How is AI Changing the Face of the Energy Industry?
Research suggests that enhancing safety is the top AI/ML use case for nearly half of utility executives, with 49% stating this is one of their main applications of the technology.
This is because AI is invaluable in helping utilities detect and manage critical risks such as gas leaks, downed power lines and equipment failures — all before they turn into serious incidents.
Eric Young is the Director of Grid Management and Distributed Intelligence at American technology company Itron, which offers products and services for energy and water resource management to customers in more than 100 countries.
In this Q&A, he shares with Energy Digital how AI is enhancing the energy industry.
Q. Please introduce yourself and your role
I’m Eric Young, Director of Grid Management and Distributed Intelligence at Itron.
I oversee our grid edge intelligence products and the development of use cases that enable automated system operations.
With more than two decades of experience in electric utility solutions, my role is centred on helping utilities adopt innovative, data-driven approaches to improve reliability, safety and efficiency.
Q. In your own words, what is Itron and how does it have a positive influence in the energy space?
Itron is a global technology company that helps utilities and cities better manage energy and water resources.
We provide smart meters, endpoints, sensors, intelligent networks and software that give utilities greater visibility and control over their operations.
Our work positively influences the energy sector by enabling smarter grid management, improving resource conservation and driving sustainability initiatives, ensuring a resilient and reliable energy future.
Q. How is AI being utilised to detect and manage critical risks such as gas leaks and equipment failures in utility operations?
AI is transforming risk detection in utilities by analysing real-time sensor data to pinpoint potential issues before they escalate.
For gas utilities, AI models can identify anomalies in pressure or flow data, which can indicate leaks, while machine learning algorithms can detect patterns tied to equipment failures, allowing proactive maintenance.
On the grid side, advanced grid edge intelligence technologies — like IoT sensors and Distributed Intelligence (DI) in advanced metering equipment (AMI) — can provide continuous visibility into environmental and system conditions. These tools can detect abnormal voltage fluctuations, overloaded circuits, impedance issues and changes in power factor, enabling utilities to mitigate risks before they impact efficiency, safety or reliability.
AI systems can also automate local fault responses, isolating damaged areas and rerouting power to protect infrastructure and reduce crew exposure to hazardous conditions.
Q. Can you provide examples of how AI has improved safety outcomes in grid management at Itron?
One example is Itron’s use of AI and machine learning to support predictive maintenance and outage prevention.
By leveraging real-time grid data from distributed sensors, AI can identify assets at risk of failure — like overloaded transformers or stressed/damaged lines — before incidents occur.
During extreme weather, AI can enhance safety through automated fault isolation and restoration (FLISR), reducing downtime and risk to repair crews as well as the general public. In gas networks, AI can help utilities pinpoint leaks by analysing real-time pressure data and detecting anomalies.
Q. What are the key challenges utilities face when integrating AI technologies for safety improvements? How does Itron address these challenges?
One major challenge is data and compute readiness.
Utilities often struggle with trapped, inaccessible or incomplete data that can hinder AI performance.
Itron addresses this by providing high-quality, actionable data through smart endpoints like AMI meters and IoT sensors.
These tools can ensure accurate real-time data collection, which fuels AI-driven insights. Another challenge is the complexity of deploying AI at scale, a challenge overcome by incorporating cloud-compute technologies into the data ecosystem. Itron’s interoperable solutions can integrate seamlessly into existing operations, minimising disruption.
Finally, many utilities lack internal AI expertise — Itron bridges this gap with proven platforms and partnerships that can make adoption straightforward, scalable and impactful.
Q. How does AI contribute to proactive risk management in utilities? What role does it play in outage management and demand response?
AI can transform risk management by predicting and allowing time for remediation of issues before they occur.
For outage management, AI-driven fault detection systems can analyse grid conditions in real time, identifying and isolating faults faster to minimise service disruptions.
Predictive analytics can also forecast potential failures, enabling utilities to prioritise regular maintenance operations as well as pre-position resources during extreme weather.
For demand response, AI can optimise energy distribution by analysing usage patterns and forecasting peak demand.
This allows utilities to manage grid loads efficiently, reducing risks like equipment overloads while ensuring reliable service for critical infrastructure, such as hospitals or shelters during emergencies.
Q. What future advancements do you foresee in AI technology that could further enhance safety and efficiency in the utility sector?
Future advancements in AI will likely focus on enhancing real-time decision making and automation.
As AI becomes more sophisticated, it will enable even faster and more accurate risk detection, such as pinpointing micro-level vulnerabilities in the historically unmonitored sections of the grid.
I also see AI playing a larger role in integrating flexible assets in our homes and businesses, increasing the effectiveness of renewable energy sources and optimising demand to available supply in both normal and emergency conditions.
These innovations will further strengthen grid reliability and ensure utilities can meet evolving safety and efficiency demands.
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