ファイナンシャルアナリスト
ビジネス・金融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
0.572
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
0.62
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3%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 8 件を表示| Task | Claude.aiRaw / share % |
|---|---|
Present oral or written reports on general economic trends, individual corporations, and entire industries.13-2051 | 0.068423.4 |
Monitor fundamental economic, industrial, and corporate developments by analyzing information from financial publications and services, investment banking firms, government agencies, trade publications, company sources, or personal interviews.13-2051 | 0.064422.1 |
Draw charts and graphs, using computer spreadsheets, to illustrate technical reports.13-2051 | 0.059420.4 |
Interpret data on price, yield, stability, future investment-risk trends, economic influences, and other factors affecting investment programs.13-2051 | 0.054618.7 |
Inform investment decisions by analyzing financial information to forecast business, industry, or economic conditions.13-2051 | 0.01715.8 |
Evaluate and compare the relative quality of various securities in a given industry.13-2051 | 0.00893.0 |
Recommend investments and investment timing to companies, investment firm staff, or the public.13-2051 | 0.00602.1 |
Prepare plans of action for investment, using financial analyses.13-2051 | 0.00572.0 |
Monitor developments in the fields of industrial technology, business, finance, and economic theory.13-2051 | 0.00471.6 |
Determine the prices at which securities should be syndicated and offered to the public.13-2051 | 0.00270.9 |
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 |
|---|---|
Advise clients on aspects of capitalization, such as amounts, sources, or timing.O*NET Task ID 21579 | 0.5 |
Analyze financial or operational performance of companies facing financial difficulties to identify or recommend remedies.O*NET Task ID 21580 | 0.5 |
Assess companies as investments for clients by examining company facilities.O*NET Task ID 21581 | 0.5 |
Collaborate on projects with other professionals, such as lawyers, accountants, or public relations experts.O*NET Task ID 21582 | 0.5 |
Collaborate with investment bankers to attract new corporate clients.O*NET Task ID 21583 | 0.5 |
Conduct financial analyses related to investments in green construction or green retrofitting projects.O*NET Task ID 21584 | 0.5 |
Confer with clients to restructure debt, refinance debt, or raise new debt.O*NET Task ID 21585 | 0.5 |
Create client presentations of plan details.O*NET Task ID 21586 | 0.5 |
Determine the prices at which securities should be syndicated and offered to the public.O*NET Task ID 21587 | 0.5 |
Draw charts and graphs, using computer spreadsheets, to illustrate technical reports.O*NET Task ID 21589 | 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
Occupation information
この職業に関わる最近の変化
2026年4月: NBER survey of 6,000 executives: 69% use AI but 90% report zero employment impact. Executives predict -0.7% employment decline over next 3 years.
[出典: NBER Working Paper 34836]2026年4月: Brookings 2024 highlights finance as high-exposure AND low-bargaining-power: union representation in the finance sector is around 1%. Financial analysts face productivity tool-driven task change with minimal institutional counterweight.
[出典: Brookings 2024 — Generative AI, the American worker]2026年4月: OpenAI workplace report (Apr 2026): Workplace ChatGPT use is concentrated in financial analyst roles more than almost any other occupation. Junior analysts produce in days what once took weeks; demand shifts toward analysts who validate model outputs.
[出典: OpenAI — ChatGPT Usage and Adoption Patterns at Work (April 2026)]