Compare roles · AI exposure side by side
Firefighters
Put up to three roles next to each other: the exposure figure, the inputs behind it, the window, what is driving change, and where the work moves. Every figure comes from the same method, so the gap between two scores means something.
Exposure
Window · adoption
until most of the change has landed
Low adoption
In one line
AI is improving detection, dispatch and situational awareness; the physical response, rescue and judgement on the fireground remain entirely human.
Inputs behind the score · scaled 0–100
Task applicability
14Observed usage
0Official exposure tier
10Labour-market trajectory
n/aPublished adoption rating
10What is driving it
- AI wildfire detection cameras
- Fire-spread and risk modelling
- Drones and thermal imaging
- Smarter dispatch and records systems
- Simulation-based training
- Very low measured task applicability
Skills worth building
- Core suppression, rescue and physical fitness
- Emergency medical qualification
- Drone operation and thermal imaging
- Incident command and decision-making
- Data and reporting literacy
- Interpreting models and sensors
Tools in the work now
Where the work moves
More exposed
Emergency Medical Technicians (EMTs)17
Different skills, growing
Complementary, less exposed
Full report
Scores are the CareerGuard Exposure Index v2: the same five inputs and weights for every role, so a gap of ten points means the same thing wherever it appears. How scores are built.