Will environmental scientists be replaced by AI?
Updated
Environmental scientists score 51 of 100 for AI exposure. The largest share of their task time, 88%, is work AI speeds up while they stay in charge. AI can take over 6% outright, and 6% stays with people.
- 6% AI can do it
- 88% AI helps
- 6% Needs a person
High exposure
Higher than 77% of the 923 occupations we scored.
Task by task
We graded 22 tasks, listed here from most to least exposed. AI can do 1 of them today, speeds up 20 and leaves 1 to people.
| Task | AI exposure |
|---|---|
| Prepare charts or graphs from data samples, providing summary information on the environmental relevance of the data. Chart and graph generation from datasets is routine software work. | 75% AI can do it |
| Analyze data to determine validity, quality, and scientific significance and to interpret correlations between human activities and environmental effects. AI can check data quality and correlations; scientist interprets significance. | 60% AI helps |
| Process and review environmental permits, licenses, or related materials. AI can screen permit documents against criteria; a reviewer signs off. | 58% AI helps |
| Collect, synthesize, analyze, manage, and report environmental data, such as pollution emission measurements, atmospheric monitoring measurements, meteorological or mineralogical information, or soil or water samples. Data synthesis, analysis and reporting are highly AI-assisted; sample collection is not. | 55% AI helps |
| Develop the technical portions of legal documents, administrative orders, or consent decrees. AI drafts technical sections well; legal review and accountability remain human. | 55% AI helps |
| Plan or develop research models, using knowledge of mathematical and statistical concepts. AI writes modeling and statistics code well; scientist sets assumptions. | 55% AI helps |
| Communicate scientific or technical information to the public, organizations, or internal audiences through oral briefings, written documents, workshops, conferences, training sessions, or public hearings. AI drafts reports and slides well, but briefings and hearings need people. | 50% AI helps |
| Review and implement environmental technical standards, guidelines, policies, and formal regulations that meet all appropriate requirements. AI can check work against standards text, but implementation needs staff judgement. | 50% AI helps |
| Provide advice on proper standards and regulations or the development of policies, strategies, or codes of practice for environmental management. AI speeds research and drafting of standards and policy; expert judgement leads. | 45% AI helps |
| Research sources of pollution to determine their effects on the environment and to develop theories or methods of pollution abatement or control. Literature synthesis and modeling aid research; lab and field work stay human. | 40% AI helps |
Show the other 12 tasks
| Task | AI exposure |
|---|---|
| Design or direct studies to obtain technical environmental information about planned projects. Study design benefits from AI assistance; site work and expert choices stay human. | 40% AI helps |
| Determine data collection methods to be employed in research projects or surveys. AI can propose sampling and survey methods; expert selects and validates them. | 40% AI helps |
| Develop methods to minimize the impact of production processes on the environment, based on the study and assessment of industrial production, environmental legislation, and physical, biological, and social environments. Impact analysis and option drafting are AI-assisted; engineering decisions stay human. | 40% AI helps |
| Provide scientific or technical guidance, support, coordination, or oversight to governmental agencies, environmental programs, industry, or the public. Drafting guidance is AI-assisted; coordination and oversight remain interpersonal. | 35% AI helps |
| Conduct applied research on environmental topics, such as waste control or treatment or pollution abatement methods. Applied research needs lab and field work; AI aids literature and analysis. | 35% AI helps |
| Develop programs designed to obtain the most productive, non-damaging use of land. Land-use planning uses GIS and drafting aids; community and site judgement stays human. | 35% AI helps |
| Monitor effects of pollution or land degradation and recommend means of prevention or control. Field monitoring stays physical, while analysis and recommendations can be AI-assisted. | 30% AI helps |
| Monitor environmental impacts of development activities. Site impact monitoring is physical; data review and reporting can be AI-assisted. | 30% AI helps |
| Evaluate violations or problems discovered during inspections to determine appropriate regulatory actions or to provide advice on the development and prosecution of regulatory cases. Regulatory action choices need legal and professional judgement; AI helps with analysis. | 30% AI helps |
| Investigate and report on accidents affecting the environment. Accident site investigation is physical; AI speeds up report writing. | 25% AI helps |
| Conduct environmental audits or inspections or investigations of violations. On-site inspections are physical; AI helps only with paperwork and reports. | 22% AI helps |
| Supervise or train students, environmental technologists, technicians, or other related staff. Supervising and training people depends on in-person mentorship and presence. | 15% Needs a person |
How environmental scientists compare
All occupations (923)
Life, physical and social science (60)
Pay and outlook in the US
- Median pay
- $82,220 a year, May 2025
- People employed
- 89,250 in the US, May 2025
- Projected change in jobs
- +6.1% from 2024 to 2034
Skills to build
- Collect field soil, water and air samples on site
- Set modeling assumptions and validate results in IBM SPSS Statistics
- Build and query emissions datasets in SQL and Microsoft Access
- Map monitoring results in ESRI ArcGIS and GIS systems
- Draft technical sections of consent decrees in Microsoft Word
- Mentor environmental technicians through supervised field sampling
Safer roles nearby
5 related occupations with lower scores.
Questions about environmental scientists and AI
Will AI replace environmental scientists?
Partly. About 4 in 10 working hours go to tasks AI can already do, mostly chart and graph preparation and environmental data reporting. Field sample collection, site inspections and accident investigation stay with people because they need someone physically present.
Which tasks is AI taking over for environmental scientists?
Chart and graph preparation has an exposure score of 75, the highest on the list, because it is routine software work. Permit review scores 58, with AI screening documents against criteria while a reviewer signs off. Data synthesis and analysis scores 55, since AI checks data quality and correlations.
Which tasks stay human for environmental scientists?
Supervising and training technicians scores 15, the lowest exposure, because mentorship depends on in-person presence. Accident investigation scores 25 and site inspections score 22, since both need a person physically on location. Field monitoring scores 30 and stays physical, though its analysis can be AI-assisted.
How can environmental scientists stay valuable?
Build field sampling skills and keep site inspection training current. Take responsibility for the interpretation step by setting assumptions in IBM SPSS Statistics and judging the significance of correlations. Write technical sections of consent decrees and permits, with a human reviewer signing off on legal risk. Query emissions data in SQL and map results in ESRI ArcGIS. Mentor technicians on site.
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