Will environmental economists be replaced by AI?
Updated
Environmental economists score 60 out of 100 for AI exposure. AI helps with 95% of their task time, and they stay in charge. AI can do the other 5%.
- 5% AI can do it
- 95% AI helps
High exposure
Higher than 91% of the 923 jobs we scored.
Task by task
We graded 20 tasks, most exposed first. AI can do 1 of them, helps with 19 and leaves 0 to people.
| Task | AI exposure |
|---|---|
| Monitor or analyze market and environmental trends. AI can monitor feeds and summarize trends; analyst reviews signals. | 60% AI can do it |
| Write technical documents or academic articles to communicate study results or economic forecasts. LLMs draft papers well; economist is responsible for findings and claims. | 55% AI helps |
| Collect and analyze data to compare the environmental implications of economic policy or practice alternatives. AI runs comparisons and code; analyst frames and checks results. | 55% AI helps |
| Write social, legal, or economic impact statements to inform decision makers for natural resource policies, standards, or programs. AI drafts impact statements; legal and policy accountability stays human. | 55% AI helps |
| Write research proposals and grant applications to obtain private or public funding for environmental and economic studies. AI drafts proposals quickly; funder fit and vision stay human. | 55% AI helps |
| Conduct research on economic and environmental topics, such as alternative fuel use, public and private land use, soil conservation, air and water pollution control, and endangered species protection. AI speeds literature search and summaries; human vets sources. | 50% AI helps |
| Assess the costs and benefits of various activities, policies, or regulations that affect the environment or natural resource stocks. AI can draft CBA calculations; analyst sets assumptions and values. | 50% AI helps |
| Develop economic models, forecasts, or scenarios to predict future economic and environmental outcomes. AI writes model code and scenario variants; economist specifies structure. | 50% AI helps |
| Develop systems for collecting, analyzing, and interpreting environmental and economic data. AI can build pipelines and tools; system design needs expert oversight. | 50% AI helps |
| Conduct research to study the relationships among environmental problems and patterns of economic production and consumption. AI aids literature and data synthesis; causal framing stays with researcher. | 45% AI helps |
Show the other 10 tasks
| Task | AI exposure |
|---|---|
| Develop environmental research project plans, including information on budgets, goals, deliverables, timelines, and resource requirements. AI drafts plans and budgets; scoping and stakeholder agreement stay human. | 45% AI helps |
| Prepare and deliver presentations to communicate economic and environmental study results, to present policy recommendations, or to raise awareness of environmental consequences. AI drafts slides and talking points; speaking and Q&A stay human. | 40% AI helps |
| Perform complex, dynamic, and integrated mathematical modeling of ecological, environmental, or economic systems. AI assists coding and solvers; model design needs deep domain expertise. | 40% AI helps |
| Examine the exhaustibility of natural resources or the long-term costs of environmental rehabilitation. AI assists theory and numerics; long-run assumptions need expert judgment. | 40% AI helps |
| Identify and recommend environmentally friendly business practices. AI drafts practice ideas; recommendations need client context and judgment. | 40% AI helps |
| Develop programs or policy recommendations to achieve environmental goals in cost-effective ways. AI helps generate and compare policy options; choice needs judgment. | 35% AI helps |
| Teach courses in environmental economics. AI helps prepare materials and grading; live teaching stays human. | 35% AI helps |
| Interpret indicators to ascertain the overall health of an environment. AI interprets indicator data; field validation and context need experts. | 35% AI helps |
| Demonstrate or promote the economic benefits of sound environmental regulations. Advocacy needs human credibility; AI helps with drafting. | 30% AI helps |
| Develop programs or policy recommendations to promote sustainability and sustainable development. Sustainability policy requires stakeholder engagement and value judgments. | 30% AI helps |
How environmental economists compare
All jobs (923)
Life, physical and social science (60)
Pay and outlook in the US
- Median pay
- $124,720 a year, May 2025
- Projected change in jobs
- +4.7% from 2024 to 2034
Skills to build
- Run cost-benefit comparisons of policy options in Python or SAS
- Map pollution and land-use data in ESRI ArcGIS
- Verify AI-summarized sources against original studies before citing them in Word
- Build impact models in Microsoft Excel with documented assumptions
- Write policy recommendations that weigh stakeholder values and tradeoffs
- Present study findings and defend them in live PowerPoint sessions
Safer roles nearby
5 related jobs with lower scores.
Questions about environmental economists and AI
Will AI replace environmental economists?
Partly. About 5 in 10 of an environmental economist's working hours go to tasks AI can already do, mostly monitoring market and environmental trends and drafting technical documents. Findings, verified claims, and the judgment on what the numbers mean stay with the economist.
Which tasks is AI taking over for environmental economists?
Trend monitoring is the most exposed task, with an exposure score of 60, because AI can watch data feeds and summarize signals for the analyst to review. Drafting technical papers and running data comparisons across policy options, each with an exposure score of 55, follow close behind, with the economist checking the results.
Which tasks stay human for environmental economists?
Demonstrating the economic benefits of sound regulations, exposure 30, stays with people because advocacy depends on credibility. Developing sustainability policy recommendations, also exposure 30, needs stakeholder engagement and value judgments. Teaching courses, exposure 35, stays human because live instruction needs a person in the room.
How can environmental economists stay valuable as AI takes on more analysis?
Build cost-benefit and impact models in Python or SAS yourself so you can check every AI-run comparison. Verify each AI-summarized source against the original study before it reaches a report. Then present findings in person, where answering questions live builds trust in your conclusions.
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Next steps for environmental economists
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