Desarrolladores de Software

Informática y Matemáticas

Exposición a la IA

  • Fuente de datos: BLSPublicado: '26.08

    Muy alto· relativa

    BajoCuatro bandas relativasMuy alto

    Valor 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

    Conjunto de datos de origen (descarga XLSX)

  • Fuente de datos: AnthropicPublicado: '26.03

    0.288

    0.000Rango de los valores aquí recogidos0.745
    Escala, base y fuente

    Índice de exposición observada, 0–1 tal como se publica

    Mapeado sobre tareas de O*NET

    Conjunto de datos de origen

  • Fuente de datos: ILOPublicado: '25

    0.53

    0.09Rango de los valores aquí recogidos0.70

    Valor 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 14% alcanza o supera este valor.

    Conjunto de datos de origen

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

Solo tareas expuestas

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.

TaskβE1 + 0.5 × E2
Analyze information to determine, recommend, and plan installation of a new system or modification of an existing system.

O*NET Task ID 21661

1.0
Analyze user needs and software requirements to determine feasibility of design within time and cost constraints.

O*NET Task ID 21662

1.0
Confer with systems analysts, engineers, programmers and others to design systems and to obtain information on project limitations and capabilities, performance requirements and interfaces.

O*NET Task ID 21664

1.0
Coordinate installation of software system.

O*NET Task ID 21666

1.0
Design, develop and modify software systems, using scientific analysis and mathematical models to predict and measure outcomes and consequences of design.

O*NET Task ID 21667

1.0
Determine system performance standards.

O*NET Task ID 21668

1.0
Develop or direct software system testing or validation procedures, programming, or documentation.

O*NET Task ID 21669

1.0
Modify existing software to correct errors, adapt it to new hardware, or upgrade interfaces and improve performance.

O*NET Task ID 21670

1.0
Monitor functioning of equipment to ensure system operates in conformance with specifications.

O*NET Task ID 21671

1.0
Obtain and evaluate information on factors such as reporting formats required, costs, or security needs to determine hardware configuration.

O*NET Task ID 21672

1.0
Train users to use new or modified equipment.

O*NET Task ID 21679

0.0

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®, Eloundou et al. (2023): see full notices on the Credits page

Occupation information

Cambios recientes que afectan a esta ocupación

jul 2026: ADP/Stanford linked postings-payroll study of ~7,000 IT workers (2019-2025) prices tasks separately within IT jobs. Advising others on the design or use of technologies is among 8 higher-wage activities; five tasks lost compensation value in 2023-2025 vs 2019-2022, including "develop models of systems, processes, or products." Effect sizes were not published.

[Fuente: ADP Research / Stanford Digital Economy Lab, Unbundling Jobs (July 2026)]

jun 2026: Cited by ADP Research as an example of a high-AI-exposure occupation. Group-level payroll data shows employment in high-exposure occupations down 0.2% year over year overall and down 4.3% for workers aged 22-25 (33rd consecutive monthly decline). The percentages are for the high-exposure group, not for this occupation alone.

[Fuente: ADP Research, Canaries Dashboard (June 2026)]

abr 2026: Korean youth employment data shows codified knowledge work most vulnerable to AI displacement. Professional/technical services lost 98,000 workers in Jan 2026 (worst since 2013). Entry-level coding tasks at highest risk.

[Fuente: Econmingle / National Assembly Budget Office (2026)]