Agricultural Inspectors

Food Preparation & Service

AI exposure

  • Data source: BLSPublished: 2026-08

    Moderate· 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

    0.36

    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, 60% 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 11 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
Write reports of findings and recommendations and advise farmers, growers, or processors of corrective action to be taken.

O*NET Task ID 14851

1.0
Compare product recipes with government-approved formulas or recipes to determine acceptability.

O*NET Task ID 14864

1.0
Interpret and enforce government acts and regulations and explain required standards to agricultural workers.

O*NET Task ID 14850

0.5
Label and seal graded products and issue official grading certificates.

O*NET Task ID 14857

0.5
Set standards for the production of meat or poultry products or for food ingredients, additives, or compounds used to prepare or package products.

O*NET Task ID 14859

0.5
Inquire about pesticides or chemicals to which animals may have been exposed.

O*NET Task ID 14861

0.5
Set labeling standards and approve labels for meat or poultry products.

O*NET Task ID 14862

0.5
Examine, weigh, and measure commodities, such as poultry, eggs, meat, or seafood to certify qualities, grades, and weights.

O*NET Task ID 14863

0.5
Review and monitor foreign product inspection systems in countries of origin to ensure equivalence to the U.S. system.

O*NET Task ID 14865

0.5
Provide consultative services in areas such as equipment or product evaluation, plant construction or layout, or food safety systems.

O*NET Task ID 14866

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