Bookkeeping Clerks

Office & Administrative Support

AI exposure

  • Data source: BLSPublished: '26.08

    Very high· relative

    LowFour relative bandsVery high

    Group-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

    Source dataset (XLSX download)

  • Data source: AnthropicPublished: '26.03

    0.310

    0.000Range of values carried here0.745
    Scale, basis and source

    Observed exposure index, 0–1 as published

    Mapped onto O*NET tasks

    Source dataset

  • Data source: ILOPublished: '25

    0.49

    0.09Range of values carried here0.70

    Group-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, 21% score at or above this value.

    Source dataset

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

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.

TaskβE1 + 0.5 × E2
Check figures, postings, and documents for correct entry, mathematical accuracy, and proper codes.

O*NET Task ID 2486

1.0
Operate computers programmed with accounting software to record, store, and analyze information.

O*NET Task ID 2487

1.0
Debit, credit, and total accounts on computer spreadsheets and databases, using specialized accounting software.

O*NET Task ID 2489

1.0
Classify, record, and summarize numerical and financial data to compile and keep financial records, using journals and ledgers or computers.

O*NET Task ID 2490

1.0
Code documents according to company procedures.

O*NET Task ID 2493

1.0
Operate 10-key calculators, typewriters, and copy machines to perform calculations and produce documents.

O*NET Task ID 2495

1.0
Perform financial calculations, such as amounts due, interest charges, balances, discounts, equity, and principal.

O*NET Task ID 2497

1.0
Perform general office duties, such as filing, answering telephones, and handling routine correspondence.

O*NET Task ID 2498

1.0
Calculate and prepare checks for utilities, taxes, and other payments.

O*NET Task ID 2501

1.0
Compare computer printouts to manually maintained journals to determine if they match.

O*NET Task ID 2502

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®, Eloundou et al. (2023): see full notices on the Credits page

Occupation information

Recent Changes Affecting This Occupation

Apr 2026: Bookkeeping clerks classified in office/administrative high-risk segment by OpenAI framework — repetitive structured ledger and reconciliation work.

[Source: OpenAI Jobs Transition Framework, April 2026]

Mar 2026: Brookings retraining analysis: workers displaced by AI from clerical roles face challenging transitions. TAA participants remained underemployed even 4 years after job loss.

[Source: Brookings Institution]

Mar 2026: AI Layoff Trap research highlights bookkeeping as especially vulnerable to over-automation due to highly structured task composition in competitive markets.

[Source: Falk & Tsoukalas (2026), The AI Layoff Trap]