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STRATUSWORKFORCE SCAN

Cartographers and Photogrammetrists

In short: today's best AI models could do about 78% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about 98% by the end of 2028 if progress keeps its long-run pace. The people and hands-on work, about 2% of the time, stays with people.

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Research, study, and prepare maps and other spatial data in digital or graphic form for one or more purposes, such as legal, social, political, educational, and design purposes. May work with Geographic Information Systems (GIS). May design and evaluate algorithms, data structures, and user interfaces for GIS and mapping systems. May collect, analyze, and interpret geographic information provided by geodetic surveys, aerial photographs, and satellite data.

14,260 people do this job in the US. $81,390 a year.

A typical 40-hour week

Not yet reviewed task by task
  • AI could take on31 h
  • A person checks AI's work0 h
  • Desk work AI can't do yet8 h
  • Stays with people1 h

Cartographers and Photogrammetrists, now: of a 40-hour week, AI could take on 31 hours, 0 hours become checking its work, 8 hours are desk work it can't do yet, and 1 hours stay with people.

The largest pieces: Compile data required for map preparation, including aerial photographs, survey notes, records, reports, and original maps (about 4 h); Determine map content and layout, as well as production specifications such as scale, size, projection, and colors, and direct production to ensure that specifications are followed (about 3 h); Examine and analyze data from ground surveys, reports, aerial photographs, and satellite images to prepare topographic maps, aerial-photograph mosaics, and related charts (about 3 h).

Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.

now
78%

of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.

Kinds of work
  • 98%
  • 0%
  • 2%
8%

of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.

Half the desk work within reach
Already

On the chosen pace and reliability. Estimate.

Share of the working time within reach, now to 2030

0%25%50%75%100%2027202820292030NowDesk work: 98% of the time
Chosen to Ceiling: the share
DateNow
NowEnd of 2030
Change assumptionsLong-run pace, four in five

What each choice means: , , , , . Every pace starts from .

At this date and pace, models finish tasks up to 2.4 work days long four times in five.

How far this has come

With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 0%. With Claude Mythos Preview (early), measured in April 2026, 11%. Today's estimate: 78%.

0%25%50%75%100%2023202420252026GPT-4, March 2023: 0% within reachGPT-4 Turbo (Nov 2023), November 2023: 0% within reachGPT-4o, May 2024: 0% within reachClaude 3.5 Sonnet (June 2024), June 2024: 0% within reacho1-preview, September 2024: 0% within reachClaude 3.5 Sonnet (Oct 2024), October 2024: 0% within reacho1, December 2024: 0% within reachClaude 3.7 Sonnet, February 2025: 0% within reacho3, April 2025: 0% within reachGPT-5, August 2025: 0% within reachGemini 3 Pro, November 2025: 1% within reachClaude Opus 4.5, November 2025: 1% within reachGPT-5.2, December 2025: 1% within reachClaude Opus 4.6, February 2026: 1% within reachClaude Mythos Preview (early), April 2026: 11% within reachToday (estimate), November 2026: 78% within reach
Each step is a new best model measured by METR, four in five; the dashed end is today's estimate. Point at a dot for the model.

A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.

Measured use over time

Of the Claude.ai conversations Anthropic sampled and tied to a work task, 0.011% went to this job's tasks in May 2026, the 359th largest of the 447 jobs that showed up at all; 1 of its 14 tasks showed up. Within each of Anthropic's methods, never across a change: 0.027% to 0.017% (released February and March 2025); 0.0085% to 0.01% (August 2025 to February 2026); 0.011% to 0.011% (April to May 2026).

0%0.025%0.05%20252026released February 2025: 0.027%released March 2025: 0.017%the week of Aug 4, 2025: 0.0085%the week of Nov 13, 2025: 0.011%the week of Feb 5, 2026: 0.01%April 2026: 0.011%May 2026: 0.011%
Each dot is one release's sample. A line joins releases made by the same method; a change of method starts a new line. Point at a dot for its window.
Each release
ConversationsShareRankTasks seen
Released February 20250.027%396 of 7083 of 14
Released March 20250.017%444 of 7033 of 14
The week of Aug 4, 20250.0085%472 of 6552 of 14
The week of Nov 13, 20250.011%460 of 6723 of 14
The week of Feb 5, 20260.01%494 of 6773 of 14
April 20260.011%344 of 4341 of 14
May 20260.011%359 of 4471 of 14

Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.

Robots and the physical work

Anthropic rates 1% of this job's working time as physical work. For 1% of the working time, a robot has been shown doing most of the task somewhere: 1% in any setting. 0.04 of 3, the 594th highest of the 923 jobs.

  • Not physical 99%
  • In any setting 1%

Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.

The tasks

Sorted by . 14 tasks from .

TaskKind
Compile data required for map preparation, including aerial photographs, survey notes, records, reports, and original maps.Done hourly or more by most who do it. 10%3.3 h50 min to 6.7 h91%Half by now
Delineate aerial photographic detail, such as control points, hydrography, topography, and cultural features, using precision stereoplotting apparatus or drafting instruments.Done hourly or more by most who do it. 10%6.7 h1.7 h to 1.7 work days69%Half by now
Prepare and alter trace maps, charts, tables, detailed drawings, and three-dimensional optical models of terrain using stereoscopic plotting and computer graphics equipment.Done hourly or more by most who do it. 10%6.7 h1.7 h to 2.1 work days61%Half by now
Collect information about specific features of the Earth, using aerial photography and other digital remote sensing techniques.Done hourly or more by most who do it. 10%6.7 h1.7 h to 2.1 work days61%Half by now
Examine and analyze data from ground surveys, reports, aerial photographs, and satellite images to prepare topographic maps, aerial-photograph mosaics, and related charts.Done more than monthly by most who do it. 10%6.7 h3.3 h to 2.5 work days80%Half by now
Determine map content and layout, as well as production specifications such as scale, size, projection, and colors, and direct production to ensure that specifications are followed.Done daily by most who do it. 10%5 h1.7 h to 1.3 work days89%Half by now
Revise existing maps and charts, making all necessary corrections and adjustments.Done more than monthly by most who do it. 9%3.3 h50 min to 1.3 work days80%Half by now
Study legal records to establish boundaries of local, national, and international properties.Done several times a day by most who do it. 8%5 h1.7 h to 1.3 work days89%Half by now
Identify, scale, and orient geodetic points, elevations, and other planimetric or topographic features, applying standard mathematical formulas.Done daily by most who do it. 7%3.3 h50 min to 1 work day86%Half by now
Build and update digital databases.Done more than monthly by most who do it. AI observed on this task.4%3.3 h1.7 h to 2.1 work days86%Half by now
Inspect final compositions to ensure completeness and accuracy.Done daily by most who do it. 4%1.7 h25 min to 4.2 h97%Half by now
Select aerial photographic and remote sensing techniques and plotting equipment needed to meet required standards of accuracy.Done more than yearly by most who do it.4%3.3 h50 min to 6.7 h91%Half by now

Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach.

Jobs that share skills with this one

From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.

Where this job works

The industry groups that employ the most of it (BLS, May 2025).

Where the most of these jobs are

The metro areas with the most people in it (BLS, May 2025).

Questions about this job

How much of the work of Cartographers and Photogrammetrists is within reach of AI now?
An estimated 78% of the working time is within reach of AI models now and 98% by the end of 2028, on METR's long-run pace at four in five. Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
Which tasks of Cartographers and Photogrammetrists come within reach first?
Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Compile data required for map preparation, including aerial photographs, survey notes, records, reports, and original maps (91% of the task's time now, 100% by the end of 2028); Determine map content and layout, as well as production specifications such as scale, size, projection, and colors, and direct production to ensure that specifications are followed (89% of the task's time now, 100% by the end of 2028); and Examine and analyze data from ground surveys, reports, aerial photographs, and satellite images to prepare topographic maps, aerial-photograph mosaics, and related charts (80% of the task's time now, 100% by the end of 2028).
Which tasks of Cartographers and Photogrammetrists stay with people?
Tasks that are people work or body work are not counted as within reach at any date. The largest: Travel over photographed areas to observe, identify, record, and verify all relevant features. Together such tasks are about 2% of the working time.
Do people already use AI for the work of Cartographers and Photogrammetrists?
In the Claude.ai conversations Anthropic sampled for May 2026 and tied to a work task, 0.011% went to this job's tasks, the 359th largest share of the 447 jobs that showed up; 1 of its 14 tasks appeared. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 8%. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
Can robots do the physical work of Cartographers and Photogrammetrists?
Anthropic's robot exposure rating (September 2026) finds 1% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 1% of the working time, 1% in any setting. Its index is 0.04 of 3. One example: Waymo Driver (autonomous vehicle fleet with automated map-change detection) for "travel over photographed areas to observe, identify, record, and verify all relevant features". A robot shown somewhere is not one in every workplace; this site's own estimates still count no physical work as within reach.
How is this estimated?
From the 14 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, each classed as desk, people or body work, and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.

How the estimates are made

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