How AI and Automation Are Transforming India's Energy Landscape The future of energy is now, in control rooms, data centers, solar farms, and substations across the country. Behind the traditional methods, a different kind of engine is running the show—one that learns, adapts, and improves, without ever needing a break.
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India's energy sector is undergoing a revolution. It isn't driven by massive new power plants or flashy green projects, but by intelligent machines and algorithms that never sleep. AI and automation are now central to how the country plans, produces, and delivers energy.
For decades, India's challenge wasn't just energy production, but how to make it reliable, clean, and future-ready. That's changing fast. Companies across the sector are turning to digital technologies for survival in a new era of decentralized, renewable energy.
"AI and automation are key to unlocking the next phase of growth in India's renewable energy sector," said Akarsh Hebbar, president, Vedanta Limited. The company has seen first-hand how these technologies can optimize operations. "One such application is the use of AI/ML algorithms to analyse performance data across our renewable energy assets. These systems help optimise energy utilization and predictive maintenance enabling timely interventions that enhance performance, lower costs, support long-term sustainability and maximize safety," Hebbar said.
Hebbar points to breakthroughs at Hindustan Zinc, where robotic systems maintain solar panels and transmit anomaly data in real-time. AI models track asset health and performance 24/7 using computer vision. The main goal is to create a system that can respond, adapt, and even learn without constant human input. "We are also integrating AI/ML technologies to ensure consistent, smart, cost-effective and sustainable energy delivery," he added.
This shift goes far beyond one company. Jaspreet Singh, partner at Grant Thornton Bharat LLP, said firms like Tata Power and ReNew Power are now using AI to forecast solar and wind output, i.e., data that feeds directly into grid planning. "AI models improve the accuracy of weather and energy production predictions, which is crucial for integrating variable renewable sources into the electrical grid," Singh explained.
Predictive maintenance and real-time data analysis are helping utilities avoid costly breakdowns and reduce energy waste. Smart grids powered by AI are emerging as critical infrastructure, balancing supply and demand in real time, integrating rooftop solar into the national grid, and preventing blackouts before they start. But equally important is India's deep bench of AI talent and supportive government policies. These make it possible to embed intelligence into everything from EV chargers to battery systems, transforming how energy is consumed, stored, and traded.
Pooja Patwari, AI lead at Avaada Group, said that hitting India's goal of 500 GW of non-fossil capacity by 2030 won't happen without full-scale digital transformation. "To realize this vision, digital transformation through AI and automation is not just beneficial—it is essential," she said. Her team is deploying digital twins—virtual replicas of physical energy systems—to simulate grid behavior and make real-time adjustments. Predictive tools extend the life of solar and wind infrastructure. And automation is managing data from thousands of sensors across solar parks, making centralized oversight more responsive and decentralized control more practical.
Looking ahead, the convergence of AI and IoT (referred to as AIoT) is expected to dominate. Edge devices deployed at wind and solar farms will process and act on data locally, cutting response times. Blockchain will enable peer-to-peer energy trading. Generative AI will help design more efficient solar layouts. AI will even optimize the production of green hydrogen, dynamically adjusting electrolyzer operations based on renewable input and market pricing.
Perhaps most significantly, the digital systems being deployed today are teaching India's energy sector how to be proactive rather than reactive. From real-time demand forecasting to automated grid stabilization, AI is rewriting the rules of energy management.
"We expect AI and IoT technologies to significantly reshape the energy landscape making it more viable, reliable and compatible," Hebbar said. What's emerging is a system not only cleaner and smarter but increasingly self-aware.
