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Copyright © 2025 by Industrial News. All rights reserved. This article first appeared in August 2025 on Industrial News.
Hari Vasudevan of KYRO discusses how, rather than replacing tradition with technology, an efficient storm response and recovery system for utilities should be based on a carefully blended approach.
Utility professionals pride themselves on rapid, decisive action. Emergency crews roll out, and everyone from linemen to consultants works diligently to restore power as quickly as possible. This “all-hands-on-deck” approach embodies traditional values of reliability, safety, and community commitment.
Yet Europe is increasingly hit by severe weather, including storms, costing billions of euros and affecting millions of lives—and this is driving up the costs to restore power. While lines of trucks and hundreds of crew members rolling in is a reassuring sight, it can ramp up massive labour and logistical expenses.
New technologies and data-driven strategies now offer ways to maintain these conservative principles while minimizing outages and controlling costs. Utilities can expedite storm recovery via AI-enabled resource tracking, real-time field data, and automating documentation processes to build a more resilient grid.
However, rather than replacing human input with technology, the path forward lies in a carefully blended approach between following traditional methods and applying technology.
There’s a massive amount of legwork that goes into actioning effective storm response, and traditional methods often rely heavily on already stretched teams. In the thick of the moment, speed is the name of the game. Yet this can be a significant challenge when trying to mobilize crews, determine who’s available from rosters of assessors, wire-guards and linemen, and where to send them for maximum effectiveness.
Boots on the ground also have to make quick-fire decisions, such as blocking off dangerous roads and clearing rights-of-way. They’re responsible for safety and security, protecting the public and utility crews alike from dangers like downed power lines and structural damage. On top of that, any crucial detail that slips through the cracks can carry huge cost implications and cause massive delays in recovering expenses post-event. Utilities have to accurately capture work hours and expenses across multiple districts to justify cost recovery.
Yet amidst the chaos of a disastrous storm, completely capturing that information isn’t always feasible. This carries serious consequences when dealing with regulators who demand transparency and accuracy in order to issue recovery costs. Evidence-based documentation, in the form of timesheets, chain-of-custody receipts, and material usage reports, is non-negotiable for approvals.
As well as causing devastating losses to local residents’ and businesses’ livelihoods, severe storms also have a massive financial impact on local communities.
For instance, total losses from last year’s Storm Boris hit €2.19 billion ($2.54 billion). While European utilities were able to lean on insurance companies, events like this still take a toll on their budgets. That’s because insurance payouts aren’t always immediately available, and, when recovery bills are in the hundreds of millions of euros, out-of-pocket expenses for utilities can become eye-watering. This puts a dent in cash flow, leaving utilities vulnerable to any other severe weather event that occurs while they’re waiting for insurance claims to be verified. Eventually, insurance premiums increase as a result of these claims and that additional cost is ultimately borne by the utility customers.
To alleviate these cash flow challenges and insurance premium increases after a disaster, utilities often have to hike up rates, putting added strain on end-customers’ bills. There’s an increasing need for a more cost-efficient approach that augments traditional methods with technology. This not only helps utility companies save on immediate costs but also enables them to reinvest those savings towards hardening the grid for long-term resilience.
Technology has a powerful role to play in reducing overhead and the manual legwork needed to rapidly and efficiently action storm responses. Now, with automation, utilities have been tracking and mapping out resources according to predicted areas of storm impact by tapping into AI-powered asset monitoring and vegetation management.
Additionally, utilities are leveraging AI to forecast specific areas that will be hit hardest, while accessing real-time analytics on resource availability and automated skills matching to deploy crews at a faster and more effective rate. Beyond that, they can speed up time to action from decision-making via platforms that connect field crews with centralized teams who have access to unified insights from the ground. Bolstering the collaborative efforts between departments that are otherwise quite isolated helps utilities double down on response and restoration efforts, maximizing transparency, and ensuring all information and communications are tracked.
Adjacent to that, utilities are applying digital tools to reduce administrative burdens, automating tasks like time sheets and expense tracking. This saves enormous amounts of effort in the aftermath of a storm that otherwise means chasing paper trails to recover costs. These automated tools digitally log each transaction, including when and where it occurred, resulting in stronger transparency for verifying costs with regulators.
The ripple effect is significant here, with AI streamlining the chain of custody. Vendors also benefit from this greater transparency as faster payment processes through accurate invoices and evidence of completed work allow them to continue providing services to utilities. In turn, that saves them up to hundreds of millions in recovery efforts.
The path forward for more resilient storm grids lies in careful coordination between AI and humans. It is important to recognize that human oversight is currently indispensable to successful AI deployment.
The transformative tech-forward approach to storm management is still grounded in the human role alongside technology. That’s why utilities must also nurture awareness and aptitude in leveraging technology for a more effective storm response. Teams, whether they’re on the ground or behind a desk monitoring events, should be empowered to fully leverage insights from digital tools to take the best course of action in as little time as possible.
Crucially, these tools are not here to replace people’s capabilities but strengthen them. By utilizing innovative technology to streamline processes, utilities reduce the burden on manual resources. Before adopting any AI tools, utilities need to ensure their teams are aware of how technology can empower their strategic decision-making and action timeframes. Practical training with these tools will also prepare teams to maximize them ahead of disaster striking, from initial response stages to verifying expenses with regulators for cost recovery.
Additionally, succinct data management is vital to smoothly integrate automation and new technology into a system. Utilities must have centralized and diverse data streams—such as crew logistics, equipment tracking, and real-time field updates—to optimize AI application for strengthening the grid. Again, ensuring teams are familiar with protocols around data input and interoperability is pivotal to a successful automation strategy for greater grid resilience.
Technology is vital to building a more resilient storm grid in the long term, but not without the human touch. Balancing tradition and technology is key to strengthening the grid and reducing cost burdens so utilities can reinvest in much-needed infrastructure advancements before the next disaster occurs.
Link to the original article - here
Copyright © 2025 by Industrial News. All rights reserved. This article first appeared in August 2025 on Industrial News.
Hari Vasudevan of KYRO discusses how, rather than replacing tradition with technology, an efficient storm response and recovery system for utilities should be based on a carefully blended approach.
Utility professionals pride themselves on rapid, decisive action. Emergency crews roll out, and everyone from linemen to consultants works diligently to restore power as quickly as possible. This “all-hands-on-deck” approach embodies traditional values of reliability, safety, and community commitment.
Yet Europe is increasingly hit by severe weather, including storms, costing billions of euros and affecting millions of lives—and this is driving up the costs to restore power. While lines of trucks and hundreds of crew members rolling in is a reassuring sight, it can ramp up massive labour and logistical expenses.
New technologies and data-driven strategies now offer ways to maintain these conservative principles while minimizing outages and controlling costs. Utilities can expedite storm recovery via AI-enabled resource tracking, real-time field data, and automating documentation processes to build a more resilient grid.
However, rather than replacing human input with technology, the path forward lies in a carefully blended approach between following traditional methods and applying technology.
There’s a massive amount of legwork that goes into actioning effective storm response, and traditional methods often rely heavily on already stretched teams. In the thick of the moment, speed is the name of the game. Yet this can be a significant challenge when trying to mobilize crews, determine who’s available from rosters of assessors, wire-guards and linemen, and where to send them for maximum effectiveness.
Boots on the ground also have to make quick-fire decisions, such as blocking off dangerous roads and clearing rights-of-way. They’re responsible for safety and security, protecting the public and utility crews alike from dangers like downed power lines and structural damage. On top of that, any crucial detail that slips through the cracks can carry huge cost implications and cause massive delays in recovering expenses post-event. Utilities have to accurately capture work hours and expenses across multiple districts to justify cost recovery.
Yet amidst the chaos of a disastrous storm, completely capturing that information isn’t always feasible. This carries serious consequences when dealing with regulators who demand transparency and accuracy in order to issue recovery costs. Evidence-based documentation, in the form of timesheets, chain-of-custody receipts, and material usage reports, is non-negotiable for approvals.
As well as causing devastating losses to local residents’ and businesses’ livelihoods, severe storms also have a massive financial impact on local communities.
For instance, total losses from last year’s Storm Boris hit €2.19 billion ($2.54 billion). While European utilities were able to lean on insurance companies, events like this still take a toll on their budgets. That’s because insurance payouts aren’t always immediately available, and, when recovery bills are in the hundreds of millions of euros, out-of-pocket expenses for utilities can become eye-watering. This puts a dent in cash flow, leaving utilities vulnerable to any other severe weather event that occurs while they’re waiting for insurance claims to be verified. Eventually, insurance premiums increase as a result of these claims and that additional cost is ultimately borne by the utility customers.
To alleviate these cash flow challenges and insurance premium increases after a disaster, utilities often have to hike up rates, putting added strain on end-customers’ bills. There’s an increasing need for a more cost-efficient approach that augments traditional methods with technology. This not only helps utility companies save on immediate costs but also enables them to reinvest those savings towards hardening the grid for long-term resilience.
Technology has a powerful role to play in reducing overhead and the manual legwork needed to rapidly and efficiently action storm responses. Now, with automation, utilities have been tracking and mapping out resources according to predicted areas of storm impact by tapping into AI-powered asset monitoring and vegetation management.
Additionally, utilities are leveraging AI to forecast specific areas that will be hit hardest, while accessing real-time analytics on resource availability and automated skills matching to deploy crews at a faster and more effective rate. Beyond that, they can speed up time to action from decision-making via platforms that connect field crews with centralized teams who have access to unified insights from the ground. Bolstering the collaborative efforts between departments that are otherwise quite isolated helps utilities double down on response and restoration efforts, maximizing transparency, and ensuring all information and communications are tracked.
Adjacent to that, utilities are applying digital tools to reduce administrative burdens, automating tasks like time sheets and expense tracking. This saves enormous amounts of effort in the aftermath of a storm that otherwise means chasing paper trails to recover costs. These automated tools digitally log each transaction, including when and where it occurred, resulting in stronger transparency for verifying costs with regulators.
The ripple effect is significant here, with AI streamlining the chain of custody. Vendors also benefit from this greater transparency as faster payment processes through accurate invoices and evidence of completed work allow them to continue providing services to utilities. In turn, that saves them up to hundreds of millions in recovery efforts.
The path forward for more resilient storm grids lies in careful coordination between AI and humans. It is important to recognize that human oversight is currently indispensable to successful AI deployment.
The transformative tech-forward approach to storm management is still grounded in the human role alongside technology. That’s why utilities must also nurture awareness and aptitude in leveraging technology for a more effective storm response. Teams, whether they’re on the ground or behind a desk monitoring events, should be empowered to fully leverage insights from digital tools to take the best course of action in as little time as possible.
Crucially, these tools are not here to replace people’s capabilities but strengthen them. By utilizing innovative technology to streamline processes, utilities reduce the burden on manual resources. Before adopting any AI tools, utilities need to ensure their teams are aware of how technology can empower their strategic decision-making and action timeframes. Practical training with these tools will also prepare teams to maximize them ahead of disaster striking, from initial response stages to verifying expenses with regulators for cost recovery.
Additionally, succinct data management is vital to smoothly integrate automation and new technology into a system. Utilities must have centralized and diverse data streams—such as crew logistics, equipment tracking, and real-time field updates—to optimize AI application for strengthening the grid. Again, ensuring teams are familiar with protocols around data input and interoperability is pivotal to a successful automation strategy for greater grid resilience.
Technology is vital to building a more resilient storm grid in the long term, but not without the human touch. Balancing tradition and technology is key to strengthening the grid and reducing cost burdens so utilities can reinvest in much-needed infrastructure advancements before the next disaster occurs.
Link to the original article - here
Hari Vasudevan, PE, is a serial entrepreneur and engineer focused on AI-driven solutions for utilities, construction, and storm response. As Founder and CEO of KYRO AI, he leads the development of AI-powered software that helps utility, vegetation, and field service teams digitize operations, improve storm response and restoration, and reduce operational risk. He also serves as Vice Chair and Strategic Adviser for the Edison Electric Institute’s Transmission Subject Area Committee and holds bachelor’s and master’s degrees in civil engineering with professional engineering licensure in multiple states.
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