Emergency Management Directors

Protective Service

AI exposure

  • Data source: BLSPublished: 2026-08

    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

    0.000

    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

    0.38

    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, 48% 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

Show 4 hidden tasks

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
Keep informed of activities or changes that could affect the likelihood of an emergency, response efforts, or plan implementation.

O*NET Task ID 7253

0.5
Prepare plans that outline operating procedures to be used in response to disasters or emergencies, such as hurricanes, nuclear accidents, and terrorist attacks, and in recovery from these events.

O*NET Task ID 7254

0.5
Propose alteration of emergency response procedures, based on regulatory changes, technological changes, or knowledge gained from outcomes of previous emergency situations.

O*NET Task ID 7255

0.5
Maintain and update all resource materials associated with emergency preparedness plans.

O*NET Task ID 7256

0.5
Coordinate disaster response or crisis management activities, such as ordering evacuations, opening public shelters, and implementing special needs plans and programs.

O*NET Task ID 7257

0.5
Keep informed of federal, state, and local regulations affecting emergency plans, and ensure that plans adhere to those regulations.

O*NET Task ID 7259

0.5
Prepare emergency situation status reports that describe response and recovery efforts, needs, and preliminary damage assessments.

O*NET Task ID 7260

0.5
Design and administer emergency or disaster preparedness training courses that teach people how to effectively respond to major emergencies and disasters.

O*NET Task ID 7261

0.5
Consult with officials of local and area governments, schools, hospitals, and other institutions to determine their needs and capabilities in the event of a natural disaster or other emergency.

O*NET Task ID 7263

0.5
Develop and perform tests and evaluations of emergency management plans in accordance with state and federal regulations.

O*NET Task ID 7264

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