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办公与行政支持

AI暴露度

  • 数据来源: BLS发布时间: 2026-08

    很高· 相对

    低四级相对区间很高

    职业群单位数值

    尺度 · 母数 · 来源

    四级相对类别（低 / 中等 / 高 / 很高）

    以BLS就业预测表中831个细分职业为基数。取值按 NEM（全国就业矩阵）代码给定，因此共用同一 NEM 代码的职业得到相同分档

    来源数据集（XLSX 文件下载）

  • 数据来源: Anthropic发布时间: 2026-03

    0.671

    0.000此处所载数值的范围0.745
    尺度 · 母数 · 来源

    观测暴露度指数，按发布原值0–1

    以O*NET任务映射为基准

    来源数据集

  • 数据来源: ILO发布时间: 2025

    0.70

    0.09此处所载数值的范围0.70

    职业群单位数值

    尺度 · 母数 · 来源

    生成式AI暴露度指数，按发布原值0–1

    ISCO-08职业小类单位 — 共用同一代码的职业取值相同

    本站计算，并非国际劳工组织发布的数值。在本站与 ILO 数据集相连的 1,012 个职业中，达到或高于此值的占 0%。

    来源数据集

该来源发布的是什么性质的数值

BLS的类别是相对排位而非绝对水平，也不是一手测量：它把多项已发表研究给出的职业百分位排名归并为四个等级。它不是就业或工资预测，不是采用概率，也不区分自动化与增强。

Task-level exposure

仅显示有暴露的工作

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

职业信息

与本职业相关的近期变化

2026年3月: EIG (Mar 2026): data entry keyers made up only 0.2% of employed 22-25 year-olds in 2018-2021, so automating data entry cannot explain much of the weakness in youth employment.

[来源: EIG: AI and Young-Adult Jobs (March 2026)]

2026年1月: Anthropic Economic Index report (Jan 2026): data entry keyers have one of the highest "effective AI coverage" scores. Only two of their nine tasks appear in Claude usage, but their largest task, reading and entering data from source documents, has high success rates with Claude.

[来源: Anthropic Economic Index (Jan 2026)]

2025年5月: ILO global analysis confirms clerical data processing among highest AI exposure occupations. Global automation score slightly decreased from 0.30 to 0.29.

[来源: ILO GenAI Index 2025]

These summaries were written by AI Changing Work from the source linked with each one, and any figures in them are given as AI Changing Work summarised them; they can differ from the source's own wording and from figures shown elsewhere on this page, so check the source before relying on them. AI Changing Work matched this page's occupation to an O*NET occupation and chose, by its own judgment, case by case, which summaries relate to that O*NET occupation; a summary appearing here does not mean that its source names this occupation.