Snowflake Positions Energy as Proving Ground for Operational AI

Energy companies in the AI era are dealing with unprecedented volumes of operational data, all while being held back by legacy infrastructure. Many of the operations now depend on analytics including predictive maintenance, grid modernization, and renewal integration. However, these companies still struggle to bring everything together, slowing everyday decisions, complicating coordination across teams. Over time, this leads to inefficiency and missed opportunities.

Enterprise data platform company Snowflake has announced new Energy Solutions to enable power, utilities, and oil and gas organizations to build a trusted data foundation for AI. The aim is to offer one shared cloud platform where users can securely connect data across IT, OT, and IoT systems. The company claims this will help modernize infrastructure and improve efficiency. It also expects this platform to accelerate progress toward a more reliable and lower-carbon future.

It is not a single boxed product. Instead, it is positioned as a combination of Snowflake’s core data platform, industry-specific datasets, and more than 30 partner-built solutions that run natively on the AI Data Cloud. 

“Data is the control plane for the future of energy,” said Fred Cohagan, Global Head of Energy, Snowflake. “Whether it’s keeping the grid secure, protecting critical assets, or balancing supply and demand in volatile markets, energy companies need a trusted data foundation that can activate AI everywhere. 

“Snowflake is helping the world’s energy leaders modernize how they manage data and harness AI to democratize insights so that anyone, not just data scientists, can act on intelligence in real time. This shift allows organizations to do more with less, optimize existing assets, and deliver stronger sustainability and shareholder outcomes.”

The launch of Energy Solutions signals Snowflake’s ambition to move deeper into operating systems, and not just enterprise analytics. With the growing reliance on AI-backed decision-making, the energy sector is emerging as a proving ground for how data platforms can support real-time planning and infrastructure management. 

Snowflake is also positioning the platform as a foundation for day-to-day energy operations. It goes beyond central data access into more practical workflows across the energy lifecycle. Snowflake says the platform supports critical energy use cases including asset performance monitoring, geospatial analysis, grip optimization, and virtual power plant support. 

Much of Snowflake’s operational reach is coming through its partners. Several vendors are building directly on the platform to contribute specialized tools and industry expertise that Snowflake does not develop itself.

For example, Itron is delivering advanced grid planning capabilities on Snowflake, allowing utilities to model grid performance years into the future using high-resolution power flow analysis. SAP is enabling energy companies to combine SAP finance and supply chain data with operational and field data on Snowflake.

Agentic GIS platform CARTO brings geospatial analytics into the platform. This helps teams visualize infrastructure and geographic risk without moving data across systems. Siemens plugs in its Industrial Edge integration to help bring data from decentralized industrial assets into Snowflake, giving energy and industrial operators greater visibility into operations. 

Siemens is also introducing new capabilities such as “Talk to Your Data,” which allow teams to interact with operational data using natural language to gain faster insight into performance, maintenance, and operational issues.

Snowflake shared several customer comments to showcase the impact of this platform. 

“Meeting our customers’ expectations for affordable and reliable energy depends on simplifying our data landscape and enabling intelligence across every part of our business,” said David Leach, Senior Vice President and Chief Data & Analytics Officer at PG&E.

            (vectorfusionart/Shutterstock)

“Snowflake helps us consolidate siloed legacy environments, govern sensitive regulatory and operational data, and deliver timely analytics to teams in the field and in the control center,” continued Leach. He shared that this foundation is helping them “improve reliability and affordability of service for our customers.”

Snowflake is not the only company working on energy data platforms. Large cloud providers like AWS, Microsoft Azure, and Google Cloud also offer tools for energy analytics. Other industrial companies such as Siemens, Schneider Electric, and GE Vernova continue to lead in operational systems and asset management, and are keen to tap into operational AI. 

Smaller vendors are also building AI tools for grid planning and forecasting. Snowflake’s advantage is that it already sits inside many enterprise data environments. It has a way to connect operational systems and partner applications on one shared platform. This sort of access to energy companies is not many other data platforms have. 

However, the opportunity is not without some challenges. Snowflake faces competition from major cloud providers. It must also contend with the typical slow pace of modernization inside many energy organizations. Also, moving critical operations off legacy systems takes time, and coordinating a large partner ecosystem adds complexity. If it is able to overcome these challenges, then it can push further in operational AI. 

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