Investment in GenAI and technologies for wildfire resilience are rising rapidly in concert with one another, often in concepts applying the capabilities of the first to empower the second. Overwhelming interest often blows through product-market misalignments, driving investment that does not solve practical problems, serve practitioner’s needs, or provide the level of trust required when making life and death decisions. When the hype, resources, stakes, and speed of GenAI and wildfire resilience combine, three critical questions arise:
What are the most valuable types of GenAI to develop and deploy for wildfire resilience?
What are the human, infrastructural, and bureaucratic prerequisites for overcoming challenges to the development and deployment of those technologies?
Which intervention points in the wildfire cycle are most in need of these applications?
This report outlines how data synthesis for fuel map predictions, automated interoperability engines, and recovery playbook customization are three undersung opportunities for applying GenAI to the wildfire crisis. These were selected to represent a variety of wildfire cycle intervention points, technical approaches, and user types. They involve detailed descriptions of the problem, solution space, technological approach, and critical next steps. Hurdles to each are detailed, as well as foundational sectoral and technical challenges that must be addressed to enable forward progress.
Opportunities were selected for a final, definitive characteristic: the technological capabilities they rely on are proven. This makes them implementable at the speed at which they can be developed, rather than on a theoretical horizon of technical evolution. This is to ensure that – as investments are made in capability development – they are also made in the tools we need to effect immediate change on the ground. The wildfire crisis is here, it is not waiting for model evolution and neither can we.
