Property Appraisers and Assessors
Business & Financial OperationsUnited States · BLS Employment Projections 2025–35: this SOC code is not among the published items.
AI exposure
- Data source: ILOPublished: 2025
0.45
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, 25% score at or above this value.
- Data source: OpenAIPublished: 2023
0.464
0.000Range of values carried here0.844Scale, basis and source
Task-level exposure
Show 27 hidden tasks| Task | Claude.aiRaw / share % | APIRaw / share % |
|---|---|---|
Prepare written reports that estimate property values, outline methods by which the estimations were made, and meet appraisal standards.13-2021 | 0.008029.5 | 0.00459.3 |
Maintain familiarity with aspects of local real estate markets.13-2021 | 0.004516.6 | 0.012024.8 |
Analyze trends in sales prices, construction costs, and rents, to assess property values or determine the accuracy of assessments.13-2021 | 0.004014.8 | 0.00398.1 |
Examine income records and operating costs of income properties.13-2021 | 0.00259.2 | 0.008417.4 |
Inspect properties to evaluate construction, condition, special features, and functional design, and to take property measurements.13-2021 | 0.00248.9 | 0.005611.5 |
Search public records for transactions such as sales, leases, and assessments.13-2021 | 0.00238.5 | 0.011924.6 |
Examine the type and location of nearby services, such as shopping centers, schools, parks, and other neighborhood features, to evaluate their impact on property values.13-2021 | 0.00186.6 | —0 |
Evaluate land and neighborhoods where properties are situated, considering locations and trends or impending changes that could influence future values.13-2021 | 0.00165.9 | —0 |
Collect and analyze relevant data to identify real estate market trends. | —0 | 0.00214.2 |
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 |
|---|---|
Calculate tax bills for properties by multiplying assessed values by jurisdiction tax rates.O*NET Task ID 21575 | 1.0 |
Compute final estimation of property values, taking into account such factors as depreciation, replacement costs, value comparisons of similar properties, and income potential.O*NET Task ID 21549 | 0.5 |
Prepare written reports that estimate property values, outline methods by which the estimations were made, and meet appraisal standards.O*NET Task ID 21550 | 0.5 |
Inspect new construction and major improvements to existing structures to determine values.O*NET Task ID 21551 | 0.5 |
Collect and analyze relevant data to identify real estate market trends.O*NET Task ID 21552 | 0.5 |
Prepare and maintain current data on each parcel assessed, including maps of boundaries, inventories of land and structures, property characteristics, and any applicable exemptions.O*NET Task ID 21553 | 0.5 |
Explain assessed values to property owners and defend appealed assessments at public hearings.O*NET Task ID 21554 | 0.5 |
Identify the ownership of each piece of taxable property.O*NET Task ID 21555 | 0.5 |
Inspect properties, considering factors such as market value, location, and building or replacement costs to determine appraisal value.O*NET Task ID 21556 | 0.5 |
Complete and maintain assessment rolls that show the assessed values and status of all property in a municipality.O*NET Task ID 21557 | 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