JobRiskAI

Geological Technicians, Except Hydrologic Technicians

SOC 19-4043Life, Physical & Social ScienceData vintage 2026-07
Moderate exposure AI applicability score 0.127, higher than 44% of the 785 occupations measured · #42 most exposed of 47 in Life, Physical & Social Science

AI touches this job. It does not define it.

AI meaningfully touches parts of this work, yet the majority of its activities remain outside observed AI usage. That's balanced exposure: real efficiency gains are available without wholesale overlap.

Where this occupation sits among all 785 measured. Bands are quintiles of the real distribution. Applicability measures task overlap with observed AI usage. It is not a probability of job loss.

What this job involves

Assist scientists or engineers in the use of electronic, sonic, or nuclear measuring instruments in laboratory, exploration, and production activities to obtain data indicating resources such as metallic ore, minerals, gas, coal, or petroleum. Analyze mud and drill cuttings. Chart pressure, temperature, and other characteristics of wells or bore holes.

Where AI overlaps this work, activity by activity

The occupation's most important work activities (O*NET weights, normalized to this set), each with its measured AI performance across 200,000 real conversations: how often AI is used for it, how well it completes it, and how much of the activity it covers.

Work activityShare of roleAI performance
Analyze environmental or geospatial data.22.5%Not observed 0.00
Maintain operational records.16.6%Not observed 0.00
Create visual designs or displays.10.6%Emerging 0.20
Collect samples of products or materials.9.6%Not observed 0.00
Gather information from physical or electronic sources.8.7%High overlap 0.65
Adjust equipment to ensure adequate performance.5.6%High overlap 0.67
Maintain electronic, computer, or other technical equipment.5.6%High overlap 0.62
Research issues related to earth sciences.4.5%Moderate 0.52
Supervise personnel activities.4.3%Not observed 0.00
Set up equipment.4.1%High overlap 0.75
Direct scientific or technical activities.4.1%Not observed 0.00
Operate laboratory or field equipment.3.9%Not observed 0.00

"Not observed" is a measurement, not missing data: that activity does not meaningfully appear in the usage sample. AI performance = completion × scope × coverage (user-goal view), 0–1.

What drives this score: the biggest AI-overlapped activity in this role is gather information from physical or electronic sources; the most important activity AI is not observed doing is analyze environmental or geospatial data. The plan below is built around exactly that split.

Balanced exposure: take the gains, deepen the moat.

Next 30 days

  • Harvest the easy wins. Parts of this role, led by Gather information from physical or electronic sources, are already AI-assistable. Claim those hours back this month.
  • Map your own mix. Your split may differ from the occupation average. Run the six-question personalization above and read your range, not the headline.

Next 90 days

  • Invest saved time in the human core. The majority of this occupation's activities show no observed AI usage. Deepen exactly those, starting with Analyze environmental or geospatial data.
  • Stay current, lightly. A monthly hour trying new tools on your real tasks beats panic-learning later.

The longer game

  • Own a niche. Moderate exposure means AI will not define this occupation, but specialists who pair domain depth with tool fluency will out-earn generalists in it.
  • Watch the boundary activities. If the 'Emerging' rows in your table above turn 'High' in a future data update, revisit the plan. No countdown clocks, just recheck.

Compare this occupation with another

Sources for this page:
  • AI applicability score and per-activity metrics: Tomlinson, Jaffe, Wang, Counts & Suri, Working with AI: Measuring the Applicability of Generative AI to Occupations, Microsoft Research 2025 (arXiv:2507.07935), data CC BY 4.0.
  • Occupation description and activity structure: O*NET 30.0 Database, USDOL/ETA, CC BY 4.0.
  • Bands, personalization weights and action plans are JobRiskAI editorial layers; method and limitations on the methodology page.