Infosys is leveraging artificial intelligence to address the inherent intermittency of renewable energy sources like solar and wind, a persistent challenge for utility companies striving to integrate clean power into their grids. By improving weather forecasting and grid management, AI is enabling more reliable and predictable output from renewable sources, transforming them into more stable components of the energy landscape. The company’s work in this area includes over 60 AI projects within the energy sector, demonstrating a significant commitment to advancing sustainable energy through technology. These initiatives are not only enhancing the reliability of renewable energy but also delivering substantial financial and operational benefits to utility providers.
The application of AI in the energy sector extends beyond simple forecasting, touching on asset management, operational efficiency, and customer service. For one major North American utility, Infosys deployed an AI solution that improved load forecasting accuracy to 95%, resulting in tens of millions of dollars in savings on infrastructure investments and a reduction in unplanned outages to less than 1%. This level of precision allows for more strategic grid investments and upgrades, ensuring that resources are allocated where they are most needed. The broader trend in the North American energy sector reflects a rapid adoption of AI, with 81% of utilities already using the technology to optimize grids, enhance safety, and meet rising consumer demands for reliable power.
Transforming Grid Management with AI
The electrical grid in the United States is an incredibly complex system, and its modernization is a critical step in the transition to a clean energy economy. AI is proving to be a powerful tool in this transformation, offering solutions for grid planning, permitting, operations, and resilience. By using AI-accelerated power grid models, utilities can conduct more effective capacity and transmission studies, ensuring the grid can handle the fluctuating input from renewable sources. These models can also assist in forecasting energy demand, which allows for more proactive planning and smoother integration of renewables. The U.S. Department of Energy has identified AI as a key technology for improving grid management and has highlighted its potential to be immediately deployed in several high-priority areas.
The Role of the Common Information Model (CIM)
A key component of Infosys’ successful AI deployment for the North American utility was the use of a Common Information Model (CIM) utility model. The CIM is a global standard for structuring and exchanging utility data, providing a unified way to model assets, operations, and processes. This standardization is crucial for ensuring interoperability between different systems and vendors, which simplifies data integration and reduces complexity. By using a common model, utilities, vendors, and researchers can more easily collaborate on developing advanced applications for managing the smart grid of the future. The CIM is maintained by the International Electrotechnical Commission (IEC) and is widely used for data exchange in bulk transmission power systems.
Infosys’ AI Strategy and Ethical Considerations
Infosys emphasizes that an AI strategy should not be a separate initiative but rather an integral part of a company’s overall business strategy. Their approach is built on five key pillars: tech incubation, building a robust platform and ecosystem, responsible AI, focusing on high-value use cases, and creating reusable solutions. This framework is designed to build a scalable and sustainable AI foundation that can be applied across an entire organization. To ensure successful execution, Infosys establishes dedicated “strategy and execution pods” that bring together experts from technology, domain, and business to build, test, and scale solutions quickly. This agile approach allows the company to adapt to the constantly evolving landscape of AI technology and regulations.
A Commitment to Responsible AI
As AI becomes more powerful and prevalent, the ethical implications of its use are a growing concern. Infosys has placed a strong emphasis on responsible AI, advocating for systems that are fair, transparent, and compliant with industry standards and regulations. The company has implemented strong governance frameworks to oversee the development and use of AI, ensuring that ethical considerations are embedded from the very beginning. This includes regular monitoring to detect any performance drifts or unintended biases in their models. By involving cross-functional teams from legal, HR, and compliance, Infosys aims to incorporate diverse perspectives into its AI governance process. The company also prioritizes educating its employees on the workings and risks of AI to empower them to use the technology responsibly.
The Growing Market for AI in Renewable Energy
The global market for AI in renewable energy is experiencing significant growth, with projections showing it will surge from $0.6 billion in 2022 to $4.6 billion by 2032. This represents a compound annual growth rate (CAGR) of 23.2%, indicating a strong and sustained investment in AI-driven solutions for the renewable energy sector. The Asia Pacific region is leading this growth, with its market share expected to grow from $4.8 billion in 2023 to $44 billion by 2032. The increasing adoption of renewable energy technologies is a primary driver of this market expansion, as AI plays a crucial role in optimizing the production and integration of clean power.
Real-World Impacts and Future Outlook
The practical applications of AI in the energy sector are already yielding significant results. For the North American utility that partnered with Infosys, the ability to perform on-demand, long-term grid forecasting has been a game-changer. The AI-powered solution, which utilizes open-source machine learning models and a scalable cloud architecture, can process data for 650,000 transformers in just 24 hours, a task that previously took 85 hours for only 6,500 assets. This massive increase in speed and scale allows for more agile responses to regulatory needs and more precise investments in grid infrastructure. As AI technology continues to advance, its role in the energy sector is expected to expand, with generative AI showing promise in areas like engineering design simulation, automated reporting, and customer service. The ongoing development of AI will be critical in balancing the goals of sustainability and performance in a rapidly changing energy market.