Somewhat Resilient
Last Update: 8/30/2026
AI Resilience Score for Environmental Economists:
45.3%
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 Economists
$124,720 median salary•1,100 annual openings•SOC Code: 19-3011.01
Environmental Economists are somewhat less resilient to AI impacts than most occupations, according to our analysis of 6 sources.
Environmental economics sits in the "Somewhat Resilient" category because AI is already taking over a meaningful chunk of the routine work, like collecting data, running calculations, and spotting trends in environmental patterns, but the higher-stakes tasks still need a human in the driver's seat. The tricky part is that this field's work often ends up in courtrooms and government regulations, so the results have to be transparent and defensible in ways that "black-box" AI models simply cannot guarantee on their own.
Learn more about how you can thrive in this position
View analysis
Chat with Coach
Latest news
More career infoAnalysisChatNewsMoreThis role is somewhat resilient
Environmental economics sits in the "Somewhat Resilient" category because AI is already taking over a meaningful chunk of the routine work, like collecting data, running calculations, and spotting trends in environmental patterns, but the higher-stakes tasks still need a human in the driver's seat. The tricky part is that this field's work often ends up in courtrooms and government regulations, so the results have to be transparent and defensible in ways that "black-box" AI models simply cannot guarantee on their own.
Read full analysisLearn more about how you can thrive in this position
View analysisChat with CoachLatest newsMore career infoAnalysisChatNewsMoreAnalysis of Current AI Resilience
Environmental Economists
Updated Quarterly
How is AI changing Environmental Economists jobs?
Right now, AI is mostly helping environmental economists rather than replacing them. The tasks facing the highest automation potential — collecting data, monitoring market and environmental trends, and running cost-benefit calculations — are exactly where machine learning shines. For example, Resources for the Future researchers are already "utilizing artificial intelligence tools to sort through the many different types of actions taken on adaptation and resilience" [1] to figure out which climate policies work best in specific communities.
Machine learning models are also being applied to environmental economics for tasks like predicting pollution patterns, valuing ecosystem services, and evaluating climate-related financial policies [2]. On the day-to-day side, environmental economists already lean on programming languages like Python and MATLAB "for custom analyses and automation" [3], and generative AI is layering on top of those tools to speed up literature reviews, coding, and first drafts of reports. But the higher-judgment tasks — presenting findings, promoting sound regulations, and teaching — stay firmly in human hands, because economics work involving "ethical policy design," contextual analysis, and persuasive communication cannot be fully substituted by AI [4].
Sources
How fast is AI adoption growing for Environmental Economists?
Adoption in this field is moving at a steady but careful pace. On the "fast" side, the tools are cheap and already commercially available (Python libraries, ChatGPT-style assistants, GIS platforms), and the BLS projects that closely related analytical roles like data scientists will grow 33.5 percent between 2024 and 2034 [5] as employers embrace AI. Employers also see clear economic benefits: Brookings researchers note that AI is reshaping labor markets and that workers who can adapt to AI tools will have real advantages [6].
On the "slower" side, environmental economics work is often used to justify regulations and lawsuits, so results must be transparent, reproducible, and defensible in court — a bar that "black-box" AI models don't always meet. Government agencies (a huge employer of environmental economists) also have strict procurement and ethics rules that slow AI rollout. The encouraging takeaway: if you're a high schooler curious about this path, learning statistics, ethical reasoning, and communication alongside AI tools will make you far more valuable — not less — as the field evolves, especially since environmental economist employment is still projected to grow about 6 percent through 2032 [3].
Sources
Will AI replace Environmental Economists?
Not entirely. We think AI will take over some tasks, but not the whole job.
Environmental economists earn a 45.3% AI Resilience Score, which puts them in meaningful-but-manageable territory. The tasks most at risk are also the most routine: collecting data, running cost-benefit calculations, and scanning research for patterns. AI tools are already doing a lot of that heavy lifting, with researchers using machine learning to sort through climate policy actions and predict pollution patterns (resources.org, frontiersin.org). That shift is real and worth taking seriously.
What stays human is the harder stuff. Designing ethical regulations, presenting findings to policymakers, and making economic arguments that hold up in court all require judgment, communication, and accountability that AI cannot reliably provide [4]. Environmental economics work is often used to justify real legal and policy decisions, so transparency and defensibility matter enormously, and black-box AI models don't clear that bar.
The broader picture is mixed but not discouraging. Employment in this field is still projected to grow about 6 percent through 2032 [3], and workers who combine statistical skills with ethical reasoning and strong communication will have a real advantage as AI tools become standard [6]. The job is changing, but it is not disappearing.
Sources
Help us improve this report.
Tell us if this analysis feels accurate or we missed something.
Share your feedback
Latest AI news for Environmental Economists
These articles highlight the intersection of AI and environmental economics, showcasing both challenges and opportunities. For instance, understanding the environmental impact of AI data centers can help economists advocate for sustainable practices in tech. Additionally, the volatility in energy markets influenced by AI demands knowledge of economic trends, allowing environmental economists to develop strategies for energy efficiency. As AI reshapes job markets, economists can play a vital role in ensuring that the green transition remains equitable and resilient, positioning themselves as key players in this evolving landscape.
The AI revolution mirrors the green transition
www.eco-business.com • 6/12/2026
The need for massive upfront investments and the likelihood of significant job displacement imply remarkable parallels between the AI...
Volatility spillover between the energy and AI markets: a TVP-VAR approach
www.frontiersin.org • 4/13/2026
With the growing energy consumption from AI model training and use, as well as the increasing integration of AI into the energy industry, the AI and energy...
'Fragile and Highly Vulnerable' – Moody's Economist Mark Zandi Warns AI Impact on Jobs is 'Dead Ahead', Sees 'Many More Months' Without Job Gains
finance.yahoo.com • 3/4/2026
As artificial intelligence advances rapidly, concerns that it could replace white-collar jobs are growing louder.
‘Roadmap’ shows the environmental impact of AI data center boom
news.cornell.edu • 11/10/2025
Researchers used advanced data analytics to create a state-by-state look at that environmental impact of the AI boom and how to make the...
New Mexico Tech Interdisciplinary Team Receives NSF Award for AI-Assisted Environmental Risk Modeling
www.nmt.edu • 9/9/2025
An interdisciplinary team of New Mexico Tech management and computer science faculty has been awarded a National Science Foundation (NSF)...
More Career Info
Career: Environmental Economists
They study how people use natural resources and suggest ways to protect the environment while supporting economic growth.
Parent Careers
Similar Careers
Employment & Wage Data
Median Wage
$124,720
Jobs (2025)
18,600
Growth (2025-35)
+4.7%
Annual Openings
1,100
Education
Master's degree
Experience
None
Source: Bureau of Labor Statistics, Employment Projections 2025-2035
Task-Level AI Resilience Scores
AI-generated estimates of task resilience over the next 3 years
1
Teach courses in environmental economics.
2
Demonstrate or promote the economic benefits of sound environmental regulations.
3
Prepare and deliver presentations to communicate economic and environmental study results, to present policy recommendations, or to raise awareness of environmental consequences.
4
Develop programs or policy recommendations to promote sustainability and sustainable development.
5
Develop programs or policy recommendations to achieve environmental goals in cost-effective ways.
6
Write research proposals and grant applications to obtain private or public funding for environmental and economic studies.
7
Write social, legal, or economic impact statements to inform decision makers for natural resource policies, standards, or programs.
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.
