Postal Service Mail Sorters
Office & Administrative SupportAI exposure
- Data source: BLSPublished: 2026-08
Low· relative
LowFour relative bandsVery highGroup-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
- Data source: AnthropicPublished: 2026-03
0.000
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: 2025
0.41
0.09Range of values carried here0.70Group-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, 36% score at or above this value.
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
| Task | APIRaw / share % |
|---|---|
Direct items according to established routing schemes, using computer-controlled keyboards or voice-recognition equipment.43-5053 | 0.00000.0 |
Operate various types of equipment, such as computer scanning equipment, addressographs, mimeographs, optical character readers, and bar-code sorters.43-5053 | 0.00000.0 |
| Not observed on any surface — 12 task(s) — These tasks have no row in the source for this release. The 0 in the share row is a display-stage composition ratio; absence is what the — in the raw row states. | |
Clear jams in sorting equipment. | —0 |
Sort odd-sized mail by hand, sort mail that other workers have been unable to sort, and segregate items requiring special handling. | —0 |
Bundle, label, and route sorted mail to designated areas, depending on destinations and according to established procedures and deadlines. | —0 |
Train new workers. | —0 |
Distribute incoming mail into the correct boxes or pigeonholes. | —0 |
Search directories to find correct addresses for redirected mail. | —0 |
Check items to ensure that addresses are legible and correct, that sufficient postage has been paid or the appropriate documentation is attached, and that items are in a suitable condition for processing. | —0 |
Open and label mail containers. | —0 |
Rewrap soiled or broken parcels. | —0 |
Move containers of mail, using equipment, such as forklifts and automated "trains". | —0 |
Load and unload mail trucks, sometimes lifting containers of mail onto equipment that transports items to sorting stations. | —0 |
Cancel letter or parcel post stamps by hand. | —0 |
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.
| Task | βE1 + 0.5 × E2 |
|---|---|
Direct items according to established routing schemes, using computer-controlled keyboards or voice-recognition equipment.O*NET Task ID 8213 | 1.0 |
Search directories to find correct addresses for redirected mail.O*NET Task ID 8220 | 1.0 |
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®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page