Wildfires are no longer confined to the western United States. In 2025 alone, the U.S. experienced more wildfires from January to August than in any comparable period over the past decade. These fires are increasingly ignited by grid-related failures, loose hardware, vegetation contact, and aging infrastructure – posing a growing threat to utilities nationwide. As climate change intensifies and regulatory scrutiny increases, utilities must shift from reactive inspection models to proactive, data-driven wildfire mitigation strategies. 

A recent industry webinar brought together experts from eSmart Systems, Microsoft, Technosylva, and the Smart Electric Power Alliance (SEPA) to explore how artificial intelligence (AI) and predictive insights are helping utilities stay ahead of wildfire risks. The core of the discussion was how digital twin technologies, AI-powered inspection platforms, and predictive analytics are redefining the way utilities inspect, manage, and protect their infrastructure. 

The Expanding Wildfire Threat 

“Wildfire risk is no longer a regional concern,” said Don McPhail, VP of Market Development at eSmart Systems. “Utilities in areas that haven’t traditionally faced wildfires are now seeing increased threats due to hotter temperatures, prolonged droughts, and vegetation growth.” 

Jared Leader from SEPA echoed this sentiment, noting that even utilities in Virginia and the Midwest are developing wildfire mitigation plans. “Having a wildfire plan is not optional anymore,” he said. “It’s central to utility planning.” 

The stakes are high. Lives, infrastructure, and billions of dollars in liability are on the line. And with federal funding, such as the $3.7 billion wildfire initiative, now supporting AI adoption and data-sharing frameworks, utilities have a unique opportunity to modernize their approach. 

Digitalization: The Foundation of Proactive Risk Management 

At the heart of this transformation is digitalization. By creating a digital representation of your grid (image-based database that integrates high-resolution imagery, asset metadata, and grid topology and it’s all centralized in one place), utilities gain near real-time visibility into asset health and environmental conditions. 

“Digitalization isn’t just the first step, it’s the bare minimum,” said Bilal Khursheed, Executive Director for Power & Utilities at Microsoft. “You can’t manage what you can’t measure.” 

This visibility enables utilities to detect vegetation encroachment, asset degradation, and environmental stressors, supporting predictive analytics that identify risks before they escalate into ignition events. 

AI-Powered Inspections: Faster, Smarter, Safer 

Traditional inspections are slow and labor-intensive. A single inspector climbing lattice towers could take years to complete a full inspection cycle. In contrast, drone-assisted inspections combined with AI-powered image analysis can reduce that timeline by up to 80%. 

In one case study, a North American utility inspected 47 lattice towers and 52 wooden poles, capturing over 3,400 images.  
 
The AI detected: 

• 781 upside-down cotter pins 
• Loose shackles and contaminated insulators 
• Anomalies like woodpecker holes and cracked poles 

These insights allowed the utility to target repairs that target high risk of ignition sources without climbing towers, improving safety and reducing risk. “We’re seeing a 60% uplift in defect detection compared to traditional methods,” McPhail noted. 

Predictive Insights and Vegetation Management 

Beyond defect detection, AI enables predictive insights by analyzing historical data and identifying patterns. For example, wooden poles near water may degrade faster due to humidity, while certain asset classes may show recurring vulnerabilities. 

Vegetation is a primary fuel source for grid-related fires. AI-powered platforms use high-resolution imagery combined with conditional data to monitor vegetation encroachment and assess the overall health of grid assets. “Risk is everywhere and constantly changing,” said Indran Ratnathicam, Chief Growth Officer at Technosylva. “It’s not about knowing if your risk is high or low—it’s about knowing where and when it is.”

Human Expertise + AI: A Collaborative Future 

While AI is a powerful tool, the panel emphasized that it’s not a replacement for human expertise. “AI augments decision-making,” said Khursheed. “It gives field crews superpowers, not pink slips.” 

McPhail added, “The real transformation happens when data becomes insight, and insight becomes action. That’s where AI fits into the workflow, not as a standalone tool, but as part of a broader strategy.” 

Advice for Utilities Starting Their AI Journey 

AFor utilities just beginning to explore AI, the panel offered clear guidance: 

• Start now. “The best time to plant a tree was 10 years ago. The second-best time is now – the same applies to utilities’ AI journey” McPhail said. 
• Standardize and centralize data. Structured, high-quality data is essential for effective AI. 
• Think beyond pilots. “Proof of concept proves potential, not readiness,” said Khursheed. Scaling requires operational integration. 
• Collaborate. Partnering with experienced technology providers ensures success under real-world conditions. 

A Call to Action 

Wildfires are a growing crisis, but AI-powered inspection platforms and predictive analytics offer a path forward. By digitalizing assets, leveraging predictive insights, and integrating vegetation management, utilities can move from reactive to proactive wildfire mitigation. 

As McPhail concluded, “Don’t wait for a fire to force change. Embrace AI and data-driven tools now. The cost of inaction is far greater than the investment in proactive technology.”