Cartographers and Surveyors

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 8 task statements that define Cartographers and Surveyors (ISCO-08 2165) score an average of 0.44 on a 0–1 exposure scale — more exposed than about 81% of the 427 placed occupations. Roughly 100% of its tasks fall somewhere on the exposed part of the gradient, and the typical task lands in the Gradient 2 band.

Exposure is task overlap, not a verdict. A high score means a generative-AI model can do part of the content of these tasks — it says nothing about whether the work is automated, whether anyone uses AI for it today, or whether jobs are lost. The gradient is scored on the international ISCO-08 system; the rest of Singulariki is U.S. O*NET/SOC, bridged below by an approximate, many-to-many crosswalk.

How its tasks split across the gradient

Each of the 8 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Noting exact position of various features and recording survey data in digital form;”

Scores 0.60 on the 2025 scale. The task of noting exact positions and recording survey data in digital form involves a combination of physical measurement and digital data entry, similar to tasks involving geodetic instruments and survey research. While Generative AI excels in data processing and preliminary analysis, the physical aspect of capturing precise measurements on-site limits full automation. Semantically similar tasks, such as "Using electronic geodetic instruments" and "Maintaining patient records and medical documentation," received scores of 0.435 and 0.4575, respectively. These scores reflect the moderate potential for AI to assist in digital record-keeping and data processing while human intervention remains critical for accurate measurements and context-specific decisions. Given Poland's high technological access, AI can support data entry and analysis effectively, leading to a balanced score of 0.45, acknowledging AI's supportive role without full automation potential.

Moving fastest, 2023 → 2025

“Designing, compiling and revising maps and charts using aerial and other photographs, satellite imagery, survey documents and data, existing maps and records, reports and statistics;”

Model capability on this task changed by +0.18 in two years — the gradient is not static, it is filling in.

U.S. occupations this maps to

The American O*NET/SOC roles that crosswalk to ISCO-08 2165, biggest by employment first, via the published (approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 correspondence. These are the closest U.S. matches — not an asserted one-to-one identity.

• Surveyors
• Geodetic Surveyors
• Cartographers and Photogrammetrists

In context

Part of the 2 - Professionals major group. Return to the full gradient to see how the whole group sits.

Cartographers and Surveyors sit at the 81st percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Cartographers and Surveyors rank in the 81st percentile for GenAI task exposure — overlap with what generative AI can attempt, not a projection of displacement. (ILO / Gmyrek et al. (2025) GenAI exposure gradient)
• About 100% of this occupation's tasks fall into an exposed gradient band. (ILO / Gmyrek et al. (2025))
• Mean task exposure rose by 0.06 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Noting exact position of various features and recording survey data in digital form;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Cartographers and Surveyors". https://singulariki.com/gradient/2165-cartographers-and-surveyors.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.