As the flames of three relentless wildfires continue to devour swaths of Southern California, families are forced to flee their homes, emergency responders are stretched to their limits and once-thriving communities are reduced to ash. The heartbreak is palpable: cherished memories, livelihoods and lives hang in the balance.
Californians are no strangers to wildfire devastation, but the escalating frequency and intensity of these blazes demands something new to combat them — a wholesale embrace of the most powerful technology available: military-grade artificial intelligence.
In the wake of 2024’s historic hurricane season, where AI technologies played a pivotal role in aiding East Coast communities’ recovery, these tools can help address the crisis in California.
From predictive modeling that identifies high-risk zones to real-time drone-assisted firefighting, AI offers the potential to turn the tide in the fight against wildfires. The lessons learned from deploying AI during hurricanes—saving lives, mitigating property loss and optimizing disaster response—can and must be adapted to meet the unique challenges of Southern California’s fire-prone terrain.
U.S. Army AI helped with hurricane response
After five hurricanes, an estimated $130 billion in economic losses and more than 300 lives lost, the fall 2024 hurricane season was one of the costliest on record. Two massive hurricanes in rapid succession pummeled Florida and other regions along the Atlantic Coast. Helene and Milton each caused billions in damage, with Milton striking deep inland to devastate the mountain communities of North Carolina.
AI technology took a prominent role in disaster relief, with the U.S. Army’s 18th Airborne Corps repurposing its battlefield AI decision-support tools to assist following Hurricane Helene.
Typically used to make rapid decisions in combat zones, disaster responders adapted this AI to track road closures, cellular outages, resource needs and other crucial data points in real-time during disaster response. It demonstrated the value of military-grade AI in providing decision support and enabling faster, more efficient deployment of resources during emergencies.
The applications of AI in such contexts reveal its potential for a wide range of disaster management scenarios, from early warning systems to long-term recovery efforts.
The expanding role of AI in disaster management
As AI capabilities continue to mature, the technology offers several powerful tools for both disaster preparedness and response, especially in early warning systems. By analyzing vast datasets, AI can identify subtle signs of impending crises, from unusual weather patterns to regions at risk of severe impacts. These insights allow communities and agencies to better prepare, potentially mitigating some of the worst outcomes.
AI-driven data can guide preventative measures for forest fires in vulnerable areas or fine-tuning evacuation plans for high-risk populations. When crisis hits, decision-support AI can help response teams prioritize actions and locate essential resources.
AI’s ability to process multiple data streams—weather updates, satellite imagery, social media, and news reports—enables responders to react with greater accuracy. Post-disaster, AI can also analyze aerial or satellite imagery to rapidly assess damages, pinpointing areas that require urgent attention while helping prioritize resource allocation.
Beyond immediate disaster response, AI can play a strategic role in identifying emerging vulnerabilities, enabling more resilient infrastructure planning, and supporting sustainable recovery initiatives.
Military technology can build disaster resilience
Advanced AI systems are making these scenarios a reality. Large language models (LLMs) used alongside retrieval-augmented generation (RAG) techniques enable analysts to synthesize data from a wide array of sources. LLMs allow users to interact with data using natural language, making it more intuitive and faster to query information. RAG combines LLMs with a retrieval system that sources information from specific, trusted datasets, reducing the risk of inaccurate information.
With real-time access to news reports, social media, government data and climate models, response teams can deploy quickly in disaster-affected areas, reducing the time needed to gather insights and enhancing response accuracy.
In essence, a capability developed to help operators in war-time crises now has applicability in a peacetime disaster response, whereby it can integrate inputs from multiple sources—chatbots, satellite imagery, eyewitness accounts and reconnaissance data—into a cohesive view. This robust data environment aids decision-makers by reducing the noise of irrelevant information, allowing them to focus on critical insights without the misleading “hallucinations” that can sometimes distort AI results.
A roadmap for disaster management
The horrifying start to 2025 underscores the accelerating frequency and intensity of natural disasters. While there is always reason for humility in the face of Mother Nature, AI allows communities to anticipate, prepare and respond far more effectively.
AI isn’t a silver bullet, but it is a vital resource that can help protect neighborhoods, preserve natural landscapes and safeguard the people who call California home. By examining what worked on the East Coast, we can build a smarter, faster and more effective wildfire response system.
It can’t come soon enough for California.
