034, highest among tech occupations
[Fuente: U.S. Bureau of Labor Statistics]mar 2026: Dallas Fed: Data scientists classified as high AI-exposure occupation. Wage premiums rising as AI amplifies analytical productivity for experienced workers.
[Fuente: Dallas Fed (Feb 2026)]