BETA
Updated: Feb 6
BETA
Updated: Feb 6
Evolving
Last Update: 11/21/2025
Your role’s AI Resilience Score is
57.1%
Median Score
Changing Fast
Evolving
Stable
What does this resilience result mean?
These roles are shifting as AI becomes part of everyday workflows. Expect new responsibilities and new opportunities.
AI Resilience Report for
Conservation Scientists
They protect the environment by studying natural areas and finding ways to manage and use resources without harming ecosystems.
Summary
The career of a conservation scientist is labeled as "Evolving" because AI is starting to take over data-heavy tasks like mapping and analysis, making these processes much faster and more efficient. While AI tools help with routine work, conservation scientists still need to use their human judgment for hands-on activities and important decision-making.
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View analysisChat with CoachLatest newsMore career infoSummary
The career of a conservation scientist is labeled as "Evolving" because AI is starting to take over data-heavy tasks like mapping and analysis, making these processes much faster and more efficient. While AI tools help with routine work, conservation scientists still need to use their human judgment for hands-on activities and important decision-making.
Read full analysisContributing Sources
AI Resilience
All scores are converted into percentiles showing where this career ranks among U.S. careers. For models that measure impact or risk, we flip the percentile (subtract it from 100) to derive resilience.
CareerVillage.org's AI Resilience Analysis
AI Task Resilience
Evolving30.6%
30.6%
Microsoft's Working with AI
AI Applicability
Evolving45.6%
45.6%
Anthropic's Economic Index
AI Resilience
Stable99%
99%
Will Robots Take My Job
Automation Resilience
Stable83.9%
83.9%
Medium Demand
Labor Market Outlook
We use BLS employment projections to complement the AI-focused assessments from other sources.
Learn about this scoreGrowth Rate (2024-34):
3.4%
Growth Percentile:
55.7%
Annual Openings:
2.5
Annual Openings Pct:
25.3%
Analysis of Current AI Resilience
Conservation Scientists
Updated Quarterly • Last Update: 11/21/2025
State of Automation & Augmentation
Conservation science is starting to use AI for data-heavy parts of the job. For example, field images and maps are often run through machine-learning models. A recent report notes that “conservation scientists are increasingly automating their research and monitoring” by using pattern‐recognition software to spot species or habitat changes [1].
In soil and water work, US researchers have used AI models to speed up calculations. One project trained a neural network on half a million soil‐loss calculations, creating a detailed erosion map of Iowa 65,000 times faster than the standard method [2]. Drones and satellites feed images into AI programs that can automatically find features like terraces or drainage ditches in fields [2].
Companies even use smart probes and robots to analyze soil health instead of hand-sampling [3]. These tools gather data and highlight potential problems so that scientists can focus their attention. AI is also helping with reports: for instance, wetland experts discuss using tools like ChatGPT to draft field protocols or regulatory summaries more quickly [4].
Still, many core tasks rely on people. Hands-on work like building erosion barriers or walking through wetlands needs human judgment and effort. Team meetings and training with landowners depend on communication skills that AI can’t replace.
In fact, a professional workshop for wetland scientists stressed that AI should help with “repetitive tasks” (data cleaning, formatting, drafting) while keeping scientists, not software, in the decision-making seat [4]. In summary, AI tools are now augmenting activities like mapping, data analysis and report writing [2] [1]. But conservationists still apply the final expertise on-site: people interpret local conditions and legal issues, so human skills remain central for many tasks.
Sources
AI Adoption
Whether these AI tools spread quickly depends on costs, benefits, and trust. One factor speeding adoption is strong need and funding: for example, a 2024 news story noted a $300 million U.S. investment in “climate-smart” farming technologies that include AI soil monitoring [3]. The USDA and others have shown big time savings – one AI method mapped erosion nearly instantly what once took days of work [2].
Free satellite data and open-source AI software make powerful tools available to many groups. These efficiencies and investment show there are clear economic and environmental incentives to use AI.
On the other hand, public agencies and communities tend to move carefully with new tech. Conservation budgets are limited, so buying sensors or hiring data scientists can be harder than hiring experienced staff. There are also social and legal concerns: people still trust human expertise for interpreting regulations or community issues.
As noted above, experts emphasize using AI as an assistant, not a replacement [4]. So even though the tech exists, adoption is likely gradual. In practice, projects with clear payoffs (like faster mapping) will roll out AI first, while other tasks wait until tools prove reliable and affordable.
In the end, young conservationists can be hopeful: AI can handle routine analysis and free them up for people skills and creativity, but it won’t take away the need for caring scientists on the ground [4] [3].
Sources
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More Career Info
Career: Conservation Scientists
Parent Careers
Similar Careers
Employment & Wage Data
Median Wage
$67,950
Jobs (2024)
28,500
Growth (2024-34)
+3.4%
Annual Openings
2,500
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
Implement soil or water management techniques, such as nutrient management, erosion control, buffers, or filter strips, in accordance with conservation plans.
2
Visit areas affected by erosion problems to identify causes or determine solutions.
3
Participate on work teams to plan, develop, or implement programs or policies for improving environmental habitats, wetlands, or groundwater or soil resources.
4
Plan soil management or conservation practices, such as crop rotation, reforestation, permanent vegetation, contour plowing, or terracing, to maintain soil or conserve water.
5
Survey property to mark locations or measurements, using surveying instruments.
6
Manage field offices or involve staff in cooperative ventures.
7
Monitor projects during or after construction to ensure projects conform to design specifications.
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.
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