Climate Scientists
Overall Exposure
2025 vs 2023
Theoretical Exposure
70What AI could do
Observed Exposure
33What AI actually does
Automation Risk Score
34Displacement risk
3-Year Outlook (2025 → 2028)
Projected changes in AI automation metrics over the next 3 years based on estimated data.
Overall Exposure
2025 → 2028 (estimated)
Theoretical Exposure
2025 → 2028 (estimated)
Observed Exposure
2025 → 2028 (estimated)
Automation Risk
2025 → 2028 (estimated)
Exposure Metrics (2023 - 2028)
Detailed Metrics Table
| Year | Overall | Theoretical | Observed | Risk | Data Type |
|---|---|---|---|---|---|
| 2023 | 38 | 55 | 18 | 22 | actual |
| 2024 | 45 | 62 | 25 | 28 | actual |
| 2025 | 53 | 70 | 33 | 34 | actual |
| 2026 | 59 | 76 | 39 | 39 | estimated |
| 2027 | 64 | 81 | 44 | 43 | estimated |
| 2028 | 68 | 85 | 48 | 47 | estimated |
Task Breakdown
About This Occupation
If you work as a Climate Scientist, AI is reshaping your profession. With an automation risk of 34/100 and overall exposure at 53%, this role faces high transformation. The highest-impact area is run and calibrate climate simulation models at 70% automation. This is classified as an 'augment' role. BLS projects +6% growth through 2034. Machine learning is revolutionizing weather pattern analysis and enabling higher-resolution climate projections than ever before.
Frequently Asked Questions
With an automation risk score of 34%, Climate Scientists has a low risk of AI replacement. Most tasks in this role require skills that are difficult for AI to replicate, such as complex decision-making, physical dexterity, or deep interpersonal interaction. AI is more likely to serve as a supportive tool.
The AI automation risk score for Climate Scientists is 34% (2025 data). Overall AI exposure is 53%, with 70% theoretical exposure and 33% observed exposure. The risk trend from 2023 to 2025 is +12 points.
The tasks with the highest automation potential for Climate Scientists are: Run and calibrate climate simulation models (70%), Analyze satellite and observational data for climate trends (65%), Collect and quality-control field measurement data (48%). These rates reflect how much of each task current AI systems can handle, based on research data from Anthropic and academic sources.
The BLS projects +6% employment change for Climate Scientists from 2024 to 2034. Combined with an overall AI exposure of 53%, this occupation is experiencing both traditional labor market shifts and AI-driven transformation. Workers should monitor both employment trends and AI capability growth.
Since AI primarily augments capabilities in this role, professionals in Climate Scientists should embrace AI as a productivity multiplier. Focus on learning to use AI tools effectively, developing higher-order analytical and creative skills, and positioning yourself as someone who can leverage AI to deliver greater value.