不動産エージェント
営業・マーケティングAI露出度
- データ出典: BLS公表時点: '26.08
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: '26.03
0.283
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: '25
0.35
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61%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 14 件を表示| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Advise clients on market conditions, prices, mortgages, legal requirements and related matters.41-9022 | 0.118148.9 | 0.027413.7 |
Promote sales of properties through advertisements, open houses, and participation in multiple listing services.41-9022 | 0.038115.8 | —0 |
Evaluate mortgage options to help clients obtain financing at the best prevailing rates and terms.41-9022 | 0.02369.8 | 0.01145.7 |
Answer clients' questions regarding construction work, financing, maintenance, repairs, and appraisals.41-9022 | 0.00853.5 | 0.01256.2 |
Generate lists of properties that are compatible with buyers' needs and financial resources.41-9022 | 0.00773.2 | 0.01467.3 |
Display commercial, industrial, agricultural, and residential properties to clients and explain their features.41-9022 | 0.00682.8 | 0.020710.3 |
Solicit and compile listings of available rental properties.41-9022 | 0.00582.4 | 0.01155.8 |
Interview clients to determine what kinds of properties they are seeking.41-9022 | 0.00562.3 | 0.039919.9 |
Act as an intermediary in negotiations between buyers and sellers, generally representing one or the other.41-9022 | 0.00522.2 | 0.01035.1 |
Rent or lease properties on behalf of clients.41-9022 | 0.00482.0 | 0.00201.0 |
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 |
|---|---|
Present purchase offers to sellers for consideration.O*NET Task ID 2440 | 0.5 |
Confer with escrow companies, lenders, home inspectors, and pest control operators to ensure that terms and conditions of purchase agreements are met before closing dates.O*NET Task ID 2441 | 0.5 |
Interview clients to determine what kinds of properties they are seeking.O*NET Task ID 2442 | 0.5 |
Prepare documents such as representation contracts, purchase agreements, closing statements, deeds, and leases.O*NET Task ID 2443 | 0.5 |
Coordinate property closings, overseeing signing of documents and disbursement of funds.O*NET Task ID 2444 | 0.5 |
Act as an intermediary in negotiations between buyers and sellers, generally representing one or the other.O*NET Task ID 2445 | 0.5 |
Promote sales of properties through advertisements, open houses, and participation in multiple listing services.O*NET Task ID 2446 | 0.5 |
Compare a property with similar properties that have recently sold to determine its competitive market price.O*NET Task ID 2447 | 0.5 |
Coordinate appointments to show homes to prospective buyers.O*NET Task ID 2448 | 0.5 |
Generate lists of properties that are compatible with buyers' needs and financial resources.O*NET Task ID 2449 | 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