Data Entry Keyers

Office & Administrative Support

AI exposure

  • Data source: BLSPublished: '26.08

    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: '26.03

    0.671

    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: '25

    0.70

    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, 0% 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

Exposed tasks only

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
Compile, sort, and verify the accuracy of data before it is entered.

O*NET Task ID 11402

1.0
Compare data with source documents, or re-enter data in verification format to detect errors.

O*NET Task ID 11403

1.0
Store completed documents in appropriate locations.

O*NET Task ID 11404

1.0
Locate and correct data entry errors, or report them to supervisors.

O*NET Task ID 11405

1.0
Maintain logs of activities and completed work.

O*NET Task ID 11406

1.0
Select materials needed to complete work assignments.

O*NET Task ID 11407

1.0
Resolve garbled or indecipherable messages, using cryptographic procedures and equipment.

O*NET Task ID 11409

1.0
Read source documents such as canceled checks, sales reports, or bills, and enter data in specific data fields or onto tapes or disks for subsequent entry, using keyboards or scanners.

O*NET Task ID 11401

0.5
Load machines with required input or output media, such as paper, cards, disks, tape, or Braille media.

O*NET Task ID 11408

0.0

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®, Eloundou et al. (2023): see full notices on the Credits page

Occupation information

Recent Changes Affecting This Occupation

May 2026: Anthropic observed-exposure score: high (routine tasks absorbed). High observed exposure; routine tasks already absorbed by LLMs.

[Source: Anthropic Economic Research (Massenkoff & McCrory, 2026)]

Apr 2026: NBER survey of 6,000 executives: 69% use AI but 90% report zero employment impact. Executives predict -0.7% employment decline over next 3 years.

[Source: NBER Working Paper 34836]

Apr 2026: Among highest automation exposure occupations. AI topped all job cut reasons in March 2026 with 15,341 positions (25% of total). Q1 cumulative AI cuts: 27,645.

[Source: Challenger March 2026]