Commodities Traders
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
0.441
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: 2025
0.63
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, 2% 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
Show 18 hidden tasks| Task | Claude.aiRaw / share % |
|---|---|
Explain stock market terms or trading practices to clients.41-3031 | 0.110221.7 |
Analyze market conditions to determine optimum times to execute securities transactions.41-3031 | 0.058911.6 |
Analyze target companies or investment opportunities to inform investment decisions.41-3031 | 0.052510.3 |
Devise trading, option, or hedge strategies.41-3031 | 0.03617.1 |
Track and analyze factors that affect price movement, such as trade policies, weather conditions, political developments, or supply and demand changes.41-3031 | 0.02975.9 |
Prepare documents needed to implement plans selected by clients.41-3031 | 0.01983.9 |
Contact prospective customers to determine customer needs, present information, or explain available services.41-3031 | 0.01943.8 |
Contact prospective customers to present information and explain available services.41-3031 | 0.01893.7 |
Inform other traders, managers, or customers of market conditions, including volume, price, competition, or dynamics.41-3031 | 0.01763.5 |
Offer advice on the purchase or sale of particular securities.41-3031 | 0.01713.4 |
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 |
|---|---|
Keep accurate records of transactions.O*NET Task ID 23195 | 1.0 |
Complete sales order tickets and submit for processing of client-requested transactions.O*NET Task ID 23197 | 1.0 |
Report all positions or trading results.O*NET Task ID 23198 | 1.0 |
Explain stock market terms or trading practices to clients.O*NET Task ID 23212 | 1.0 |
Calculate costs for billings or commissions.O*NET Task ID 23213 | 1.0 |
Prepare and send requests for price quotations to all companies in a particular market.O*NET Task ID 23219 | 1.0 |
Make bids or offers to buy or sell securities.O*NET Task ID 23192 | 0.5 |
Monitor markets or positions.O*NET Task ID 23193 | 0.5 |
Agree on buying or selling prices at optimal levels for clients.O*NET Task ID 23194 | 0.5 |
Buy or sell stocks, bonds, commodity futures, foreign currencies, or other securities on behalf of investment dealers.O*NET Task ID 23196 | 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