As the world watches in dismay at the devastation caused by the recent LA wildfires, I reflect deeply on the challenges utility companies face in these extraordinary times. These events are not just stories on the news—they’re stark reminders of the growing vulnerabilities in our infrastructure. Our thoughts and prayers are with the LA community as they recover from this tragedy.
In moments like these, the stakes are painfully clear. It’s no longer a matter of "if" such events will occur but "when" and "how often." The costs—both human and financial—are staggering. Today, hundreds of thousands of people are without power, and the toll on critical infrastructure is mounting.
Utility companies are increasingly on the front lines of a crisis we can no longer ignore. In 2023 alone, the U.S. experienced 28 weather disasters that caused over $ 1 billion in damages. These events don't just test our grids—they expose vulnerabilities that can leave entire communities in the dark.
Over the years, I've worked at the crossroads of technology and utility engineering, construction, and storm response, and one thing has become clear: the old ways of doing things are no longer enough. Reacting after the damage is done—sending crews in to assess, repair, and restore—is too slow and costly. If we want to build grids to handle the challenges ahead, we need to get ahead of the storms. That's where artificial intelligence comes in. It's not just a tool for utilities; it's a way to turn heaps of data into clear, actionable plans. It's about anticipating problems and solving them before they escalate.
From Reactive to Proactive
Traditional utility responses rely on reactive methods—sending teams to assess and repair damage afterward. However, today's storms are not the same as those our systems were originally designed to handle.
In 2024, Hurricanes like Milton and Helene caused extensive power outages and significant damage to electrical infrastructure across the nation. The U.S. Environmental Protection Agency reports that cyclonic storm intensity has increased over the past 40 years, causing more significant challenges. Climate change has increased the frequency, intensity, and unpredictability of severe weather events, including hurricanes, wildfires, and extreme heat waves.
For every hour of power outage, businesses, hospitals, and families bear the brunt. Communities lose trust in their providers, and the cost, both financial and social, escalates with every delay. Outdated infrastructure poses a significant challenge to operational efficiency. In the U.S., more than 70% of the transmission lines are over 25 years old and approaching the end of their typical 50–80-year lifecycle, resulting in annual economic losses estimated between $28 billion and $169 billion.
In the past, utilities relied on sweeping, generalized improvements to their infrastructure in anticipation of future storms. However, advancements in AI can enable a more precise approach. By analyzing past data and predicting the potential effects of upcoming storms and power outages, utilities can identify and prioritize the weakest points in the grid. This data-driven strategy allows for targeted upgrades, ensuring resources are directed where needed most. It can help us shift from reactive recovery to proactive preparation.
A Data-Driven Approach
One of the most transformative applications for utilities is predictive analytics. We can forecast vulnerabilities before a storm hits by analyzing historical weather patterns, grid performance, and vegetation data by using predictive analytics. Imagine knowing where power lines are likely to fail days in advance. Take vegetation management, for instance. Overgrown trees are one of the leading causes of outages during storms. Traditional inspection methods can be manual, slow, and labor-intensive. I've seen utilities spend months on guesswork-driven processes, and the aging infrastructure only compounds the challenge.
This is where LiDAR and AI step in to redefine traditional approaches. LiDAR technology creates highly detailed 3D maps of landscapes and infrastructure, revealing risks we could only guess before—like conductor sag, vegetation encroachment, and inadequate ground clearances. These maps, enriched with AI and machine learning, don't just highlight problems; they categorize risks by span. For instance:
- Span/Conductor sag assessments: Detailed evaluations of sagging lines and ground clearance risks help us understand the threats before they escalate.
- Vegetation risk profiles: By quantifying grow-in and fall-in risks, brush density, and even specific tree species, utilities can focus resources where the risks are highest.
- Land use insights: Beyond vegetation, LiDAR data shows how wetlands, residential areas, and commercial properties intersect with infrastructure, ensuring a more holistic risk strategy.
These capabilities fundamentally change how we prepare for and respond to storms. By combining annual updates from LiDAR with historical weather and outage data, we can identify trends and focus on the areas that matter most. It’s about turning data into action—directing crews to the riskiest areas with precision and ensuring annual inspections address the right priorities.
When a storm hits, every minute counts. Hurricane Beryl and Hurricane Helene are clear examples of this, which paralyzed parts of the U.S. For restoration teams, having a clear, real-time understanding of blocked routes, damaged infrastructure, and high-risk spans is invaluable. LiDAR-driven insights, combined with AI, allow us to scan miles of power lines in days instead of months. This speed and accuracy can mean the difference between communities left in the dark for days and grids fortified to withstand the worst of nature.
This is not just about improving efficiency—it’s about fundamentally reshaping how we think about resilience. AI and LiDAR aren't just tools but the foundation for building smarter, safer grids that protect the people and communities we serve.
Overcoming Barriers to AI Adoption
AI adoption isn't easy. Utilities grapple with tight budgets, legacy systems, and cultural resistance. Some industry veterans worry that AI threatens their roles. But here's the truth: AI doesn't take jobs; it makes those jobs more effective. The real challenge is collaboration between utilities, policymakers, and technology providers.
Overcoming regulatory hurdles and securing funding for AI requires clear communication and shared urgency. Public-private partnerships will be critical to unlocking AI's full potential. A Deloitte report revealed that AI-driven predictive maintenance can help minimize downtime, maximize productivity, and save capital. The U.S. Department of Energy also emphasizes AI's pivotal role in achieving national climate goals, particularly in enhancing grid reliability and integrating renewable energy sources. These partnerships are key to breaking adoption barriers.
Amplifying Human Expertise
AI does not replace human expertise; it enhances it. The scale of modern utility challenges is staggering. No human team can process the sheer volume of weather, grid, and environmental data being generated today. That's where AI comes in.
For example, it can monitor real-time conditions across thousands of acres during wildfire season. It flags anomalies like rising temperatures or unusual wind shifts—so human operators can focus their efforts on the areas that matter most. This is not man versus machine; it's man with machine. It's the synergy between human intuition and machine precision that will carry utilities forward.
The Bottom Line
The storms are here and the challenges are real. But so are the solutions. AI is not just a tool; it's a necessity. It's the bridge between where we are and need to be: a future where outages are minimized, recovery is swift, and communities are protected.
For utility leaders, the question is no longer whether to adopt AI. It is how far we're willing to go to unlock its full potential. Every storm, disruption, and power outage reminds us of the urgency of this mission. We can lead this transformation—not just to survive the climate challenges ahead but to thrive despite them. The time to act is now.
