Wildland Fire Supervisors
Overall Exposure
2025 vs 2023
Theoretical Exposure
43What AI could do
Observed Exposure
11What AI actually does
Automation Risk Score
10Displacement 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 |
|---|---|---|---|---|---|
| 2024 | 22 | 38 | 6 | 7 | actual |
| 2025 | 27 | 43 | 11 | 10 | estimated |
| 2026 | 32 | 48 | 16 | 13 | estimated |
| 2027 | 36 | 52 | 20 | 16 | estimated |
| 2028 | 40 | 56 | 24 | 19 | estimated |
Task Breakdown
About This Occupation
If you work as a Wildland Fire Supervisor, AI augments your fire behavior analysis and reporting while field leadership remains human-led. With an automation risk of 10/100 and overall exposure at 27%, this role faces low transformation. Fire behavior modeling sees the highest automation at 55%. BLS projects +6% growth through 2034.
Frequently Asked Questions
With an automation risk score of 10%, Wildland Fire Supervisors 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 Wildland Fire Supervisors is 10% (2025 data). Overall AI exposure is 27%, with 43% theoretical exposure and 11% observed exposure. The risk trend from 2023 to 2025 is 0 points.
The tasks with the highest automation potential for Wildland Fire Supervisors are: Analyze fire behavior models and weather forecasts (55%), Complete incident documentation and after-action reports (48%), Direct crew positioning and suppression tactics on fire line (8%). 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 Wildland Fire Supervisors from 2024 to 2034. Combined with an overall AI exposure of 27%, 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 Wildland Fire Supervisors 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.