Mitigation of the coordination crisis in wildfire management using a multi-agent AI system
The devastating California wildfires of January 2025 underscored the staggering human and economic tolls of escalating climate disasters. While retrospective analyses often attribute these losses to climate change, fuel accumulation, and wildland-urban interface expansion, a critical systemic blind spot remains: the inefficiencies in wildfire suppression driven by misaligned incentives, behavioral biases, and fragmented interagency coordination. In this perspective, we argue that Agentic Artificial Intelligence (Agentic AI) offers a transformative pathway to bridge these operational divides, moving beyond isolated, local resource optimization toward a synchronized, global response capability. To address these challenges, we propose a comprehensive governance framework designed to successfully employ multi-agent AI systems for disaster management. By aligning incentives, ensuring accountability, and fostering cross-agency collaboration, this framework provides a blueprint for leveraging Agentic AI to mitigate the coordination crisis in wildfire management and build systemic resilience against future climate shocks. Integrating agentic AI within a shared governance framework for wildfire management would help overcome cooperation problems and improve collaboration and coordination in decision-making across agencies, suggests a synthesis of inefficiencies and options for improvement.