保険販売員
営業・マーケティング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
0.319
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
0.53
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14%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 9 件を表示| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Interview prospective clients to obtain data about their financial resources and needs, the physical condition of the person or property to be insured, and to discuss any existing coverage.41-3021 | 0.009419.7 | 0.055058.6 |
Customize insurance programs to suit individual customers, often covering a variety of risks.41-3021 | 0.008718.3 | 0.016617.7 |
Explain necessary bookkeeping requirements for customer to implement and provide group insurance program.41-3021 | 0.008016.8 | —0 |
Confer with clients to obtain and provide information when claims are made on a policy.41-3021 | 0.007616.0 | 0.009610.2 |
Call on policyholders to deliver and explain policy, to analyze insurance program and suggest additions or changes, or to change beneficiaries.41-3021 | 0.005411.3 | —0 |
Develop marketing strategies to compete with other individuals or companies who sell insurance.41-3021 | 0.00275.7 | —0 |
Seek out new clients and develop clientele by networking to find new customers and generate lists of prospective clients.41-3021 | 0.00255.3 | 0.009910.5 |
Install bookkeeping systems and resolve system problems.41-3021 | 0.00183.8 | —0 |
Calculate premiums and establish payment method.41-3021 | 0.00153.2 | —0 |
Explain features, advantages, and disadvantages of various policies to promote sale of insurance plans. | —0 | 0.00293.1 |
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 |
|---|---|
Calculate premiums and establish payment method.O*NET Task ID 719 | 1.0 |
Perform administrative tasks, such as maintaining records and handling policy renewals.O*NET Task ID 728 | 1.0 |
Install bookkeeping systems and resolve system problems.O*NET Task ID 734 | 1.0 |
Call on policyholders to deliver and explain policy, to analyze insurance program and suggest additions or changes, or to change beneficiaries.O*NET Task ID 718 | 0.5 |
Customize insurance programs to suit individual customers, often covering a variety of risks.O*NET Task ID 720 | 0.5 |
Sell various types of insurance policies to businesses and individuals on behalf of insurance companies, including automobile, fire, life, property, medical and dental insurance, or specialized policies, such as marine, farm/crop, and medical malpractice.O*NET Task ID 721 | 0.5 |
Interview prospective clients to obtain data about their financial resources and needs, the physical condition of the person or property to be insured, and to discuss any existing coverage.O*NET Task ID 722 | 0.5 |
Seek out new clients and develop clientele by networking to find new customers and generate lists of prospective clients.O*NET Task ID 723 | 0.5 |
Explain features, advantages, and disadvantages of various policies to promote sale of insurance plans.O*NET Task ID 724 | 0.5 |
Contact underwriter and submit forms to obtain binder coverage.O*NET Task ID 725 | 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