Emergency Preparedness Specialists

Protective Service

AI exposure

  • Data source: BLSPublished: 2026-08

    Very high· relative

    LowFour relative bandsVery high

    Group-level value

    Scale, basis and source

    Four relative bands (Low / Moderate / High / Very high)

    831 detailed occupations in the BLS Employment Projections table. Assigned per National Employment Matrix (NEM) code, so occupations sharing a NEM code carry the same band

    Source dataset (XLSX download)

  • Data source: AnthropicPublished: 2026-03

    0.185

    0.000Range of values carried here0.745
    Scale, basis and source

    Observed exposure index, 0–1 as published

    Mapped onto O*NET tasks

    Source dataset

  • Data source: ILOPublished: 2025

    0.42

    0.09Range of values carried here0.70

    Group-level value

    Scale, basis and source

    Generative AI exposure index, 0–1 as published

    ISCO-08 unit group — every occupation sharing the code gets this value

    Computed by this site, not published by the ILO: of the 1,012 occupations this site links to the ILO dataset, 33% score at or above this value.

    Source dataset

What kind of figure this source publishes

The BLS category is a relative rank, not an absolute level, and it is not a first-hand measurement: it groups an occupation's percentile ranks across several published studies into four bands. It is not an employment or wage forecast, not a probability of adoption, and it does not separate automation from augmentation.

Task-level exposure

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
Write reports to summarize testing activities, including descriptions of goals, planning, scheduling, execution, results, analysis, conclusions, and recommendations.

O*NET Task ID 15947

1.0
Establish, maintain, or test call trees to ensure appropriate communication during disaster.

O*NET Task ID 15951

1.0
Create or administer training and awareness presentations or materials.

O*NET Task ID 15954

1.0
Maintain and update organization information technology applications and network systems blueprints.

O*NET Task ID 15948

0.5
Interpret government regulations and applicable codes to ensure compliance.

O*NET Task ID 15949

0.5
Identify individual or transaction targets to direct intelligence collection.

O*NET Task ID 15950

0.5
Design or implement products and services to mitigate risk or facilitate use of technology-based tools and methods.

O*NET Task ID 15952

0.5
Create business continuity and disaster recovery budgets.

O*NET Task ID 15953

0.5
Attend professional meetings, read literature, and participate in training or other educational offerings to keep abreast of new developments and technologies related to disaster recovery and business continuity.

O*NET Task ID 15955

0.5
Test documented disaster recovery strategies and plans.

O*NET Task ID 15956

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

Occupation information