Real Estate Agents
Sales & MarketingAI exposure
- Data source: BLSPublished: '26.08
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: '26.03
0.283
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: '25
0.35
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, 61% 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 30 hidden tasks| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Advise clients on market conditions, prices, mortgages, legal requirements, and related matters.41-9022 | 0.0300100.0 | 0.010033.3 |
Inspect condition of premises, and arrange for necessary maintenance or notify owners of maintenance needs.41-9022 | 0.00000.0 | 0.010033.3 |
Interview clients to determine what kinds of properties they are seeking. | —0 | 0.010033.3 |
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