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# Will climate change policy analysts be replaced by AI?

Updated October 2026

Climate change policy analysts score 58 out of 100 for AI exposure. AI helps with 72% of their task time, and they stay in charge. AI can do another 15%. 13% needs a person.

-   **15%** AI can do it
-   **72%** AI helps
-   **13%** Needs a person

High exposure

Higher than 88% of the 923 jobs we scored.

## Task by task

We graded 14 tasks, most exposed first. AI can do 2 of them, helps with 10 and leaves 2 to people.

| Task | AI exposure |
| --- | --- |
| Gather and review climate-related studies from government agencies, research laboratories, and other organizations. Literature search and screening are highly automatable with verification. | 72% AI can do it |
| Analyze and distill climate-related research findings to inform legislators, regulatory agencies, or other stakeholders. Summarizing research into stakeholder briefs is core LLM work. | 70% AI can do it |
| Write reports or academic papers to communicate findings of climate-related studies. Drafting papers from findings is strong AI work; authors stay accountable. | 70% AI helps |
| Prepare study reports, memoranda, briefs, testimonies, or other written materials to inform government or environmental groups on environmental issues, such as climate change. Drafting reports is strong; testimony needs accountable human approval. | 68% AI helps |
| Research policies, practices, or procedures for climate or environmental management. Desk research suits AI; verification keeps human in charge. | 68% AI helps |

## How climate change policy analysts compare

All jobs (923)

Life, physical and social science (60)

The dark line is **climate change policy analysts, at 58**. Each dot is a score, and darker dots mean more jobs share it. The short marks are the averages, 37 for all jobs and 47 for life, physical and social science.

## Pay and outlook in the US

Median pay

$82,220 a year, May 2025

Projected change in jobs

+6.1% from 2024 to 2034

## Skills to build

-   Screen climate studies and verify citations before drafting
-   Draft legislative recommendations in Microsoft Word
-   Map emissions and policy data in ESRI ArcGIS software
-   Run policy data checks in Python, R or SAS
-   Present and defend proposals in live stakeholder meetings
-   Build stakeholder decks in Microsoft PowerPoint

## Safer roles nearby

5 related jobs with lower scores.

-   [Chief sustainability officers51 out of 100](https://www.aigentcy.com/ai-exposure/chief-sustainability-officers/)
-   [Environmental scientists51 out of 100](https://www.aigentcy.com/ai-exposure/environmental-scientists/)
-   [Industrial ecologists52 out of 100](https://www.aigentcy.com/ai-exposure/industrial-ecologists/)
-   [Conservation scientists43 out of 100](https://www.aigentcy.com/ai-exposure/conservation-scientists/)
-   [Environmental restoration planners51 out of 100](https://www.aigentcy.com/ai-exposure/environmental-restoration-planners/)

## Questions about climate change policy analysts and AI

Will AI replace climate change policy analysts?

Climate change policy analysts score 58 out of 100 for AI exposure. AI helps with 72% of their task time, and they stay in charge. AI can do another 15%. 13% needs a person.

Will climate change policy analysts be replaced?

Partly. About 5 in 10 working hours go to tasks AI can already do, mostly gathering and screening climate studies and distilling findings into stakeholder briefs. What stays with people is advocacy, live defense of proposals and legislative recommendations that need political judgment.

Which climate policy tasks is AI taking over?

Literature search and briefing are the most exposed. Gathering and reviewing climate studies scores 72 on exposure, and distilling findings for legislators scores 70. AI can screen sources and draft summaries quickly, but the analyst still checks every citation before it reaches a regulator.

Which climate policy tasks stay human?

Promoting mitigation initiatives with government and environmental groups scores 18 on exposure, the lowest in the job. Relationship building depends on in-person trust. Presenting and defending research proposals also scores 18, because a live defense needs expert judgment from a person in the room.

How can climate change policy analysts stay valuable?

Verify every AI-drafted summary against the primary study before it enters a brief. Take responsibility for the legislative recommendations in Microsoft Word, tying each one to a named statute or regulation. Build geospatial evidence in ESRI ArcGIS software, run data checks in Python or R, and rehearse live testimony with stakeholders.

## Related jobs

-   [Environmental economists60 out of 100](https://www.aigentcy.com/ai-exposure/environmental-economists/)
-   [Sustainability specialists60 out of 100](https://www.aigentcy.com/ai-exposure/sustainability-specialists/)
-   [Brownfield redevelopment specialists49 out of 100](https://www.aigentcy.com/ai-exposure/brownfield-redevelopment-specialists/)
-   [Environmental engineers54 out of 100](https://www.aigentcy.com/ai-exposure/environmental-engineers/)

## Next steps for climate change policy analysts

-   ### Check your job
    
    Your job title is a rough guide. Your tasks decide your score. Paste your job description or CV to see which tasks AI can do.
    
    [Check your job](https://www.aigentcy.com/tools/ai-exposure-checker/) [Check your CV](https://www.aigentcy.com/tools/cv-checker/)
    
-   ### Estimate team savings
    
    The score is per person. Add headcount and salary to see the hours AI can take on in a team of climate change policy analysts, and what they cost.
    
    [Estimate what AI saves a team of climate change policy analysts](https://www.aigentcy.com/tools/team-ai-audit/?role=climate-change-policy-analysts) [Work out the return on automation](https://www.aigentcy.com/tools/ai-savings-calculator/)
    

### Check which roles in your team AI can take on

We map your team's tasks, show what AI can do today and build the automations that pay back first.

[Book an AI audit](https://www.aigentcy.com/audit/)

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Sources and licences

Occupation data from the O\*NET 30.3 Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA), used under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) and modified by Aigentcy. O\*NET® is a trademark of USDOL/ETA. Wage, employment and projection data from the U.S. Bureau of Labor Statistics. EU occupation names from ESCO, European Commission. AI usage signals from the Anthropic Economic Index (CC BY) and Microsoft Research (CC BY 4.0). [Methodology and sources](https://www.aigentcy.com/ai-exposure/methodology/). Scores © Aigentcy. Quote them with a link to the page.
