Investment Bankers
Business & Financial OperationsAI exposure
- Data source: BLSPublished: 2026-08
Very high· relative
LowFour relative bandsVery highGroup-level value
Scale, basis and source
Four relative bands (Low / Moderate / High / Very high)
831 detailed occupations in the BLS Employment Projections table. Assigned per National Employment Matrix (NEM) code, so occupations sharing a NEM code carry the same band
- Data source: AnthropicPublished: 2026-03
0.572
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: 2025
0.62
0.09Range of values carried here0.70Group-level value
Scale, basis and source
Generative AI exposure index, 0–1 as published
ISCO-08 unit group — every occupation sharing the code gets this value
Computed by this site, not published by the ILO: of the 1,012 occupations this site links to the ILO dataset, 3% score at or above this value.
What kind of figure this source publishes
The BLS category is a relative rank, not an absolute level, and it is not a first-hand measurement: it groups an occupation's percentile ranks across several published studies into four bands. It is not an employment or wage forecast, not a probability of adoption, and it does not separate automation from augmentation.
Task-level exposure
Exposed tasks only| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Inform investment decisions by analyzing financial information to forecast business, industry, or economic conditions.13-2051 | 0.051536.8 | 0.072441.7 |
Interpret data on price, yield, stability, future investment-risk trends, economic influences, and other factors affecting investment programs.13-2051 | 0.027019.2 | 0.047127.2 |
Recommend investments and investment timing to companies, investment firm staff, or the public.13-2051 | 0.021615.4 | 0.022012.7 |
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 | 0.01188.4 | 0.01327.6 |
Draw charts and graphs, using computer spreadsheets, to illustrate technical reports.13-2051 | 0.01057.5 | 0.00412.4 |
Present oral or written reports on general economic trends, individual corporations, and entire industries.13-2051 | 0.00846.0 | 0.00744.3 |
Evaluate and compare the relative quality of various securities in a given industry.13-2051 | 0.00745.3 | 0.00724.1 |
Prepare plans of action for investment, using financial analyses.13-2051 | 0.00211.5 | —0 |
| Not observed on any surface — 10 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. | ||
Monitor developments in the fields of industrial technology, business, finance, and economic theory. | —0 | —0 |
Determine the prices at which securities should be syndicated and offered to the public. | —0 | —0 |
Contact brokers and purchase investments for companies, according to company policy. | —0 | —0 |
Collaborate with investment bankers to attract new corporate clients to securities firms. | —0 | —0 |
Conduct financial analyses related to investments in green construction or green retrofitting projects. | —0 | —0 |
Determine the financial viability of alternative energy generation or fuel production systems, based on power source or feedstock quality, financing costs, potential revenue, and total project costs. | —0 | —0 |
Evaluate financial viability and potential environmental benefits of cleantech innovations to secure capital investments from sources such as venture capital firms and government green fund grants. | —0 | —0 |
Forecast or analyze financial costs associated with climate change or other environmental factors, such as clean water supply and demand. | —0 | —0 |
Identify potential financial investments that are environmentally sound, considering issues such as carbon emissions and biodiversity. | —0 | —0 |
Research and recommend environmentally-related financial products, such as energy futures, water rights, carbon credits, government environmental funds, and cleantech industry funds and company stocks. | —0 | —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 |
|---|---|
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 |
Develop and maintain client relationships.O*NET Task ID 21588 | 0.0 |
Supervise, train, or mentor junior team members.O*NET Task ID 21604 | 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
Recent Changes Related to This Occupation
Oct 2024: 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.
[Source: Brookings 2024 — Generative AI, the American worker]These summaries were written by AI Changing Work from the source linked with each one, and any figures in them are given as AI Changing Work summarised them; they can differ from the source's own wording and from figures shown elsewhere on this page, so check the source before relying on them. AI Changing Work matched this page's occupation to an O*NET occupation and chose, by its own judgment, case by case, which summaries relate to that O*NET occupation; a summary appearing here does not mean that its source names this occupation.