Logistics Analysts

Transportation & Material Moving

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

    0.157

    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

    0.46

    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, 24% 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
Enter logistics-related data into databases.

O*NET Task ID 15883

1.0
Write or revise standard operating procedures for logistics processes.

O*NET Task ID 15891

1.0
Maintain logistics records in accordance with corporate policies.

O*NET Task ID 15899

1.0
Enter carbon-output or environmental-impact data into spreadsheets or environmental management or auditing software programs.

O*NET Task ID 20014

1.0
Identify opportunities for inventory reductions.

O*NET Task ID 15881

0.5
Monitor industry standards, trends, or practices to identify developments in logistics planning or execution.

O*NET Task ID 15882

0.5
Develop or maintain payment systems to ensure accuracy of vendor payments.

O*NET Task ID 15884

0.5
Determine packaging requirements.

O*NET Task ID 15885

0.5
Develop or maintain freight rate databases for use by supply chain departments to determine the most economical modes of transportation.

O*NET Task ID 15886

0.5
Contact potential vendors to determine material availability.

O*NET Task ID 15887

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