<p>Renewable energy is booming. In 2024, the world added a record 585 GW of clean power, and grids everywhere are stepping up to welcome the surge. India mirrors this momentum: its renewable capacity crossed 234 GW in June 2025, putting the nation in a strong position to save fuel and cut carbon at scale. </p><p>The next leap is smarter orchestration that turns torrents of weather, market, and asset data into real-time decisions. When utilities trade static spreadsheets for digital twins and AI-driven dispatch, they can trim curtailment fees, ease local bottlenecks, and unlock the full value of every new megawatt, keeping solar parks productive and neighbourhood feeders reliably green.</p>.<p>A well-managed power network requires detailed knowledge of its infrastructure, including weather intelligence and forecasts that help reduce costs for both solar and wind energy, with real-time Supervisory Control and Data Acquisition (SCADA) combined with AI models. GenAI platforms swiftly summarise lengthy tender documents, identifying potential risks and opportunities, while reducing review times from days to mere hours. Integrating AI-enabled system enhancements via cloud computing into real-time operations strengthens baseline systems, resulting in greater operational efficiency and accuracy.</p>.<p>Effective technology integration clearly impacts energy distribution efficiency and profitability for ESCOMs. Renewable Energy Sources (RES) leveraging advanced technologies have successfully reduced transmission losses and improved operational performance. India has very ambitious plans to add nearly 300 GW of clean energy between now and 2030, which means adding nearly<br>60 GW every year. These insights underline the critical role of AI and technology integration in achieving India’s ambitious RE targets. </p>.<p>At CoP28, global leaders agreed on the goal of rapidly scaling clean energy to achieve a tripling of RE capacity and a doubling of energy efficiency improvements by 2030. The Statistical Review of World Energy 2025 demonstrates that despite unprecedented growth in RE over the past decade, the share of fossil fuels has hardly been dented.</p>.<p>Asia is home to more than half the world’s population and is now responsible for over half of global primary energy consumption. The energy growth curve has been steep. The Asia-Pacific region accounts for nearly half of the world’s primary energy use, driven by rapid economic growth, a large population, and accelerating urbanisation. Home to around 60% of the global population — and some of the largest and fastest-growing economies such as China, India and Indonesia — demand for energy has surged and is projected to continue rising in the coming decades.</p>.<p>The region is now the leading contributor to annual greenhouse gas emissions, with a 51% share of global carbon emissions. Within Asia, India is a major hotspot of economic growth. Unfortunately, this growth has hitherto been heavily reliant on fossil fuels. As the country seeks to scale up its economy towards developed-nation status, it must also modernise and decarbonise its vast energy system, which is set to expand rapidly in line with economic growth metrics.</p>.<p>It is in this context that AI assumes vital importance for India. With the advent of Generative AI, new possibilities have begun to emerge — enhancing efficiency, optimisation, and sustainability with far-reaching effects. The complexities of renewable energy production make the sector well-suited to AI and GenAI applications. Machine learning and data processing capabilities are key to improving the efficiency and reliability of RE systems.</p>.<p>The overall expansion trajectory of AI in clean energy production can be characterised in four broad stages: early AI applications in renewables; growth and expansion; the emergence of GenAI and <br>its effects across the value chain; and the convergence of AI with quantum computing (QC) and high-performance computing (HPC).</p>.<p>Modern AI, in conjunction with other technologies, has opened up a world of new possibilities, though not without challenges. AI systems are prone to adversarial attacks, which exploit their heavy reliance on data and can disrupt the reliability of energy systems. The rapid growth in <br>demand for AI specialists has created a recruitment bottleneck, with a significant shortage of skilled professionals in both the AI and renewable energy sectors.</p>.<p>Regulatory frameworks for responsible AI deployment are essential and are slowly taking shape, but they continue to face persistent challenges. It becomes crucial for governments and regulatory agencies to evolve and establish precise directives for deploying strong AI applications.</p>.<p>However, the possibilities offered by AI and other modern technologies are immense, especially in dealing with the effects of climate change. AI and QC will be demanding frontiers of technology. The country’s recent track record in digital innovation is impressive. We have a unique opportunity: a large market, a large-scale carbon challenge and a vast, competent talent pool that must be harnessed to lead the way for the world.</p>.<p><em>(The writer is research scholar, California Public University, US)</em></p>.<p><em>Disclaimer: The views expressed above are the author's own. They do not necessarily reflect the views of DH.</em></p>
<p>Renewable energy is booming. In 2024, the world added a record 585 GW of clean power, and grids everywhere are stepping up to welcome the surge. India mirrors this momentum: its renewable capacity crossed 234 GW in June 2025, putting the nation in a strong position to save fuel and cut carbon at scale. </p><p>The next leap is smarter orchestration that turns torrents of weather, market, and asset data into real-time decisions. When utilities trade static spreadsheets for digital twins and AI-driven dispatch, they can trim curtailment fees, ease local bottlenecks, and unlock the full value of every new megawatt, keeping solar parks productive and neighbourhood feeders reliably green.</p>.<p>A well-managed power network requires detailed knowledge of its infrastructure, including weather intelligence and forecasts that help reduce costs for both solar and wind energy, with real-time Supervisory Control and Data Acquisition (SCADA) combined with AI models. GenAI platforms swiftly summarise lengthy tender documents, identifying potential risks and opportunities, while reducing review times from days to mere hours. Integrating AI-enabled system enhancements via cloud computing into real-time operations strengthens baseline systems, resulting in greater operational efficiency and accuracy.</p>.<p>Effective technology integration clearly impacts energy distribution efficiency and profitability for ESCOMs. Renewable Energy Sources (RES) leveraging advanced technologies have successfully reduced transmission losses and improved operational performance. India has very ambitious plans to add nearly 300 GW of clean energy between now and 2030, which means adding nearly<br>60 GW every year. These insights underline the critical role of AI and technology integration in achieving India’s ambitious RE targets. </p>.<p>At CoP28, global leaders agreed on the goal of rapidly scaling clean energy to achieve a tripling of RE capacity and a doubling of energy efficiency improvements by 2030. The Statistical Review of World Energy 2025 demonstrates that despite unprecedented growth in RE over the past decade, the share of fossil fuels has hardly been dented.</p>.<p>Asia is home to more than half the world’s population and is now responsible for over half of global primary energy consumption. The energy growth curve has been steep. The Asia-Pacific region accounts for nearly half of the world’s primary energy use, driven by rapid economic growth, a large population, and accelerating urbanisation. Home to around 60% of the global population — and some of the largest and fastest-growing economies such as China, India and Indonesia — demand for energy has surged and is projected to continue rising in the coming decades.</p>.<p>The region is now the leading contributor to annual greenhouse gas emissions, with a 51% share of global carbon emissions. Within Asia, India is a major hotspot of economic growth. Unfortunately, this growth has hitherto been heavily reliant on fossil fuels. As the country seeks to scale up its economy towards developed-nation status, it must also modernise and decarbonise its vast energy system, which is set to expand rapidly in line with economic growth metrics.</p>.<p>It is in this context that AI assumes vital importance for India. With the advent of Generative AI, new possibilities have begun to emerge — enhancing efficiency, optimisation, and sustainability with far-reaching effects. The complexities of renewable energy production make the sector well-suited to AI and GenAI applications. Machine learning and data processing capabilities are key to improving the efficiency and reliability of RE systems.</p>.<p>The overall expansion trajectory of AI in clean energy production can be characterised in four broad stages: early AI applications in renewables; growth and expansion; the emergence of GenAI and <br>its effects across the value chain; and the convergence of AI with quantum computing (QC) and high-performance computing (HPC).</p>.<p>Modern AI, in conjunction with other technologies, has opened up a world of new possibilities, though not without challenges. AI systems are prone to adversarial attacks, which exploit their heavy reliance on data and can disrupt the reliability of energy systems. The rapid growth in <br>demand for AI specialists has created a recruitment bottleneck, with a significant shortage of skilled professionals in both the AI and renewable energy sectors.</p>.<p>Regulatory frameworks for responsible AI deployment are essential and are slowly taking shape, but they continue to face persistent challenges. It becomes crucial for governments and regulatory agencies to evolve and establish precise directives for deploying strong AI applications.</p>.<p>However, the possibilities offered by AI and other modern technologies are immense, especially in dealing with the effects of climate change. AI and QC will be demanding frontiers of technology. The country’s recent track record in digital innovation is impressive. We have a unique opportunity: a large market, a large-scale carbon challenge and a vast, competent talent pool that must be harnessed to lead the way for the world.</p>.<p><em>(The writer is research scholar, California Public University, US)</em></p>.<p><em>Disclaimer: The views expressed above are the author's own. They do not necessarily reflect the views of DH.</em></p>
