Share and intensity of work current AI systems can materially affect.
SOC 17-1021
Cartographers and Photogrammetrists AI displacement risk
Cartographers compile aerial imagery, survey notes, and satellite data into maps, and automated generalization now drafts much of that compilation. AI feature extraction from imagery is genuinely good, so the role is shifting toward database design, accuracy verification, and editorial judgment about what a map should say.
Likely potential for exposed tasks to move to software after workflow integration.
This is one of the honest moderate-exposure geospatial roles: routine map production is increasingly automated. What persists is geodetic rigor, legal-boundary work, and accountability for maps that navigation, defense, and land-title systems depend on.
Distribution
Where Cartographers and Photogrammetrists sits across 620 tracked roles
Displacement pressure 52 — higher than 81% of the 620 occupations tracked on displacement.ai.
Score version
This page uses Seed model v0.4 (seed-v0.4-2026-05), last reviewed 2026-08-15. Directional occupation-level planning model using hand-reviewed public research, task exposure estimates, wage context, and transition-pathway assumptions.
14 O*NET task statements matched to SOC 17-1021. The displayed task profile combines these official task statements with the current public score model.
Median wage context: $81,390 (May 2025, US national). The latest BLS row matched SOC 17-1021.
Scores are planning signals, not forecasts. Local hiring demand, employer-specific workflows, licensing, and credentials must be validated before making career decisions.
2030 economic stress test
How Anthropic's scenarios classify Cartographers and Photogrammetrists
SOC 17-1021 places this role in the paper's cognitive occupation group. These group-level outcomes do not change the 52/100 role score and are not an occupation forecast.
+0.4% group wage
-0.5% cognitive employment since mid-2026; 2.9% cognitive unemployment.
Economy-wide: +1.6% GDP and 3.9% unemployment.
-0.3% group wage
-3.9% cognitive employment since mid-2026; 4.5% cognitive unemployment.
Economy-wide: +8.3% GDP and 4.6% unemployment.
-11.5% group wage
-21.5% cognitive employment since mid-2026; 17.9% cognitive unemployment.
Economy-wide: +32.4% GDP and 11.9% unemployment.
Compare the assumptions and limitations across all three scenarios. Source: The Anthropic Institute Working Paper No. 2026-02.
Official task evidence
O*NET task matches for Cartographers and Photogrammetrists
The current evidence import matched 14 task statements from Task Statements 31.0 (August 2026). These rows are used as a grounding layer for judging which parts of the occupation are repeatable, language-heavy, analytical, social, physical, or compliance-sensitive.
Dataset31.0 (August 2026)
Matched tasks14
SOC17-1021
- Core task / ID 3517
Compile data required for map preparation, including aerial photographs, survey notes, records, reports, and original maps.
- Core task / ID 3522
Delineate aerial photographic detail, such as control points, hydrography, topography, and cultural features, using precision stereoplotting apparatus or drafting instruments.
- Core task / ID 3524
Prepare and alter trace maps, charts, tables, detailed drawings, and three-dimensional optical models of terrain using stereoscopic plotting and computer graphics equipment.
- Core task / ID 3526
Study legal records to establish boundaries of local, national, and international properties.
- Core task / ID 3518
Inspect final compositions to ensure completeness and accuracy.
- Core task / ID 3516
Revise existing maps and charts, making all necessary corrections and adjustments.
Source: O*NET Resource Center, Task Statements. Raw import target: data/raw/onet/task-statements-31-0.txt.
Task profile
Where AI changes the work
Compile data required for map preparation
Exposure 70, automation 46%, augmentation 62%.
O*NET evidence: Compile data required for map preparation, including aerial photographs, survey notes, ... (ID 3517)
Examine surveys, aerial photos, and satellite images
Exposure 64, automation 40%, augmentation 66%.
O*NET evidence: Examine and analyze data from ground surveys, reports, aerial photographs, and satellit... (ID 3520)
Inspect final compositions for completeness and accuracy
Exposure 52, automation 26%, augmentation 62%.
O*NET evidence: Inspect final compositions to ensure completeness and accuracy. (ID 3518)
Build and update digital databases
Exposure 58, automation 30%, augmentation 64%.
O*NET evidence: Build and update digital databases. (ID 3523)
TaskExposureAutomationAugmentation
Compile data required for map preparation7046%62%
Examine surveys, aerial photos, and satellite images6440%66%
Inspect final compositions for completeness and accuracy5226%62%
Build and update digital databases5830%64%
Transition pathways
Adjacent moves that preserve existing skills
role redesign
ModerateGIS Analyst
Training horizon: 3-6 months. Skill overlap 72. Wage preservation signal 104.
- Own spatial analysis projects
- Automate data pipelines
- Serve internal map clients
credentialed transition
ModerateGeospatial Data Engineer
Training horizon: 12-24 months. Skill overlap 56. Wage preservation signal 128.
- Learn cloud geospatial tooling
- Build ETL for imagery
- Add scripting to production work
Comparison guides
Compare the next move before you commit
3-6 months
Cartographers and Photogrammetrists to GIS Analyst
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Cartographers and Photogrammetrists into GIS Analyst.
12-24 months
Cartographers and Photogrammetrists to Geospatial Data Engineer
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Cartographers and Photogrammetrists into Geospatial Data Engineer.
What the AI risk score means for Cartographers and Photogrammetrists
The displacement pressure score for Cartographers and Photogrammetrists is 52. That score blends task exposure, automation pressure, augmentation potential, wage vulnerability, transition feasibility, and source confidence. It is designed to help workers and workforce teams decide where to act first, not to claim a specific date when a job will disappear.
For this role, the clearest risk pattern is visible at the task level. Compile data required for map preparation carries 46% automation pressure, while Examine surveys, aerial photos, and satellite images carries 66% augmentation potential. That means the best response is usually a targeted redesign of work: move away from repeatable production tasks and toward judgment, exception handling, coordination, stakeholder context, and accountable use of AI tools.
Labor-market context and wage risk
Median wage: $81,390 (May 2025, US national). Employment context: Mapmaking role transformed by automated generalization. Typical education: Bachelor degree typical.
Wage vulnerability is 36, while transition feasibility is 66. A high wage-vulnerability score means workers should pay close attention to salary preservation before making a move. A high transition-feasibility score means there are adjacent paths that can reuse existing skills without requiring a complete career reset.
- Moderate displacement pressure
- AI extracts map features from imagery
- Legal-boundary work stays human
Upskilling priorities
Skills that make this role more resilient
The safest upskilling plan starts with skills already close to the work. For Cartographers and Photogrammetrists, the strongest near-term skill priorities are listed below. These are useful whether the goal is to stay in the role, move to a redesigned version of the role, or transition into an adjacent occupation.
GIS data analysis
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Map design
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Accuracy verification
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Geospatial databases
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
90-day transition plan
The most practical next step is not to wait for a layoff or a full role redesign. Use the next 90 days to create evidence that you can operate in a safer, more AI-augmented version of the work.
- In the first 30 days, document the repetitive tasks in your current work and identify where AI can reduce drafting, lookup, classification, or reporting time.
- By 60 days, complete one small project connected to GIS Analyst, such as own spatial analysis projects.
- By 90 days, compare internal openings and external postings for GIS Analyst or Geospatial Data Engineer and update your resume around measurable workflow outcomes.
FAQ
Questions about AI and Cartographers and Photogrammetrists
Will AI replace Cartographers and Photogrammetrists?
Cartographers compile aerial imagery, survey notes, and satellite data into maps, and automated generalization now drafts much of that compilation. AI feature extraction from imagery is genuinely good, so the role is shifting toward database design, accuracy verification, and editorial judgment about what a map should say. The better planning signal is not full replacement, but which tasks become automated, which tasks become AI-assisted, and which responsibilities still need human judgment.
Which parts of Cartographers and Photogrammetrists work are most exposed to AI?
Compile data required for map preparation and Examine surveys, aerial photos, and satellite images show the strongest automation pressure in this model. Examine surveys, aerial photos, and satellite images and Build and update digital databases are better treated as AI-augmented work.
What should Cartographers and Photogrammetrists learn next?
Start with GIS data analysis, Map design, Accuracy verification. The most practical adjacent paths in this model are GIS Analyst and Geospatial Data Engineer.
How should this score be used?
Use it as a planning signal, not a prediction. Confirm local hiring demand, wages, licensing, credentials, and employer adoption before making a career move.
Sources
Evidence trail
International Labour Organization / 20 May 2025Generative AI and Jobs: A Refined Global Index of Occupational ExposureOECD / 11 July 2023OECD Employment Outlook 2023: Artificial Intelligence and the Labour MarketO*NET Resource Center / Database 31.0 (August 2026)Occupation, Task, Skill, and Work-Activity DataUS Bureau of Labor Statistics / May 2025 estimates (released 15 May 2026)Occupational Employment and Wage Statistics