In a talk at the Edison Electric Institute, NVIDIA founder and CEO Jensen Huang made a pointed observation:
“The greatest impact and return is in applying AI in the delivery of energy over the grid.”
Utility companies power our homes, keep the water running, and supply the energy that is needed to keep society functioning. Yet, most of this critical infrastructure has aged significantly over the years, sustained only through reactive maintenance and stretched workforces.
Enter AI and the promise of building resilience into utility infrastructure.
AI for utilities
Artificial Intelligence (AI) refers to systems that can carry out tasks independently – analysis of large volumes of data, identification of patterns (that humans typically cannot see), and even taking autonomous actions without human involvement.
In the utilities sector, AI can be applied across the value chain. For energy resources, AI can help with predicting demand fluctuations, dynamically balancing grid loads, and detecting faults in equipment before they cause outages. For water utilities, AI works alongside smart sensors across the network to monitor pipeline health continuously and in real time. It can even flag contamination risks early and pinpoint leakage points. On the customer operations side, AI systems can handle billing queries and service requests round the clock.
Technologies that help power AI in utilities
There are several technologies that power AI in utilities and make it viable and valuable.
Machine learning and predictive analytics: Proactive intervention is possible in utilities due to the power of machine learning and predictive analytics. These machine learning models look at past data and also current, real-time data to forecast demand and predict equipment failures.
Internet of Things (IoT) and smart sensors: Grid sensors and smart meters are used across utility infrastructure to generate streams of data that are fed into AI-models. The data is analysed by these AI models and is used to detect and predict issues in the infrastructure before they escalate.
Digital twins: Digital twins are exact virtual replicas of real-world assets, such as transformers, pipelines, or entire networks. They bring with them the benefit that they can be used for testing, without touching any live infrastructure. Layered over a digital twin, AI recognizes patterns and predicts failures, delivering actionable insights to future infrastructure planners. Combined with AI, digital twins enable more accurate forecasting and infrastructure planning.
Natural Language Processing (NLP): In customer service, NLP powers chatbots, virtual agents, and automated outage communication systems. These can handle thousands of customer queries while freeing up humans to handle the more complex, high-empathy interactions.
Advantages of using AI in utilities: Using AI in utilities brings with it several compelling advantages. Let us look at a few of them.
Improved grid reliability: This is one of the foremost advantages of using AI in utilities. AI can predict vulnerabilities in the utilities infrastructure before they compound into bigger problems and outages. AI also helps prioritise restoration activities based on impact and severity, making it critical to ensure the long-term reliability and stability of utility infrastructure.
Operational efficiency: When repetitive operational tasks are automated with the help of AI, employees can focus on higher value tasks that customer engagement, strategic planning and critical infrastructure management.
Better renewable energy integration
Renewable energy sources such as solar and wind are vital to the future of sustainable energy. They are dependent on weather conditions - a sudden drop in wind speed or unexpected cloud cover can significantly reduce power generation within minutes, making it difficult for utilities to maintain a stable balance between electricity supply and demand. AI can predict such fluctuations with great accuracy by analysing large volumes of historical and real-time data. As renewable energy adoption grows, AI can optimize its distribution across the grid, enhance its overall efficiency and improve sustainability outcomes.
At ReNew, one of India’s largest renewable energy and decarbonization companies, leveraging AI has improved the electricity output by up to 1.5% from existing solar and wind installations. It has also streamlined maintenance, demonstrating AI's potential to enhance efficiency and reduce costs.
Improved customer experience
Customers these days expect seamless, responsive experiences and service. AI-powered chatbots and virtual assistants are well-equipped to resolve issues, leading to enhanced customer experience and better customer engagement.
Challenges in adopting AI in utilities
Adopting AI in Utilities is not without its challenges. Many of the utilities operate on aging infrastructure that is not really built for incorporating AI. Moreover, the AI systems will only be as effective as the data that they learn from and consume. If the data is fragmented or siloed, building high quality data ecosystems will be an uphill task. Cybersecurity is another major concern. Utilities must have proper governance and access controls in place to protect against potential cyber threats.
It is also seen that workforce readiness for adopting AI in utilities is a hurdle. There is a skills readiness issue and cultural resistance when workers fear a threat to their jobs with AI. Moreover. while piloting AI in smaller projects is relatively easy, scaling it across the entire organization is another matter altogether. The leap from proof of concept to operational reality requires sustained commitment from leadership.
AI in utilities should be built keeping the human in mind – whether it is the frontline worker, the field engineer or the end customer. When the human focus is maintained, the use of AI becomes a force to reckon with. With AI, operators can make improved decisions, engineers are dispatched with better information and data at their fingertips and customers receive more empathetic service.
How Infosys BPM can help
Utility operations are anything but predictable. They surge with seasons, buckle under outages, shift with rate changes, and field calls from customers who won't wait. Infosys BPM's energy and utility business process services are built for exactly this reality, combining GIS data management, AI-powered forecasting, master data management, and generative AI to help energy companies cut costs, drive efficiency, and stay focused on what matters most.
