AI exposure Office and administrative support
Will AI replace data entry keyers?
Data Entry Keyers, also called data entry clerks. US occupation 43-9021.
The reading
67.1%
of the time data entry keyers spend on their work goes on tasks where AI is already being used to do that work.of data entry keyers' working hours go on tasks AI has already started taking off their plate.
Ranked 3 of 756 US occupations. More exposed than 99% of them.Further along than 99% of them.
Per cent of working time Square-law scale
Average US job 7.7%
One of the most exposed jobs in the country.Front of the queue for an AI assistant.
What AI already does for data entry keyersWhat data entry keyers no longer do alone
O*NET lists 9 tasks for data entry keyers. AI use at work shows up in 1 of them. Each score runs from 0.5, where every observed use helps a person with the task, to 1, where every use does the task outright.
- 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. mostly automated 1.00
What it does not touch, yetWhat still needs a human
8 of the 9 tasks show no AI use at work in the data.
- Compare data with source documents, or re-enter data in verification format to detect errors.Core task
- Compile, sort, and verify the accuracy of data before it is entered.Core task
- Locate and correct data entry errors, or report them to supervisors.Core task
- Select materials needed to complete work assignments.Core task
- Store completed documents in appropriate locations.Core task
- Load machines with required input or output media, such as paper, cards, disks, tape, or Braille media.
Show the other 2
- Maintain logs of activities and completed work.
- Resolve garbled or indecipherable messages, using cryptographic procedures and equipment.
How that compares
Among the 50 office and administrative support occupations, data entry keyers rank 2. The group averages 19.1%, and its most exposed job is Customer Service Representatives at 70.1%. The average US occupation sits at 7.7%.
Just above in the ranking
- 1Computer Programmers 74.5%
- 2Customer Service Representatives 70.1%
Just below
What this does and does not mean
Exposure is observed use, not a forecast. Anthropic maps work conversations with Claude onto the tasks O*NET lists for each job and asks, of the tasks AI could speed up, which are actually being used for at work. A use that does the task outright counts in full and a use that assists a person counts half. The task scores are averaged into the occupation figure by the share of time spent on each task.
A high figure means AI is already part of how this work gets done. It does not mean anyone has been replaced. Anthropic's own reading of the labour market finds no systematic rise in unemployment among exposed workers so far, and about 14% fewer 22 to 25 year olds starting exposed jobs.No measurable rise in unemployment among exposed workers so far, and about 14% fewer 22 to 25 year olds starting these jobs. Gap years for everyone. Labor market impacts, 5 March 2026.
Task list and titles from O*NET 31.0 by the US Department of Labor, Employment and Training Administration, used under the CC BY 4.0 licence. Scores from the Anthropic Economic Index (CC BY). Checked 1 November 2026. How the ranking works.