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Will AI replace data entry jobs? Clerks, automation and the data

Updated

Data entry is the job people most often expect AI to take, and for once the data mostly agrees that the risk is real. Reading forms, extracting fields and typing them into systems is exactly what current AI tools do well.

The short answer: AI and automation are likely to keep shrinking pure data entry work. The ILO's 2025 index scores data entry clerks at 0.70, among the highest of any occupation and in its top exposure gradient. The US Bureau of Labor Statistics does not publish a separate data entry profile in its Occupational Outlook Handbook, but projects a 6 percent decline for general office clerks from 2025 to 2035, citing technology that automates clerical tasks. The work that remains moves toward checking, fixing and managing data. Projections can change.

How exposed data entry is

From the ILO's 2025 index, which scores tasks 0 to 1 for generative AI exposure:

Occupation (ISCO-08)ILO bandMean task score
Data Entry ClerksGradient 40.70
Typists and Word Processing OperatorsGradient 40.65
Accounting and Bookkeeping ClerksGradient 40.64
General Office ClerksGradient 40.60

Gradient 4 is the ILO's highest band. Even here, the ILO concludes that transformation of jobs is the most likely impact of generative AI overall, but it finds the highest exposure among clerical occupations.

What the BLS projects

OccupationProjected change 2025 to 2035Openings a year
General office clerksDecline 6%About 249,000

The BLS says the continued use of technology that automates document preparation and other clerical tasks, such as automated phone systems, is expected to mean fewer general office clerks are needed. All projected openings come from replacing workers who change occupations or retire, which is why openings stay high even as the occupation shrinks.

Data entry tasks AI is taking on

  • Reading scanned forms, invoices and receipts.
  • Extracting names, dates, amounts and codes into fields.
  • Copying data between systems.
  • Matching and deduplicating records.
  • Flagging missing or inconsistent entries.

Where the human work moves

  • Checking: AI extraction makes mistakes. Someone has to review exceptions and spot-check output. See checking AI output.
  • Exceptions: unreadable documents, unusual cases and records that do not fit.
  • Data quality: keeping records accurate and consistent across systems.
  • Privacy: handling personal data carefully when tools process it. See AI agents and personal data.
  • Running the workflow: setting up, monitoring and improving the automated process.

If you work in data entry

The most direct path is toward the checking and data quality side of the work, and from there to roles such as data analyst, bookkeeping or operations support. See AI skills to learn, AI jobs without coding and will AI replace data analysts?

See also will AI replace receptionists? and will AI take my job?

Pay and how to get in

The US Bureau of Labor Statistics puts the median annual pay for general office clerks at $45,010 in May 2025, against $50,980 for all workers. The typical education needed to enter is: high school diploma or equivalent. See how this job compares in AI exposure by pay and AI exposure by education level.

Questions and answers

Will AI replace data entry jobs?

Pure data entry is at high risk. The ILO scores data entry clerks at 0.70, in its highest gradient, and the BLS projects a 6 percent decline for general office clerks from 2025 to 2035, citing automation of clerical tasks.

How exposed are data entry clerks to AI?

In the ILO 2025 index, data entry clerks score 0.70, among the highest of any occupation.

Does the BLS project data entry jobs?

Its Occupational Outlook Handbook has no separate data entry profile. For general office clerks it projects a 6 percent decline with about 249,000 openings a year.

What data entry work stays human?

Checking AI output, handling exceptions, keeping data accurate, protecting personal data and running the automated workflow.

What can data entry workers move into?

Data quality and review roles, and from there data analysis, bookkeeping or operations support.

Sources