売掛金管理担当者
ビジネス・金融AI露出度
- データ出典: BLS公表時点: 2026-08
非常に高い· 相対
低い4段階の相対区分非常に高い職業群単位の値
尺度・母数・出典
4段階の相対区分（低い / 中程度 / 高い / 非常に高い）
BLS雇用見通し表の詳細職業831件が母数。値は NEM(全国雇用マトリクス)コード単位で付与されるため、同じ NEM コードの職業は同じバンドになります
- データ出典: Anthropic公表時点: 2026-03
0.310
0.000ここに掲載された値の範囲0.745尺度・母数・出典
- データ出典: ILO公表時点: 2025
0.49
0.09ここに掲載された値の範囲0.70職業群単位の値
尺度・母数・出典
生成AI露出度指数、公開されたまま0–1
ISCO-08の職業小分類単位 — 同じコードの職業はすべて同じ値
当サイトの算出であり、ILOが公表した数値ではありません。当サイトがILOデータセットに結び付けた職業1,012件のうち、この値以上のものは21%です。
この出典がどのような性格の値か
BLSの区分は絶対水準ではなく相対順位であり、一次測定でもありません。複数の既存研究が付けた職業別パーセンタイル順位を4段階にまとめた値です。雇用や賃金の予測でもなく、導入確率でもなく、自動化と増強を区別しません。
Task-level exposure
非表示の作業 19 件を表示| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Perform financial calculations, such as amounts due, interest charges, balances, discounts, equity, and principal.43-3031 | 0.260081.3 | 0.060016.2 |
Check figures, postings, and documents for correct entry, mathematical accuracy, and proper codes.43-3031 | 0.01003.1 | 0.03008.1 |
Compile statistical, financial, accounting, or auditing reports and tables pertaining to such matters as cash receipts, expenditures, accounts payable and receivable, and profits and losses.43-3031 | 0.01003.1 | 0.01002.7 |
Debit, credit, and total accounts on computer spreadsheets and databases, using specialized accounting software.43-3031 | 0.01003.1 | 0.00000.0 |
Classify, record, and summarize numerical and financial data to compile and keep financial records, using journals and ledgers or computers.43-3031 | 0.01003.1 | 0.00000.0 |
Transfer details from separate journals to general ledgers or data processing sheets.43-3031 | 0.01003.1 | 0.00000.0 |
Calculate costs of materials, overhead, and other expenses, based on estimates, quotations and price lists.43-3031 | 0.01003.1 | 0.00000.0 |
Code documents according to company procedures.43-3031 | 0.00000.0 | 0.220059.5 |
Access computerized financial information to answer general questions as well as those related to specific accounts.43-3031 | 0.00000.0 | 0.050013.5 |
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 |
|---|---|
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®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page
職業情報
この職業に関わる最近の変化
2025年5月: Brookings retraining analysis: workers displaced by AI from clerical roles face challenging transitions. TAA participants remained underemployed even 4 years after job loss.
[出典: Brookings Institution]2024年10月: Brookings (Oct 2024) names bookkeepers among the office and administrative support jobs, a sector with high generative AI exposure and high automation potential, that have long given women without a college degree decent-paying, stable work.
[出典: Brookings 2024 — Generative AI, the American worker]These summaries were written by AI Changing Work from the source linked with each one, and any figures in them are given as AI Changing Work summarised them; they can differ from the source's own wording and from figures shown elsewhere on this page, so check the source before relying on them. AI Changing Work matched this page's occupation to an O*NET occupation and chose, by its own judgment, case by case, which summaries relate to that O*NET occupation; a summary appearing here does not mean that its source names this occupation.