GIS Specialists
United States · BLS Employment Projections 2024–34 (figures for SOC 15-1299 occupational group)
AI exposure in published research
Figures below are reproduced from external datasets without modification. Where a dataset does not cover this occupation, the value is shown as — rather than as zero.
Data provider: OpenAI · "GPTs are GPTs"
Time basis: 2023 baselineex-ante estimate
Scored against GPT-4-generation capability.
- Human rater basis
- 60.2%
- GPT-4 rater basis
- 59.3%
β = direct exposure (E1) + 0.5 × exposure when tools are available (E2), per the source repository's definition.
29 rated tasks · 29 tasks with β ≥ 0.5 (100.0%)
- Version:
- gh-main-0471612
- License:
- MIT License · Copyright (c) 2024 OpenAI
Data provider: Anthropic Economic Index
Time basis: Published 2026-03-05composite index
- Observed exposure
- 31.1%
Theoretical exposure index weighted by measured Claude usage, per the original report's definition.
256 tasks · usage observed in 106 · mean 37.0%
Data: Anthropic Economic Index — labor_market_impacts, CC-BY, https://huggingface.co/datasets/Anthropic/EconomicIndex
AI Changing Work uses Anthropic Economic Index data under CC-BY; Anthropic does not endorse or sponsor this site or its analyses.
- Version:
- hf-lmi-2026-03
- License:
- CC BY 4.0
- Observation period:
- — (not applicable to this release)
- Model:
- — (not stated by the source)
- Definition source:
- https://www.anthropic.com/research/labor-market-impacts
2023 prediction vs observation-based index published 2026-03-05
One card (GPTs are GPTs) is a 2023 estimate of what AI could theoretically do; the other (Anthropic Economic Index) is built from observed usage and was published on 2026-03-05 — that is its publication date, not the period it observed. They measure different things, so the two figures cannot be added, averaged, or ranked against each other. The older figure is kept here as a baseline for comparison rather than removed.
Caution: the Anthropic figures — observed exposure and task penetration — take the Eloundou β as one of their inputs. The two sides resembling each other is therefore not evidence that the earlier prediction came true; reading it that way is circular reasoning.
The Anthropic figures are measured on Claude users, who are not the whole economy and not the whole workforce.
The mapping of O*NET tasks and occupation codes was performed by AI Changing Work. The source figures themselves were not modified.
These indices are not forecasts. Which point in time each one belongs to is stated on the badge on its card.
Task Breakdown
- Collect and process geospatial data from multiple sources
- Create thematic maps and spatial visualizations
- Perform spatial analysis and geographic modeling
- Develop and maintain GIS databases and geodatabases
- Consult with stakeholders to define spatial analysis requirements
About This Occupation
If you work as a GIS Specialist, AI is reshaping your profession. With an automation risk of 39/100 and overall exposure at 51%, this role faces high transformation. The highest-impact area is collecting and processing geospatial data at 65% automation. This is classified as an 'augment' role. BLS projects +5% growth through 2034. Specialists who combine spatial analysis skills with AI-driven data processing and predictive modeling will be valued.
ISCO-08 classification
Software and Applications Developers and Analysts Not Elsewhere Classified
Indirect mapping — this occupation is linked to the ISCO unit group by a rule-based fallback.
Definition
ILO original text (English)
This unit group covers software and applications developers and analysts not classified elsewhere in Minor Group 251: Software and Applications Developers and Analysts. For instance, the group includes those professionals specializing in quality assurance including software testing.
Definition & vocabulary source
Source: International Labour Organization (ILO) — ISCO-08 Structure
License: ILO CC BY 4.0
Official occupational information
- ONET15-1243.01
Data Warehousing Specialists
Design, model, or implement corporate data warehousing activities. Program and configure warehouses of database information and provide support to warehouse users.
View original - ONET15-1299.01
Web Administrators
Manage web environment design, deployment, development and maintenance activities. Perform testing and quality assurance of web sites and web applications.
View original - ONET15-1299.02
Geographic Information Systems Technologists and Technicians
Assist scientists or related professionals in building, maintaining, modifying, or using geographic information systems (GIS) databases. May also perform some custom application development or provide user support.
View original - ONET15-1299.03
Document Management Specialists
Implement and administer enterprise-wide document management systems and related procedures that allow organizations to capture, store, retrieve, share, and destroy electronic records and documents.
View original - ONET15-1299.08
Computer Systems Engineers/Architects
Design and develop solutions to complex applications problems, system administration issues, or network concerns. Perform systems management and integration functions.
View original - ONET15-1299.09
Information Technology Project Managers
Plan, initiate, and manage information technology (IT) projects. Lead and guide the work of technical staff. Serve as liaison between business and technical aspects of projects. Plan project stages and assess business implications for each stage. Monitor progress to assure deadlines, standards, and cost targets are met.
View original - ONET15-2051.01
Business Intelligence Analysts
Produce financial and market intelligence by querying data repositories and generating periodic reports. Devise methods for identifying data patterns and trends in available information sources.
View original
Frequently Asked Questions
The Anthropic Economic Index puts observed exposure at 31.1%. The OpenAI "GPTs are GPTs" rubric puts occupation-level β at 60.2% under human raters. Both figures are reproduced from published research without modification.
They come from two published datasets: the Anthropic Economic Index (labor_market_impacts, CC BY 4.0) and the OpenAI "GPTs are GPTs" exposure rubric (MIT License, Copyright (c) 2024 OpenAI). AI Changing Work maps them onto O*NET occupation and task codes and does not calculate exposure scores of its own. AI Changing Work uses Anthropic Economic Index data under CC-BY; Anthropic does not endorse or sponsor this site or its analyses.
No. They are a diagnosis of exposure as measured at the time each source dataset was published. AI Changing Work publishes no prediction of future automation or job displacement for this occupation.