How AI Changes The Energy Industry

AI is changing how the world produces, manages, and consumes energy. It optimizes energy use, significantly reducing energy consumption and costs and making the future greener and more resilient. AI also brings significant benefits to both the top and bottom corporate lines, a group of energy experts said.

"Various applications of AI for optimal energy use can be seen, from energy-efficient buildings to smart grids," Kumar Parakala, President of GHD Digital, told International Business Times. "It helps improve equipment performance, detect anomalies, provide recommendations on consumption patterns, usage, and generation, and can pinpoint which facilitates more efficient resource allocation and enables more sustainable practices."

Moreover, he sees the growing use of generative AI algorithms providing valuable insight to optimize energy generation and distribution while promoting innovation and sustainability.

"Generative AI can optimize the design in the conceptual phase to balance aesthetic appeal, functionality, and environmental impact—imagine buildings that are visually striking, energy-efficient, and purpose-built," he added. "It can also elevate new designs beyond the current trends."

Christina Shim, head of Sustainability Software at IBM, sees AI as a critical part of the energy transition for developing, managing, and maintaining complex, reliable grids.

"A key ingredient in a functioning energy industry is data—for producing, forecasting, load balancing, and real-time management," she said, adding, "AI can supercharge what is possible with that data. It's already being discussed at the board and C-Suite levels, but it's not being adopted quickly enough."

Lennart Hinrichs, Executive Vice President and General Manager of Americas at TWAICE, agrees. "AI will be a tool to address key challenges in predicting demand but also making supply more resilient," he said. "With AI, the issues surrounding unplanned downtime of assets (e.g., battery energy storage systems) can be mitigated by predictive maintenance and optimized operation."

Supratik Chaudhuri, Power & Utilities Lead at Publicis Sapient, provides further insight into the segments of the industry that would be mostly affected by AI. "Key impact areas include smarter grid management, where AI uses data from sensors and smart meters for more efficient power distribution and renewable energy integration," he explains. "Predictive maintenance is another crucial development where AI can predict and prevent failures by analyzing equipment data, reducing maintenance costs, and improving plant efficiency."

Shim looks further into how AI can make renewable energy producers more reliable by predicting the weather and supply and demand. "That means utilities will have a better sense of how much renewable power will be generated at any time in the future and also how much will be needed by customers," she added.

She points to the example of Danish utility Andel, which uses AI to help coordinate Copenhagen's microgrids, primary grid, and "load balance" power with minimal disruptions, and the case of Indian utility Mercados, which uses AI-infused software to improve the accuracy of its demand predictions from 85 to 98 percent.

"Because India requires states to procure power beforehand, these improved demand forecasts meant less over-purchasing, which wasted precious power resources, and less under-purchasing, which would have risked other problems," Shim added.

Meanwhile, she sees AI boosting the energy industry's top and bottom lines. "For those who use it effectively, it will help to generate revenue and growth," she stated. "It will also be a competitive differentiator by boosting reliability, cost-effectiveness, and productivity—as well as managing bottom-line risks."

Chaudhuri provides further insight into AI's financial impact on the energy sector. "It enables companies to boost revenue through improved resource management and innovative services like dynamic pricing, which adjusts in real-time to demand," he stated. "Simultaneously, AI-driven cost reductions, through predictive maintenance and operational optimizations, enhance profitability and competitiveness."

Jimmie Lee, the developer of the AI Chatbot Platform Aeona, sees AI optimizing energy use, leading to significant reductions in energy consumption and costs.

"In the Long Term, I can forecast Full integration with renewable energy sources, widespread use in exploration and resource identification, and comprehensive AI-driven operational optimizations," he stated.