Mostly Resilient
Last Update: 5/19/2026
AI Resilience Score for Environmental Scientists:
55.2%
Median Score
Meaningful human contribution
Measures the parts of the occupation that still require a human touch. This score averages data from up to four AI exposure datasets, focusing on the role’s resilience against automation.
Med
Long-term employer demand
Predicts the health of the job market for this role through 2034. Using Bureau of Labor Statistics data, it balances projected annual job openings (60%) with overall employment growth (40%).
Med
Sustained economic opportunity
Measures future earning potential and career flexibility. This score is a blend of total projected labor income (67%) and the role’s inherent ability to adapt to economic and technological shifts (33%).
Med
This reflects the reliability of your score based on the number of data sources available for this career and how closely those sources agree on the outlook. A higher confidence means more consistent evidence from labor experts and AI models.
Most data sources align, with only minor variation. This is a well-supported result.
Contributing sources
AI Resilience Report forEnvironmental Scientists and Specialists, Including Health
$80,060 median salary•8,500 annual openings•SOC Code: 19-2041.00
Environmental Scientists and Specialists, Including Health are somewhat more resilient to AI impacts than most occupations, according to our analysis of 7 sources.
Environmental Scientists are labeled "Mostly Resilient" because while AI is genuinely changing parts of the job — like processing sensor data, searching emissions records, and building reports — the most important parts of the work still require a human. Inspections, policy recommendations, community communication, and standing behind your findings in a courtroom or public hearing all demand judgment, accountability, and trust that AI simply can't provide.
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Environmental Scientists are labeled "Mostly Resilient" because while AI is genuinely changing parts of the job — like processing sensor data, searching emissions records, and building reports — the most important parts of the work still require a human. Inspections, policy recommendations, community communication, and standing behind your findings in a courtroom or public hearing all demand judgment, accountability, and trust that AI simply can't provide.
Read full analysisAnalysis of Current AI Resilience
Environmental Scientists
Updated Quarterly
How is AI changing Environmental Scientists jobs?
Right now, AI in environmental science is mostly being used to augment people, not replace them. The clearest example is data work: in March 2026, an AI platform called OpenEPA launched that transforms a decade of EPA Greenhouse Gas Reporting Program data into a searchable layer, letting users perform plain-language queries to generate structured answers about national emissions trends. Every output includes a provenance record so researchers can verify the underlying EPA data for citations or regulatory filings — meaning a human scientist is still the one signing off.
For pollution monitoring, the World Economic Forum reports [1] that AI and ML models can process large volumes of air-quality sensor data faster, allowing quicker action by governments trying to improve air quality, and researchers in April 2026 unveiled new AI-driven air quality monitoring systems [2]. The profession's own journals are leaning in: the Society of Environmental Toxicology and Chemistry issued a 2025 call for papers [3] on applying AI to field or laboratory experiments and analyzing pre-existing large datasets. Tasks like writing reports, building charts, and crunching sensor data are getting faster — but inspections, policy advice, and audits still rely on human judgment.
Sources
How fast is AI adoption growing for Environmental Scientists?
Adoption will likely be steady but cautious. On the speed-up side, tools are already commercially available and cheap compared to scientist salaries — the Bureau of Labor Statistics reports [4] the 2024 median pay was $80,060 per year, so even modest time savings pay off. Slowing things down: environmental decisions feed into legal cases and regulations, so accuracy and traceability matter enormously.
Brookings analysts in March 2026 [5] note that scientific roles tend to score high on AI complementarity — meaning AI works with workers rather than instead of them. Encouragingly, the BLS still projects employment growing 4 percent from 2024 to 2034, with about 8,500 openings each year [4]. The human skills that stay valuable — fieldwork, ethical judgment, communicating with communities, and standing behind your findings in a public hearing — are exactly the parts AI can't take over.
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More Career Info
Career: Environmental Scientists and Specialists, Including Health
They study the environment to find ways to protect it and keep people healthy by solving problems like pollution and climate change.
Parent Careers
Employment & Wage Data
Median Wage
$80,060
Jobs (2024)
90,300
Growth (2024-34)
+4.4%
Annual Openings
8,500
Education
Bachelor's degree
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2024-2034
Task-Level AI Resilience Scores
AI-generated estimates of task resilience over the next 3 years
1
Conduct applied research on environmental topics, such as waste control or treatment or pollution abatement methods.
2
Conduct environmental audits or inspections or investigations of violations.
3
Evaluate violations or problems discovered during inspections to determine appropriate regulatory actions or to provide advice on the development and prosecution of regulatory cases.
4
Collect, synthesize, analyze, manage, and report environmental data, such as pollution emission measurements, atmospheric monitoring measurements, meteorological or mineralogical information, or soil ...
5
Monitor environmental impacts of development activities.
6
Analyze data to determine validity, quality, and scientific significance and to interpret correlations between human activities and environmental effects.
7
Provide advice on proper standards and regulations or the development of policies, strategies, or codes of practice for environmental management.
Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.
