Data Entry Keyers
Office and Administrative Support Occupations- O*NET-SOC code
- 43-9021.00
Operate data entry device, such as keyboard or photo composing perforator. Duties may include verifying data and preparing materials for printing.
- Data source: BLSPublished: 2026-08
Very high· 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
0.671
0.000Range of values carried here0.745Scale, basis and source
Observed exposure index, 0–1 as published
Mapped onto O*NET tasks
Published per SOC 2018 occupation; every O*NET occupation with the same SOC 2018 code carries this value
- Data source: ILOPublished: 2025
0.70
0.09Range of values carried here0.70Group-level value
Scale, basis and source
Generative AI exposure index, 0–1 as published
Published per ISCO-08 unit group. Linked to this occupation, wholly or in part, by applying U.S. Bureau of Labor Statistics crosswalks (ISCO-08 to 2010 SOC, 2010 SOC to 2018 SOC) as published
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 7 hidden tasks9 rated tasks · 8 tasks with β ≥ 0.5 (88.9%)
β = direct exposure (E1) + 0.5 × exposure when tools are available (E2), per the source repository's definition.
- Source unit: O*NET 27.2 tasks → O*NET 31.0 occupation code
- All rated tasks are in the O*NET 31.0 task list.
- Source
- OpenAI "GPTs are GPTs" exposure rubric
- Release
- gh-main-0471612
- License
- MIT License, Copyright (c) 2024 OpenAI
| Task (O*NET 20.1) | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Compile, sort and verify the accuracy of data before it is entered.43-9021.00 | 0.016778.0 | 0.113265.6 |
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.43-9021.00 | 0.004722.0 | 0.059534.4 |
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 (O*NET 27.2) | βE1 + 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 |
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
All O*NET 31.0 task statements (9)
All O*NET 31.0 task statements for this occupation (English, as published; task type core or supplemental). Exposure values are not listed here; they are in the table above, next to each task statement as worded in the O*NET version each source used.
| Task (O*NET 31.0) | Type |
|---|---|
| Compile, sort, and verify the accuracy of data before it is entered. | Core |
| Compare data with source documents, or re-enter data in verification format to detect errors. | Core |
| Store completed documents in appropriate locations. | Core |
| Locate and correct data entry errors, or report them to supervisors. | Core |
| Select materials needed to complete work assignments. | Core |
| 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. | Supplemental |
| Maintain logs of activities and completed work. | Supplemental |
| Load machines with required input or output media, such as paper, cards, disks, tape, or Braille media. | Supplemental |
| Resolve garbled or indecipherable messages, using cryptographic procedures and equipment. | Supplemental |
0.10/ 3· Robot exposure index
Scale, basis and source
Each physical task is graded 0–3 by the setting in which robots that have been deployed, sold or demonstrated could do it (0 none · 1 purpose-built robot settings such as a fenced machine cell or a bottling line · 2 structured facilities such as a hospital pharmacy or a container port · 3 unstructured settings such as a private home or a construction site), and the grades are averaged by share of working time
Physical tasks among this occupation's O*NET 29.3 tasks
Anthropic estimated the grades and time shares with Claude Opus 5 using web search, as of 2026.
The robot exposure index is a different measure from the AI exposure figures on this site and cannot be added to or compared with them. It does not measure actual adoption or cost, and 0 also covers occupations with no physical tasks.
Tier of each physical task
Robot environment tiers (E0–E3)
E0 noneDetails
Rated not doable by robots that have been deployed, sold or demonstrated, even in a purpose-built setting
E1 purpose-built robot settingsDetails
Rated doable in a setting built around the machine, such as a fenced machine cell or a bottling line
E2 structured facilitiesDetails
Rated doable in a human work facility that an institution keeps to a working standard, such as a hospital pharmacy or a container port
E3 unstructured settingsDetails
Rated doable in a setting that no institution keeps to a working standard, such as a private home or a construction site
Only tasks classified as physical are listed; other tasks have no tier in the source.
| Task (O*NET 29.3) | Robot environment tier |
|---|---|
| Store completed documents in appropriate locations. | E1 purpose-built robot settings |
| Select materials needed to complete work assignments. | E1 purpose-built robot settings |
| Load machines with required input or output media, such as paper, cards, disks, tape, or Braille media. | E1 purpose-built robot settings |
Occupation information
Employment outlook (BLS)
- Employment, 2025
- 132K
- Projected employment, 2035
- 98K
- Change (2025–35)
- -25.5%
- Median annual wage, 2025
- $41,340
- Typical education needed for entry
- High school diploma or equivalent
Korea classification links (KSCO)
Links from the current release of the Korea Occupation Direct Crosswalk v1.1, made by AI Changing Work. Relation values are read from the O*NET-SOC occupation side.
| KSCO code | KSCO title | Relation | Status |
|---|---|---|---|
| 37239 | 그 외 전산 자료 입력원 | Same scope | confirmed |
Relation and status definitions(kr-direct v1.1)
ILO occupational description
AI Changing Work links the ISCO-08 unit groups below to this occupation by applying the U.S. Bureau of Labor Statistics crosswalks (2018 SOC to 2010 SOC, 2010 SOC to ISCO-08) as published, without case-by-case selection; each link may be whole or partial.
- ISCO-08 4132Data Entry Clerks
The definition, tasks and examples below are the ILO's description of that unit group, not of this occupation.
Data entry clerks enter coded, statistical, financial and other numerical data into electronic equipment, computerized databases, spreadsheets or other data repositories using a keyboard, mouse, optical scanner, speech recognition software or other data entry tools. They enter data into mechanical and electronic devices to perform mathematical calculations.
Tasks
- (a) receiving and registering invoices, forms, records and other documents for data capture;
- (b) entering numerical data, codes and text from source material into computer-compatible storage and processing devices;
- (c) verifying accuracy and completeness of data and correcting entered data, if needed;
- (d) operating bookkeeping and calculating machines;
- (e) importing and exporting data between different database systems and software.
Example occupations
Data entry operator · Data input clerk · Payment entry clerk
Sources: ILO ISCO-08 — details: Credits
ESCO occupational vocabulary
Each entry below is matched to this occupation in the published ESCO-O*NET Crosswalk (version 1, 2022). The match types are that crosswalk's; the wording is AI Changing Work's.
- data entry clerkESCO 4132.1Same scope
Data entry clerks update, maintain and retrieve information held on computer systems. They prepare source data for computer entry by compiling and sorting information, process customer and account source documents by reviewing data for deficiencies and verify entered customer and account data.
- typistESCO 4131.1Overlapping, not the same
Typists operate computers to type and revise documents and compile material to be typed, such as correspondence, reports, statistical tables, forms, and audios. They read instructions accompanying material or follow verbal instructions to determine requirements such as number of copies needed, priority and desired format.
Source: European Commission, DG EMPL — ESCO API 2026-08-08 (bridge v1.2.1)
License: CC BY 4.0 (EU Reuse Notice)
ESCO reuse terms and the modification notice are in Credits.
France classification links (ROME)
AI Changing Work's links between this occupation and ROME 4.0 job profiles, judged with AI models. Relations are read from this occupation's side. Links marked “provisional” were adopted on the judgments of two judges from the same model family (Claude) alone, or by an operator rule applied to their judgments, so they rest on weaker evidence than confirmed links.
| ROME code | ROME title (French) | Relation |
|---|---|---|
| M1606 | Opérateur / Opératrice de saisie | Same scopeprovisional |
Source: France Travail — Répertoire Opérationnel des Métiers et des Emplois (ROME 4.0), version 61, last updated 15 June 2026 (https://www.data.gouv.fr/datasets/repertoire-operationnel-des-metiers-et-des-emplois-rome). Licence Ouverte 2.0.
ROME codes and titles are reproduced unchanged; the links to O*NET-SOC occupations are AI Changing Work's own judgment and are not a France Travail correspondence.
(AI Changing Work link release: fr-direct v1)
Spain classification links (CNO-11)
AI Changing Work's links between this occupation and CNO-11 occupations, judged with AI models. Relations are read from this occupation's side.
| CNO-11 code | CNO-11 title (Spanish) | Relation |
|---|---|---|
| 4301 | Grabadores de datos | Same scopeprovisional |
Source: Instituto Nacional de Estadística (INE), National Classification of Occupations 2011 (CNO-11, Royal Decree 1591/2010) — www.ine.es · Licensed CC BY 4.0. CNO-11 codes and Spanish titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own judgment and are not an INE correspondence.
(AI Changing Work link release: es-direct v1)
Germany classification links (KldB)
AI Changing Work's links between this occupation and KldB occupations, judged with AI models. Relations are read from this occupation's side.
| KldB code | KldB title (German) | Relation |
|---|---|---|
| 71401 | Büro- und Sekretariatskräfte (ohne Spezialisierung) - Helfer-/Anlerntätigkeiten | This occupation is narrowerprovisional |
| 71432 | Steno- und Phonotypisten/-typistinnen - fachlich ausgerichtete Tätigkeiten | Related, not a matchprovisional |
Source: © Statistik der Bundesagentur für Arbeit — Klassifikation der Berufe 2010 – überarbeitete Fassung 2020, https://statistik.arbeitsagentur.de. KldB codes and titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own mapping (eigene Zuordnung) and are not a Bundesagentur für Arbeit correspondence.
(AI Changing Work link release: de-direct v1)
Japan classification links (JSCO)
AI Changing Work's links between this occupation and JSCO occupations, judged with AI models. Relations are read from this occupation's side.
| JSCO code | JSCO title (Japanese) | Relation |
|---|---|---|
| 312 | データ・エントリー装置操作員 | Same scopeprovisional |
Source: Ministry of Internal Affairs and Communications (MIC), Japan Standard Occupational Classification (Dec. 2009, MIC Notification No. 555). JSCO codes and Japanese titles are reproduced unchanged; the links to O*NET occupations are AI Changing Work's own judgment and are not a MIC correspondence.
(AI Changing Work link release: jp-direct v1)
Recent Changes Related to This Occupation
Summaries and relation labels are AI Changing Work's own; check any figures against the linked source.
Directly related 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.
[Source: EIG: AI and Young-Adult Jobs (March 2026)]Directly related 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.
[Source: Anthropic Economic Index (Jan 2026)]Related ILO global analysis confirms clerical data processing among highest AI exposure occupations. Global automation score slightly decreased from 0.30 to 0.29.
[Source: ILO GenAI Index 2025]
Sources, licenses and AI Changing Work's modification and translation notices for this page: Credits & sources