Geospatial Information Technologists
Overall Exposure
2025 vs 2023
Theoretical Exposure
76What AI could do
Observed Exposure
44What AI actually does
Automation Risk Score
29Displacement risk
3-Year Outlook (2025 โ 2028)
Projected changes in AI automation metrics over the next 3 years based on estimated data.
Overall Exposure
2025 โ 2028 (estimated)
Theoretical Exposure
2025 โ 2028 (estimated)
Observed Exposure
2025 โ 2028 (estimated)
Automation Risk
2025 โ 2028 (estimated)
Exposure Metrics (2023 - 2028)
Detailed Metrics Table
| Year | Overall | Theoretical | Observed | Risk | Data Type |
|---|---|---|---|---|---|
| 2024 | 55 | 72 | 38 | 25 | actual |
| 2025 | 60 | 76 | 44 | 29 | estimated |
| 2026 | 65 | 80 | 50 | 33 | estimated |
| 2027 | 69 | 83 | 55 | 37 | estimated |
| 2028 | 73 | 86 | 60 | 41 | estimated |
Task Breakdown
About This Occupation
If you work as a Geospatial Information Technologist, AI is augmenting your spatial analysis and data processing capabilities. With an automation risk of 29/100 and overall exposure at 60%, this role sees high transformation. Satellite imagery processing is 70% automated while database design remains at 42%. BLS projects +5% growth through 2034.
Frequently Asked Questions
With an automation risk score of 29%, Geospatial Information Technologists has a low risk of AI replacement. Most tasks in this role require skills that are difficult for AI to replicate, such as complex decision-making, physical dexterity, or deep interpersonal interaction. AI is more likely to serve as a supportive tool.
The AI automation risk score for Geospatial Information Technologists is 29% (2025 data). Overall AI exposure is 60%, with 76% theoretical exposure and 44% observed exposure. The risk trend from 2023 to 2025 is 0 points.
The tasks with the highest automation potential for Geospatial Information Technologists are: Process and analyze satellite imagery and remote sensing data (70%), Develop custom geospatial applications and visualization tools (52%), Design and manage spatial databases and geodata infrastructure (42%). These rates reflect how much of each task current AI systems can handle, based on research data from Anthropic and academic sources.
The BLS projects +5% employment change for Geospatial Information Technologists from 2024 to 2034. Combined with an overall AI exposure of 60%, this occupation is experiencing both traditional labor market shifts and AI-driven transformation. Workers should monitor both employment trends and AI capability growth.
Since AI primarily augments capabilities in this role, professionals in Geospatial Information Technologists should embrace AI as a productivity multiplier. Focus on learning to use AI tools effectively, developing higher-order analytical and creative skills, and positioning yourself as someone who can leverage AI to deliver greater value.