Share and intensity of work current AI systems can materially affect.
SOC 19-4042
Environmental Science Technicians AI displacement risk
Environmental science and protection technicians collect air, soil, and water samples, run pollutant tests, and document hazardous conditions. Continuous monitoring stations automate routine readings, but regulated chain-of-custody sampling, spill investigation, and field inspection stay physical and accountability-bound.
Likely potential for exposed tasks to move to software after workflow integration.
Sensor networks change where technicians spend time: more deployment and data QA, fewer manual rounds. Contamination events and enforcement cases require defensible samples collected by a person who can testify to the process.
Distribution
Where Environmental Science Technicians sits across 620 tracked roles
Displacement pressure 38 — higher than 65% of the 620 occupations tracked on displacement.ai.
Score version
This page uses Seed model v0.4 (seed-v0.4-2026-05), last reviewed 2026-08-15. Directional occupation-level planning model using hand-reviewed public research, task exposure estimates, wage context, and transition-pathway assumptions.
25 O*NET task statements matched to SOC 19-4042. The displayed task profile combines these official task statements with the current public score model.
Median wage context: $55,090 (May 2025, US national). The latest BLS row matched SOC 19-4042.
Scores are planning signals, not forecasts. Local hiring demand, employer-specific workflows, licensing, and credentials must be validated before making career decisions.
2030 economic stress test
How Anthropic's scenarios classify Environmental Science Technicians
SOC 19-4042 places this role in the paper's cognitive occupation group. These group-level outcomes do not change the 38/100 role score and are not an occupation forecast.
+0.4% group wage
-0.5% cognitive employment since mid-2026; 2.9% cognitive unemployment.
Economy-wide: +1.6% GDP and 3.9% unemployment.
-0.3% group wage
-3.9% cognitive employment since mid-2026; 4.5% cognitive unemployment.
Economy-wide: +8.3% GDP and 4.6% unemployment.
-11.5% group wage
-21.5% cognitive employment since mid-2026; 17.9% cognitive unemployment.
Economy-wide: +32.4% GDP and 11.9% unemployment.
Compare the assumptions and limitations across all three scenarios. Source: The Anthropic Institute Working Paper No. 2026-02.
Official task evidence
O*NET task matches for Environmental Science Technicians
The current evidence import matched 25 task statements from Task Statements 31.0 (August 2026). These rows are used as a grounding layer for judging which parts of the occupation are repeatable, language-heavy, analytical, social, physical, or compliance-sensitive.
Dataset31.0 (August 2026)
Matched tasks25
SOC19-4042
- Core task / ID 1550
Collect samples of gases, soils, water, industrial wastewater, or asbestos products to conduct tests on pollutant levels or identify sources of pollution.
- Core task / ID 20869
Investigate hazardous conditions or spills or outbreaks of disease or food poisoning, collecting samples for analysis.
- Core task / ID 1549
Record test data and prepare reports, summaries, or charts that interpret test results.
- Core task / ID 1556
Prepare samples or photomicrographs for testing and analysis.
- Core task / ID 1560
Discuss test results and analyses with customers.
- Core task / ID 1565
Inspect workplaces to ensure the absence of health and safety hazards, such as high noise levels, radiation, or potential lighting hazards.
Source: O*NET Resource Center, Task Statements. Raw import target: data/raw/onet/task-statements-31-0.txt.
Task profile
Where AI changes the work
Collect samples of gases, soils, and water
Exposure 36, automation 16%, augmentation 52%.
O*NET evidence: Collect samples of gases, soils, water, industrial wastewater, or asbestos products to ... (ID 1550)
Record test data and prepare reports
Exposure 58, automation 32%, augmentation 66%.
O*NET evidence: Record test data and prepare reports, summaries, or charts that interpret test results. (ID 1549)
Set up stations to monitor pollutants
Exposure 40, automation 20%, augmentation 52%.
O*NET evidence: Set up equipment or stations to monitor and collect pollutants from sites, such as smok... (ID 1563)
Investigate hazardous conditions and spills
Exposure 28, automation 10%, augmentation 48%.
O*NET evidence: Investigate hazardous conditions or spills or outbreaks of disease or food poisoning, c... (ID 20869)
TaskExposureAutomationAugmentation
Collect samples of gases, soils, and water3616%52%
Record test data and prepare reports5832%66%
Set up stations to monitor pollutants4020%52%
Investigate hazardous conditions and spills2810%48%
Transition pathways
Adjacent moves that preserve existing skills
role redesign
ModerateEnvironmental Health Specialist
Training horizon: 3-6 months. Skill overlap 66. Wage preservation signal 114.
- Own inspection programs
- Manage monitoring networks
- Write enforcement-ready reports
credentialed transition
ModerateEnvironmental Scientist
Training horizon: 24-36 months. Skill overlap 58. Wage preservation signal 142.
- Complete a science degree
- Lead remediation studies
- Master regulatory frameworks
Comparison guides
Compare the next move before you commit
3-6 months
Environmental Science Technicians to Environmental Health Specialist
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Environmental Science Technicians into Environmental Health Specialist.
24-36 months
Environmental Science Technicians to Environmental Scientist
Compare AI displacement pressure, wage preservation, skill overlap, training time, and first proof project for moving from Environmental Science Technicians into Environmental Scientist.
What the AI risk score means for Environmental Science Technicians
The displacement pressure score for Environmental Science Technicians is 38. That score blends task exposure, automation pressure, augmentation potential, wage vulnerability, transition feasibility, and source confidence. It is designed to help workers and workforce teams decide where to act first, not to claim a specific date when a job will disappear.
For this role, the clearest risk pattern is visible at the task level. Record test data and prepare reports carries 32% automation pressure, while Record test data and prepare reports carries 66% augmentation potential. That means the best response is usually a targeted redesign of work: move away from repeatable production tasks and toward judgment, exception handling, coordination, stakeholder context, and accountable use of AI tools.
Labor-market context and wage risk
Median wage: $55,090 (May 2025, US national). Employment context: Pollution sampling role sharing the sensor-network shift. Typical education: Associate degree common.
Wage vulnerability is 56, while transition feasibility is 66. A high wage-vulnerability score means workers should pay close attention to salary preservation before making a move. A high transition-feasibility score means there are adjacent paths that can reuse existing skills without requiring a complete career reset.
- Moderate displacement pressure
- Sensors automate routine readings
- Enforcement sampling stays human
Upskilling priorities
Skills that make this role more resilient
The safest upskilling plan starts with skills already close to the work. For Environmental Science Technicians, the strongest near-term skill priorities are listed below. These are useful whether the goal is to stay in the role, move to a redesigned version of the role, or transition into an adjacent occupation.
Field sampling
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Monitoring equipment
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Laboratory testing
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
Compliance documentation
Build proof of this skill through a work sample, checklist, dashboard, case note, workflow map, or portfolio artifact tied to the transition paths on this page.
90-day transition plan
The most practical next step is not to wait for a layoff or a full role redesign. Use the next 90 days to create evidence that you can operate in a safer, more AI-augmented version of the work.
- In the first 30 days, document the repetitive tasks in your current work and identify where AI can reduce drafting, lookup, classification, or reporting time.
- By 60 days, complete one small project connected to Environmental Health Specialist, such as own inspection programs.
- By 90 days, compare internal openings and external postings for Environmental Health Specialist or Environmental Scientist and update your resume around measurable workflow outcomes.
FAQ
Questions about AI and Environmental Science Technicians
Will AI replace Environmental Science Technicians?
Environmental science and protection technicians collect air, soil, and water samples, run pollutant tests, and document hazardous conditions. Continuous monitoring stations automate routine readings, but regulated chain-of-custody sampling, spill investigation, and field inspection stay physical and accountability-bound. The better planning signal is not full replacement, but which tasks become automated, which tasks become AI-assisted, and which responsibilities still need human judgment.
Which parts of Environmental Science Technicians work are most exposed to AI?
Record test data and prepare reports and Set up stations to monitor pollutants show the strongest automation pressure in this model. Record test data and prepare reports and Collect samples of gases, soils, and water are better treated as AI-augmented work.
What should Environmental Science Technicians learn next?
Start with Field sampling, Monitoring equipment, Laboratory testing. The most practical adjacent paths in this model are Environmental Health Specialist and Environmental Scientist.
How should this score be used?
Use it as a planning signal, not a prediction. Confirm local hiring demand, wages, licensing, credentials, and employer adoption before making a career move.
Sources
Evidence trail
International Labour Organization / 20 May 2025Generative AI and Jobs: A Refined Global Index of Occupational ExposureOECD / 11 July 2023OECD Employment Outlook 2023: Artificial Intelligence and the Labour MarketO*NET Resource Center / Database 31.0 (August 2026)Occupation, Task, Skill, and Work-Activity DataUS Bureau of Labor Statistics / May 2025 estimates (released 15 May 2026)Occupational Employment and Wage Statistics