Will AI replace Remote Sensing Scientists and Technologists?
Work in Remote Sensing Scientists and Technologists sits in the in-between: AI reaches some of it (~46% in theory) but is only measured doing about 4% today — part human, part machine.
O*NET-SOC 19-2099
How your 22 core tasks split
Top = what GPT-4 judged AI could speed up. Bottom = how much AI was actually used for these tasks (Anthropic's March 2026 report, usage from Aug & Nov 2025). The gap is the real story.
Back in 2023, GPT-4 judged AI could, in theory, assist with a moderate share of this job's tasks (~46%). By late 2025, real-world AI use had reached about 4% of its task activity (still rare). The gap between that 2023 forecast and today is the real story.
Where this job sits among 738 jobs
Each dot is one of 738 U.S. jobs. Right = AI can do more of it. Up = AI is actually used more.
The signals here line up
Theoretical reach (~46%), real-world use (~4%) and the task-level picture mostly agree — so this read is more reliable than for jobs where the signals contradict each other. Even so, AI-risk estimates shift by model (a 2026 study saw the "high-risk" share swing 2.7%–51.5%), so treat these as directional, not destiny.
See all 22 tasks, ratedBased on real task-level AI scores — click to collapse
- None — AI cannot fully do any core task alone yet.
- Manage or analyze data obtained from remote sensing systems to obtain meaningful results.
- Analyze data acquired from aircraft, satellites, or ground-based platforms, using statistical analysis software, image analysis software, or Geographic Information Systems (GIS).
- Process aerial or satellite imagery to create products such as land cover maps.
- Design or implement strategies for collection, analysis, or display of geographic data.
- Integrate other geospatial data sources into projects.
- Develop or build databases for remote sensing or related geospatial project information.
- Collect supporting data, such as climatic or field survey data, to corroborate remote sensing data analyses.
- Prepare or deliver reports or presentations of geospatial project information.
- Organize and maintain geospatial data and associated documentation.
- Conduct research into the application or enhancement of remote sensing technology.
- Train technicians in the use of remote sensing technology.
- Attend meetings or seminars or read current literature to maintain knowledge of developments in the field of remote sensing.
- Apply remote sensing data or techniques, such as surface water modeling or dust cloud detection, to address environmental issues.
- Develop automated routines to correct for the presence of image distorting artifacts, such as ground vegetation.
- Monitor quality of remote sensing data collection operations to determine if procedural or equipment changes are necessary.
- Develop new analytical techniques or sensor systems.
- Compile and format image data to increase its usefulness.
- Set up or maintain remote sensing data collection systems.
- Use remote sensing data for forest or carbon tracking activities to assess the impact of environmental change.
- Direct all activity associated with implementation, operation, or enhancement of remote sensing hardware or software.
- Discuss project goals, equipment requirements, or methodologies with colleagues or team members.
- Participate in fieldwork.
How we measured this — and how fresh it is
AI's theoretical reach data: 2023
From GPTs-are-GPTs (Eloundou et al.), where GPT-4 rated how much of each task an AI tool could meaningfully speed up. This is the most recent open, commercially-usable occupation-level potential dataset — it dates to 2023. Newer multi-model re-runs exist but swing wildly (one 2026 study saw "high-risk" jobs range 2.7%–51.5% by model) and aren't openly licensed, so we show the stable 2023 baseline and pair it with newer real-world data.
Real-world AI use 2026 report
From the Anthropic Economic Index, which observes how real Claude conversations map onto each occupation's tasks. Published in Anthropic's March 2026 labor-market report, based on usage measured in Aug & Nov 2025 (Sonnet 4 / 4.5).
Task list & ratings O*NET 30.3
Tasks come from O*NET 30.3. Each task's "AI can do / speeds up / still on you" tier uses the real task-level exposure scores from GPTs-are-GPTs (E1 / E2 / E0) — not a guess from keywords.
Sources: O*NET 30.3 (CC BY 4.0) · GPTs-are-GPTs (MIT, 2023) · Anthropic Economic Index (CC BY, Aug & Nov 2025). Page compiled June 2026. "O*NET" is a trademark of the U.S. Department of Labor.
This page is for general informational purposes only and is not career, financial, or employment advice. AI exposure reflects research estimates of task overlap, not predictions about any individual's job, employer, or future employment.