As wildfires intensify, a new generation of artificial intelligence systems is learning to detect and fight flames before crews can respond.
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The fires stopped waiting for summer. Now they burn across entire regions year-round, fueled by heat, wind and drought. Each season brings new records: Greater casualties, greater evacuations, and entire cities wiped out in hours.
In the first half of 2025 alone, global insured losses from natural disasters reached approx. 80 billion dollarsmuch of it from wildfires and severe storms, according to Reuters. Firefighters are battling burnout, insurers are pulling out of high-risk areas, and communities are being left scrambling for new ways to defend themselves.
This search has turned to a bold question – can machines help fight fires themselves; In Israel, based in Tel Aviv FireDome recently unveiled an artificial intelligence system that can detect and suppress small flames within seconds, long before human crews arrive. It is part of a broader movement to use artificial intelligence not only for prediction but also for intervention, bridging the gap between early warning and real-time response to wildfires.
Wildfire Resilience-as-a-Service
For decades, fire technology focuses on detection. Satellites, drones and sensors signaled when a blaze had already spread. But today’s new AI systems are now trying to act in the moment. They combine thermal cameras, machine learning algorithms and localized suppression units that can react immediately when a heat anomaly occurs near homes or businesses.
of FireDome field test in October 2025 demonstrated a version of this approach, using sensors and artificial intelligence models trained on millions of fire images to trigger precision launch capsules filled with water or an environmentally friendly retardant. The company described the event as a step toward “fire resilience as a service,” in which communities could deploy automated systems that respond the moment a threat occurs.
“This is the tipping point,” Gadi Benjamini, co-founder and CEO of FireDome, said in a press release. “Wildfires are becoming larger, more costly and more difficult to insure. This demonstration shows that the FireDome can act in seconds to protect lives, property rights and critical assets before first responders arrive.”
What remains uncertain is the scale of innovative systems like FireDome, although the company claims its system is effective even for large fires. While the company’s demo is promising, questions about reliability and safety remain. Can systems like this work reliably outside test sites, in unpredictable terrain and changing winds? And can they be safely integrated with already depleted human firefighting crews? It remains to be seen how these systems react when deployed in nature.
Training Machines To respond
Indeed, the true promise of these technologies lies in how they learn. Vision models recognize heat signatures and verify that an area is clear of people, vehicles or animals. Machine learning algorithms then adjust for factors such as wind and slope, deciding when and where to act. Each activation feeds new data into the model, improving accuracy over time.
AI researchers refer to this as closed-loop learning: The system observes, acts, measures the result, and adapts. It’s the same principle behind self-driving cars or industrial robotics, but applied to an unstable physical environment.
In the event of disasters, this continuous learning ability could help machines help faster than any human coordination network can manage — if the oversight keeps up.
Speed meets responsibility
Advocates see potential beyond firefighting. Former U.S. Fire Administrator Dr. Lori Moore-Merrell said in a statement that the integration of automated systems with precision suppression could help insurers and governments rethink how they bill and manage fire hazard. However, autonomy raises new concerns about certification, liability and how to ensure that split-second decisions made by algorithms are safe and accountable.
Benjamini acknowledges this tension, noting that technology is only part of the solution. “Artificial intelligence can help us move faster,” he said, “but it must move responsibly. The goal is not to replace firefighters – it’s to give them time.”
This is where politics should come. The development of artificial intelligence in disaster zones blurs the lines between assistance and autonomy. Communities will need clear rules about who controls these systems, how errors are reported, and what happens when human and machine decisions conflict.
A new AI chapter in climate response
The emergence of autonomous fire systems marks a broader turning point in climate adaptation. Instead of sitting in data centers, AI moves into forests, floodplains, and power grids—environments where every second counts. Whether the goal is to suppress wildfires, predict floods, or protect power lines, AI moves from analysis to action.
Insurance magazineI expect global insured losses from climate-induced catastrophes to arrive $145 billion by the end of 2025. This pressure is forcing governments and companies to look for faster, smarter ways to limit damage. Systems like FireDome won’t replace human responders, but they could become an added layer of protection that steps in when danger strikes and lines of communication fail.
What is emerging is not just a new tool, but a new kind of partnership between intelligence and resilience. The challenge now is to build that partnership on trust, transparency and proof that it really works when the next inferno flattens everything in its path.
