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AI exposure Office and administrative support

Will AI replace credit authorizers?

Credit Authorizers, Checkers, and Clerks. US occupation 43-4041.

13.0%

of the time credit authorizers spend on their work goes on tasks where AI is already being used to do that work.of credit authorizers' working hours go on tasks AI has already started taking off their plate.

Ranked 160 of 756 US occupations. More exposed than 78% of them.Further along than 78% of them.

Average US job 7.7%

Well above the typical job.Ahead of most of the workforce.

What AI already does for credit authorizersWhat credit authorizers no longer do alone

O*NET lists 16 tasks for credit authorizers. AI use at work shows up in 3 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.

  1. Receive charge slips or credit applications by mail, or receive information from salespeople or merchants by telephone. mostly automated 0.98
  2. Relay credit report information to subscribers by mail or by telephone. mostly automated 0.95
  3. Prepare reports of findings and recommendations. automated and assisted 0.72

What it does not touch, yetWhat still needs a human

13 of the 16 tasks show no AI use at work in the data.

  • Compile and analyze credit information gathered by investigation.Core task
  • Interview credit applicants by telephone or in person to obtain personal and financial data needed to complete credit report.Core task
  • Keep records of customers' charges and payments.Core task
  • Obtain information about potential creditors from banks, credit bureaus, and other credit services, and provide reciprocal information if requested.Core task
  • Call customers to collect payment on delinquent accounts.
  • Consult with customers to resolve complaints or verify financial or credit transactions.
Show the other 7
  • Contact former employers and other acquaintances to verify applicants' references, employment, health history, or social behavior.
  • Evaluate customers' computerized credit records and payment histories to decide whether to approve new credit, based on predetermined standards.
  • Examine city directories and public records to verify residence property ownership, bankruptcies, liens, arrest record, or unpaid taxes of applicants.
  • File sales slips in customers' ledgers for billing purposes.
  • Mail charge statements to customers.
  • Prepare credit cards or charge account plates.
  • Review individual or commercial customer files to identify and select delinquent accounts for collection.

How that compares

Among the 50 office and administrative support occupations, credit authorizers rank 28. 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%.

All 756 occupations, ranked

Just above in the ranking

  1. 157Special Education Teachers, Middle School 13.4%
  2. 158Bioengineers and Biomedical Engineers 13.3%
  3. 158Dietitians and Nutritionists 13.3%

Just below

  1. 161Tax Preparers 12.8%
  2. 162Personal Service Managers, All Other 12.4%
  3. 163Police and Sheriff's Patrol Officers 12.3%

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.