ロジスティクス専門家
輸送・資材運搬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
0.157
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
0.46
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24%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 55 件を表示| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Develop or maintain cost estimates, forecasts, or cost models.13-1081 | 0.037832.2 | 0.00636.9 |
Develop or maintain payment systems to ensure accuracy of vendor payments.13-1081 | 0.012110.3 | 0.00697.5 |
Develop an understanding of customers' needs and take actions to ensure that such needs are met.13-1081 | 0.00937.9 | 0.012914.1 |
Determine feasibility of designing new facilities or modifying existing facilities, based on factors such as cost, available space, schedule, technical requirements, or ergonomics.13-1081 | 0.00685.8 | —0 |
Support the development of training materials and technical manuals.13-1081 | 0.00554.7 | —0 |
Develop and implement technical project management tools, such as plans, schedules, and responsibility and compliance matrices.13-1081 | 0.00514.3 | 0.00151.6 |
Analyze or interpret logistics data involving customer service, forecasting, procurement, manufacturing, inventory, transportation, or warehousing.13-1081 | 0.00504.3 | 0.019721.5 |
Develop logistic metrics, internal analysis tools, or key performance indicators for business units.13-1081 | 0.00443.7 | —0 |
Propose logistics solutions for customers.13-1081 | 0.00423.6 | —0 |
Determine packaging requirements.13-1081 | 0.00403.4 | 0.00192.1 |
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 |
|---|---|
Report project plans, progress, and results.O*NET Task ID 8940 | 1.0 |
Support the development of training materials and technical manuals.O*NET Task ID 8947 | 1.0 |
Develop an understanding of customers' needs and take actions to ensure that such needs are met.O*NET Task ID 8933 | 0.5 |
Direct availability and allocation of materials, supplies, and finished products.O*NET Task ID 8934 | 0.5 |
Collaborate with other departments as necessary to meet customer requirements, to take advantage of sales opportunities or, in the case of shortages, to minimize negative impacts on a business.O*NET Task ID 8935 | 0.5 |
Review logistics performance with customers against targets, benchmarks, and service agreements.O*NET Task ID 8937 | 0.5 |
Develop and implement technical project management tools, such as plans, schedules, and responsibility and compliance matrices.O*NET Task ID 8938 | 0.5 |
Direct team activities, establishing task priorities, scheduling and tracking work assignments, providing guidance, and ensuring the availability of resources.O*NET Task ID 8939 | 0.5 |
Direct and support the compilation and analysis of technical source data necessary for product development.O*NET Task ID 8941 | 0.5 |
Explain proposed solutions to customers, management, or other interested parties through written proposals and oral presentations.O*NET Task ID 8942 | 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