The race against wildfire destruction is being transformed by artificial intelligence, with utilities like Avista leading the charge. After investing $10 million in AI-powered camera systems across the Pacific Northwest, the company is showcasing how technology can provide the critical minutes needed to prevent catastrophic blazes.
During my recent visit to Avista’s operations center in Spokane, I witnessed their network of high-definition cameras scanning the horizon, powered by algorithms trained to distinguish smoke patterns from clouds, dust, or fog. This system represents a remarkable shift from traditional wildfire detection methods.
“The technology allows us to identify potential fires within 30 seconds of ignition,” explains Jake Lanphere, Avista’s Wildfire Resiliency Program Manager. “Before this system, we might not know about a fire until someone called it in or it grew large enough to be visible from miles away.”
What makes this approach particularly effective is the integration of multiple data sources. The AI doesn’t just process visual information—it combines weather data, historical fire patterns, and vegetation conditions to calculate risk levels across Avista’s 30,000-square-mile service area. When potential smoke is detected, the system automatically alerts operators who can verify the threat and coordinate with emergency services.
The technology has already proven its worth. Last summer, during a period of extreme heat and dry conditions, the system identified three separate ignition events before they developed into major fires. According to data from the National Interagency Fire Center, early detection can reduce wildfire suppression costs by up to 75%, a significant saving compared to the millions typically spent fighting established blazes.
Climate scientists at Washington State University have noted that as climate change intensifies, the Pacific Northwest faces longer and more severe fire seasons. Utilities have increasingly found themselves at the intersection of climate adaptation and public safety.
“We’re not just protecting our infrastructure,” notes Heather Rosentrater, Avista’s Senior Vice President of Energy Delivery. “This is about community safety and environmental stewardship. When we prevent a wildfire, we’re also preventing carbon emissions, protecting watersheds, and preserving habitats.”
The system isn’t perfect. During my demonstration, I observed how the AI occasionally flagged dust from agricultural operations as potential smoke. But the technology’s continuous learning capabilities mean these false positives are becoming increasingly rare. Each alert, whether accurate or not, contributes to the algorithm’s training dataset.
Beyond detection, the same technology is helping Avista make smarter decisions about grid management during high-risk conditions. Traditional approaches often involved broad public safety power shutoffs—cutting electricity to large areas during dangerous weather. The granular data from the AI system allows for more surgical interventions.
“We can now be much more precise about where and when we need to modify operations,” explains Lanphere. “Instead of shutting down power to entire communities, we might reconfigure the grid to reduce risk in specific high-threat areas while maintaining service elsewhere.”
The financial calculus for utilities is compelling. According to a recent MIT Technology Review analysis, the average cost of wildfire damage attributed to utility infrastructure has exceeded $4.2 billion annually in the Western United States over the past decade. Even with the substantial upfront investment in AI systems, the potential savings in liability, infrastructure damage, and restoration costs make the technology an increasingly essential investment.
Other utilities are taking notice. PG&E in California and Portland General Electric in Oregon have begun implementing similar systems, creating what industry experts describe as a technological safety net spanning the western states most vulnerable to wildfire.
The most promising aspect may be the technology’s continuous improvement. The current generation of AI wildfire detection can spot smoke within 30 seconds to two minutes of ignition. The next iteration, currently in development, aims to predict conditions that could lead to ignition before a fire even starts.
As climate change continues to reshape our relationship with natural disasters, the integration of artificial intelligence into our environmental safety systems represents a critical adaptation strategy. For communities across the wildfire-prone West, these technological sentinels watching the horizon may be the difference between a close call and a catastrophe.
While perfect prevention remains elusive, the minutes gained through early detection provide the margin of safety that firefighters, utilities, and communities desperately need in our increasingly fire-prone world.
