Production, Planning, and Expediting Clerks

Office & Administrative Support

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

    0.093

    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

    0.44

    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, 28% 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 1 hidden task

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
Review documents, such as production schedules, work orders, or staffing tables, to determine personnel or materials requirements or material priorities.

O*NET Task ID 11363

1.0
Calculate figures, such as required amounts of labor or materials, manufacturing costs, or wages, using pricing schedules, adding machines, calculators, or computers.

O*NET Task ID 11369

1.0
Distribute production schedules or work orders to departments.

O*NET Task ID 11370

1.0
Maintain files, such as maintenance records, bills of lading, or cost reports.

O*NET Task ID 11374

1.0
Provide documentation and information to account for delays, difficulties, or changes to cost estimates.

O*NET Task ID 11378

1.0
Examine documents, materials, or products and monitor work processes to assess completeness, accuracy, and conformance to standards and specifications.

O*NET Task ID 11362

0.5
Revise production schedules when required due to design changes, labor or material shortages, backlogs, or other interruptions, collaborating with management, marketing, sales, production, or engineering.

O*NET Task ID 11365

0.5
Confer with establishment personnel, vendors, or customers to coordinate production or shipping activities and to resolve complaints or eliminate delays.

O*NET Task ID 11366

0.5
Record production data, including volume produced, consumption of raw materials, or quality control measures.

O*NET Task ID 11367

0.5
Requisition and maintain inventories of materials or supplies necessary to meet production demands.

O*NET Task ID 11368

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