Contributed by Donald McPhail | VP of market development at eSmart Systems
ESB Networks has launched a five-year program to digitally inspect up to 10,000 structures across the Republic of Ireland.
The near-term benefits are tangible: faster reporting, fewer field visits, and lower carbon emissions from the inspection program itself. The more consequential shift, though, is that asset condition data from across the network is now being captured in a single, comparable, longitudinal record and treated as the data foundation for proactive, risk-based asset management.
This represents a concrete example in Europe of a distribution operator treating grid inspection as core infrastructure for decarbonization, with lessons in its adoption relevant on both sides of the Atlantic.
The Operational Context
ESB Networks is responsible for building, operating, and maintaining the electricity distribution system in the Republic of Ireland, serving approximately 2.4 million customers. It is a subsidiary within the ESB Group, which has publicly committed to enabling a net-zero electricity system by 2040.
That commitment shapes the operational picture in concrete ways. ESB Networks is absorbing growing volumes of variable renewable generation, supporting electrification of heat and transport, and managing a distribution network that, like most networks in Northern Europe, includes a significant share of aging assets. Corrosion is one of the more visible condition challenges in Irish networks, and one that an image-based, AI-supported inspection program is well-positioned to track consistently over time.
The utility’s infrastructure spans tens of thousands of structures across multiple voltage levels, each requiring periodic inspection. Helicopter patrols, foot patrols, and climbing crews on a fixed cycle have been the standard tools of the trade for decades, for ESB Networks and for the wider distribution sector. What’s changed is how far inspection data can go. It should help drive better planning, investment, maintenance, and operational decisions.
The Challenge: Making Inspection Work Harder
The pressures driving ESB Networks to modernize its inspection program are representative of the challenges facing distribution operators across Europe and North America. The industry as a whole is rethinking how inspection data is captured. Conventional inspection, built around periodic visits, paper or PDF reports, and locally-held records, was designed for a different operating environment. It works fine when inspection cycles are long, and the data is mostly consumed locally. It works less well when condition data needs to drive network-wide capital prioritization, feed predictive maintenance models, or demonstrate measurable progress against a published decarbonization target.
There are also carbon and cost implications with the traditional approach. Every helicopter hour and truck roll has both a financial and an emissions cost, impacting environmental performance for utilities with a net-zero emissions target.
ESB Networks set the bar deliberately high. The new program would need to produce findings in a consistent, network-wide format. It would need to build a persistent record of asset condition that grew over time. And it would need to make a measurable contribution to reducing the inspection program’s own emissions footprint.
The Solution: AI-Powered Structured Visual Inspection at Network Scale
ESB Networks partnered with eSmart Systems to deploy Grid Vision, an AI-enabled platform for grid inspection and asset management. The program is scoped to digitally inspect up to 10,000 structures over five years.
The inspection methodology combines UAV imagery, captured under standardized protocols, with AI-supported defect detection and human-in-the-loop validation. Each image is processed by computer vision models trained to identify specific asset-condition categories, and every flagged finding is reviewed by trained analysts before being actioned.
The result is a structured visual asset repository. Every inspected structure has a linked image record, accurate asset location, a condition assessment, and a recommended action. Findings are objective, comparable across regions, and, critically, persistent. They live in a digital asset record that grows with each inspection cycle.
Building a Longitudinal Asset Record
The strategic point of the program is not the inspection itself, but rather the resulting database that enables ESB’s transition from field-based inspections to insight-driven grid intelligence. Each cycle of UAV imagery and AI-assisted assessment contributes to a longitudinal record of each structure’s condition. That longitudinal record is the precondition for enabling ESB Networks to perform risk-based replacement prioritization and predictive maintenance analysis. Without a consistent, comparable dataset captured at the structure level, those downstream capabilities are unattainable.
This matters because the AI capabilities available to utilities will improve substantially every year, unlocking increasing value. Whereas structurally inconsistent inspection data fails to unlock any new value over time.
Results and Scale
The program is delivering measurable operational outcomes. Inspection-to-report timelines have compressed substantially, with automated workflows reducing the time from imagery capture to actionable findings. This is reducing the truck rolls and helicopter hours required to maintain network visibility.
Importantly, the carbon footprint of the inspection program itself is dropping, a measurable contribution to ESB Group’s 2040 commitment. Asset condition data is now being captured in a consistent, network-wide format that supports proactive asset decisions.
The five-year program will continue to expand as inspection data is integrated with broader asset and environmental datasets. The intent is to build inspection into a continuous intelligence layer, not to treat it as a discrete, periodic activity.
Oisín Armstrong of ESB’s engineering & major projects team described the practical value directly: the virtual inspection approach is allowing ESB to “gain efficiency through an end-to-end inspection program, saving time, reducing costs and our carbon footprint, and supporting our mission to achieve zero carbon emissions by 2040.”
A Replicable Model for Distribution Operators Facing the Energy Transition
What makes the ESB Networks deployment relevant to the broader sector is its replicability. ESB Networks is not an outlier in its operating conditions. Variable renewable integration, electrification load growth, aging assets, severe-weather exposure, and a published decarbonization commitment are conditions shared by hundreds of distribution operators across Europe and North America. The key ingredients of the program were a phased approach scoped at the program level rather than as a one-off deployment, a structured capture protocol that prioritizes data consistency, and an integration model that treats inspection findings as inputs to asset management rather than as standalone reports.
As grid reliability pressures intensify and decarbonization commitments harden, distribution operators of all sizes will need a defensible, data-grounded answer to the same question: which assets do we prioritize, in what order, and on what evidence? Answering that question well requires a different kind of data foundation than periodic reporting alone can provide. ESB Networks’ experience offers a concrete, field-tested blueprint for building it.
About the Author
Donald McPhail is vice president of market development at eSmart Systems. He has more than 15 years of experience working with electric utilities and technology vendors across the United States, Australia, the United Kingdom, and Europe, helping organizations integrate asset intelligence, component-level inspection data, and risk modeling into wildfire mitigation, extreme weather resilience, and grid modernization strategies.