销售代表
销售与市场营销AI暴露度
- 数据来源: BLS发布时间: '26.08
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: ILO发布时间: '25
0.49
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 21%。
- 数据来源: OpenAI发布时间: '23
0.567
0.000此处所载数值的范围0.844尺度 · 母数 · 来源
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
仅显示有暴露的工作| Task | Claude.aiRaw / share % |
|---|---|
Analyze customer bills and utility rate structures to select optimal rate structures for customers.41-3099 | 0.003546.1 |
Explain contracts or related documents to customers.41-3099 | 0.002330.3 |
Monitor the flow of energy in response to changes in consumer demand.41-3099 | 0.001823.7 |
| Not observed on any surface — 13 task(s) — These tasks have no row in the source for this release. The 0 in the share row is a display-stage composition ratio; absence is what the — in the raw row states. | |
Contact prospective buyers or sellers of power to arrange transactions. | —0 |
Answer customer questions related to energy sales procedures, energy markets, or alternative energy sources. | —0 |
Forecast energy supply and demand to minimize costs and maximize availability. | —0 |
Negotiate prices or contracts for energy sales or purchases. | —0 |
Price energy based on market conditions. | —0 |
Develop or deliver proposals or presentations on topics such as the purchase or sale of energy. | —0 |
Purchase or sell energy or energy derivatives for customers. | —0 |
Create product packages based on assessment of customers' needs. | —0 |
Facilitate the delivery or receipt of wholesale power or retail load scheduling. | —0 |
Analyze and evaluate energy supply bids to determine the best options. | —0 |
Monitor energy supply contracts to ensure proper implementation and execution by suppliers. | —0 |
Prepare and send requests for price quotations to all energy companies in a particular market. | —0 |
Research and recommend new products or services, such as alternative energy sources or renewable energy credits. | —0 |
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 |
|---|---|
Create forms or agreements to complete sales.O*NET Task ID 23227 | 1.0 |
Develop sales presentations or proposals to explain service specifications.O*NET Task ID 23228 | 1.0 |
Inform customers of contracts or other information pertaining to purchased services.O*NET Task ID 23232 | 1.0 |
Maintain customer records using automated systems.O*NET Task ID 23233 | 1.0 |
Quote prices, credit terms, contract terms, or fulfillment dates for services.O*NET Task ID 23236 | 1.0 |
Answer customers' questions about services, prices, availability, or credit terms.O*NET Task ID 23222 | 0.5 |
Attend sales or trade meetings or read related publications to obtain information about market conditions, business trends, regulations, or industry developments.O*NET Task ID 23223 | 0.5 |
Compute and compare costs of services.O*NET Task ID 23224 | 0.5 |
Consult with clients after sales or contract signings to resolve problems and provide ongoing support.O*NET Task ID 23225 | 0.5 |
Contact prospective or existing customers to discuss how services can meet their needs.O*NET Task ID 23226 | 0.5 |
Distribute promotional materials at meetings, conferences, or trade shows.O*NET Task ID 23229 | 0.0 |
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
Occupation information
与本职业相关的近期变化
2026年3月: ATE study identifies sales representatives among 236 information-intensive occupations at moderate-to-high risk of agentic AI displacement by 2030 in US tech hubs.
[来源: Gupta & Kumar (2026) Agentic AI and Occupational Displacement]