Billing and Posting Clerks
Office & Administrative SupportAI exposure
- 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
0.192
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: 2025
0.64
0.09Range of values carried here0.70Group-level value
Scale, basis and source
Generative AI exposure index, 0–1 as published
ISCO-08 unit group — every occupation sharing the code gets this value
Computed by this site, not published by the ILO: of the 1,012 occupations this site links to the ILO dataset, 1% score at or above this value.
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 19 hidden tasks| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Prepare itemized statements, bills, or invoices and record amounts due for items purchased or services rendered.43-3021 | 0.016634.1 | —0 |
Resolve discrepancies in accounting records.43-3021 | 0.009419.3 | 0.00677.8 |
Verify accuracy of billing data and revise any errors.43-3021 | 0.006212.7 | 0.033038.5 |
Review documents such as purchase orders, sales tickets, charge slips, or hospital records to compute fees or charges due.43-3021 | 0.00449.0 | 0.022125.8 |
Compile reports of cost factors, such as labor, production, storage, or equipment.43-3021 | 0.00387.8 | —0 |
Estimate market value of products or services.43-3021 | 0.00275.5 | —0 |
Monitor equipment to ensure proper operation.43-3021 | 0.00255.1 | —0 |
Compare previously prepared bank statements with canceled checks and reconcile discrepancies.43-3021 | 0.00163.3 | —0 |
Perform bookkeeping work, including posting data or keeping other records concerning costs of goods or services or the shipment of goods.43-3021 | 0.00153.1 | —0 |
Keep records of invoices and support documents. | —0 | 0.013215.4 |
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 | βE1 + 0.5 × E2 |
|---|---|
Post stop-payment notices to prevent payment of protested checks.O*NET Task ID 23237 | 1.0 |
Verify accuracy of billing data and revise any errors.O*NET Task ID 23238 | 1.0 |
Prepare itemized statements, bills, or invoices and record amounts due for items purchased or services rendered.O*NET Task ID 23240 | 1.0 |
Perform bookkeeping work, including posting data or keeping other records concerning costs of goods or services or the shipment of goods.O*NET Task ID 23241 | 1.0 |
Operate typing, adding, calculating, or billing machines.O*NET Task ID 23242 | 1.0 |
Resolve discrepancies in accounting records.O*NET Task ID 23243 | 1.0 |
Review documents, such as purchase orders, sales tickets, charge slips, or hospital records, to compute fees or charges due.O*NET Task ID 23245 | 1.0 |
Keep records of invoices and support documents.O*NET Task ID 23246 | 1.0 |
Route statements for mailing or over-the-counter delivery to customers.O*NET Task ID 23247 | 1.0 |
Compare previously prepared bank statements with canceled checks and reconcile discrepancies.O*NET Task ID 23251 | 1.0 |
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®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page