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商业与金融AI暴露度
- 数据来源: BLS发布时间: 2026-08
很高· 相对
低四级相对区间很高职业群单位数值
尺度 · 母数 · 来源
四级相对类别（低 / 中等 / 高 / 很高）
以BLS就业预测表中831个细分职业为基数。取值按 NEM（全国就业矩阵）代码给定，因此共用同一 NEM 代码的职业得到相同分档
- 数据来源: Anthropic发布时间: 2026-03
0.186
0.000此处所载数值的范围0.745尺度 · 母数 · 来源
- 数据来源: ILO发布时间: 2025
0.60
0.09此处所载数值的范围0.70职业群单位数值
尺度 · 母数 · 来源
生成式AI暴露度指数，按发布原值0–1
ISCO-08职业小类单位 — 共用同一代码的职业取值相同
本站计算，并非国际劳工组织发布的数值。在本站与 ILO 数据集相连的 1,012 个职业中，达到或高于此值的占 4%。
该来源发布的是什么性质的数值
BLS的类别是相对排位而非绝对水平，也不是一手测量：它把多项已发表研究给出的职业百分位排名归并为四个等级。它不是就业或工资预测，不是采用概率，也不区分自动化与增强。
Task-level exposure
显示隐藏的 12 项工作| Task | Claude.aiRaw / share % |
|---|---|
Explain to customers the different types of loans and credit options that are available, as well as the terms of those services.13-2072 | 0.043550.2 |
Market bank products to individuals and firms, promoting bank services that may meet customers' needs.13-2072 | 0.010311.9 |
Work with clients to identify their financial goals and to find ways of reaching those goals.13-2072 | 0.009811.3 |
Analyze potential loan markets and develop referral networks to locate prospects for loans.13-2072 | 0.00708.1 |
Handle customer complaints and take appropriate action to resolve them.13-2072 | 0.00273.2 |
Set credit policies, credit lines, procedures and standards in conjunction with senior managers.13-2072 | 0.00252.9 |
Prepare reports to send to customers whose accounts are delinquent, and forward irreconcilable accounts for collector action.13-2072 | 0.00252.9 |
Negotiate payment arrangements with customers who have delinquent loans.13-2072 | 0.00232.7 |
Provide special services such as investment banking for clients with more specialized needs.13-2072 | 0.00212.4 |
Analyze applicants' financial status, credit, and property evaluations to determine feasibility of granting loans.13-2072 | 0.00202.3 |
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 |
|---|---|
Explain to customers the different types of loans and credit options that are available, as well as the terms of those services.O*NET Task ID 3410 | 1.0 |
Review loan agreements to ensure that they are complete and accurate according to policy.O*NET Task ID 3413 | 1.0 |
Compute payment schedules.O*NET Task ID 3414 | 1.0 |
Prepare reports to send to customers whose accounts are delinquent, and forward irreconcilable accounts for collector action.O*NET Task ID 3426 | 1.0 |
Authorize or sign mail collection letters.O*NET Task ID 21636 | 1.0 |
Review billing for accuracy.O*NET Task ID 21647 | 1.0 |
Approve loans within specified limits, and refer loan applications outside those limits to management for approval.O*NET Task ID 3407 | 0.5 |
Meet with applicants to obtain information for loan applications and to answer questions about the process.O*NET Task ID 3408 | 0.5 |
Analyze applicants' financial status, credit, and property evaluations to determine feasibility of granting loans.O*NET Task ID 3409 | 0.5 |
Obtain and compile copies of loan applicants' credit histories, corporate financial statements, and other financial information.O*NET Task ID 3411 | 0.5 |
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