Wildfires are intensifying across the U.S., with utilities facing unprecedented challenges as these disasters threaten grid infrastructure and customer safety. Traditional reactive approaches are no longer sufficient, as utilities struggle to balance operational reliability with the growing need for proactive, data-driven risk management in an increasingly volatile climate landscape.
This webinar reveals how leading utilities are transforming their wildfire mitigation strategies through AI-powered solutions, predictive insights and digital grid asset management. Industry experts share proven methodologies for anticipating risks, optimizing maintenance schedules, and maintaining grid resilience while reducing wildfire exposure.
Explore:
- How digitalization of grid assets enhances wildfire risk visibility and supports smarter decision-making
- Real-world applications of AI and geospatial analysis in proactive threat prevention
- Strategies for combining risk assessment with predictive maintenance for faster, smarter risk mitigation
How does Grid Vision work with national wildfire agencies like NIFC, and does government shutdown impact data availability?
We use the best available private utility data as well as public wildfire and situational data, as appropriate. As an asset management and planning tool, our platform is designed to operate independently and not reliant on government data feeds, ensuring continuous access to inspection insights, asset health indicators, and high-risk component detection.
Are insurance carriers working with utilities to strengthen wildfire risk programs?
Yes. We see growing collaboration between insurers and utilities to reduce financial exposure. Grid Vision helps utilities provide objective evidence of proactive maintenance and risk reduction, which supports insurance discussions and lowers long-term risk costs.
Which regions outside the Western United States are most exposed to wildfire risk and need predictive mitigation tools?
Wildfire risk is rising in the Mountain States, Texas, the Southeast, and parts of the Northeast due to climatic shifts and expanding electrification. We are seeing strong interest in predictive wildfire programs in Canada and Europe, particularly in regions with aging overhead networks near vegetation and communities.
How do you help cost-sensitive utilities justify investment in AI and wildfire mitigation technology?
We focus on operational outcomes. Utilities using Grid Vision report faster inspections, reduced helicopter and field exposure, better prioritization of capital work, and lower likelihood of ignition events. Early, targeted action reduces long-term costs and improves customer and regulator confidence.
Can Grid Vision use Vexcel imagery or other high-resolution aerial datasets?
Yes. Grid Vision is data-flexible and supports Vexcel and similar providers when available. When coverage gaps exist, we work with utilities and partners to capture imagery using drones, helicopters, or satellite data at the appropriate resolution. We’re agnostic to the data capture hardware, as long as it meets the resolution requirements to power Grid Vision’s analytics.
Do you support regions where high-resolution imagery is limited, such as parts of California or Los Angeles?
We help utilities deploy the right capture approach for their network. Grid Vision supports RGB, LiDAR, and thermal data so utilities can expand coverage quickly and build consistent inspection programs that scale across all assets.
During an active wildfire, can Grid Vision account for incident team strategies and tactics?
We provide an accurate view of asset intelligence and geospatial context from recent image capture, to help utilities understand system risks. Utilities can overlay incident response zones and suppression perimeters to support prioritization and restoration decision making.
How close is the industry to integrating operational system data with weather, imagery, and geospatial intelligence?
Utilities are moving rapidly to connect asset condition data with outage events, line faults, weather, and vegetation. Grid Vision can feed risk insights into operational and planning systems, helping utilities focus efforts where the grid and the environment create the highest ignition potential. With our public APIs our strategy is to be a proponent of an integrated ecosystem approach, to deliver the best outcomes for our customers.
What type of weather data does Grid Vision require to support proactive wildfire mitigation?
We use surface-based measurements where available, along with environmental data such as wind, temperature, drought indices, and vegetation, which can be overlayed in Grid Vision. Combined with inspection intelligence, this supports identification of high-risk components and zones by combining these data sets for blended risk assessment.
How do you reduce false positives and maintain trust in AI inspection results?
Our models are trained with utility-validated data and continuously improved through operator feedback using our VerifyAI processes. Utilities control acceptance of findings, and every insight includes traceable image evidence so decisions remain accurate, transparent, and auditable.
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