AI as a Game Changer for the Energy and Utilities Industry 

This year, leading experts from the energy industry once again gathered at the SAP for Energy & Utilities Conference—this time in Toulouse in the south of France. Throughout the three conference days featuring keynotes and case studies, AI was an omnipresent topic. 

AI works when the foundation is right 

The energy and utilities sector is investing heavily in AI. Business leaders worldwide are embracing artificial intelligence to increase efficiency, unlock new business models, and prepare for the energy transition. A successful proof of concept is often the first milestone—but it marks only the beginning. The real challenge lies in scaling pilot projects across the entire organization. 

In this context, the time and effort required for a full implementation is frequently underestimated. Around six months are needed to build a robust data foundation. A further 12 months pass before initial results manifest in the form of a measurable return on investment. Large-scale rollout can take another three years. The reasons for this are manifold: 

• Unrealistic expectations: Many people use AI in their daily lives for simple tasks and expect similarly seamless effects in complex enterprise environments. 
• Legacy infrastructure: Historically grown system landscapes cannot be transformed overnight. 
• Regulatory complexity: In regulated industries such as electricity, gas, and water supply, compliance requirements are particularly high. They must be factored into every architectural decision from the very beginning. 
• Lack of AI-specific talent: What is needed are people who genuinely understand both the business and AI. This bridge between IT and the business side will become increasingly important in the future. 
• Organizational change management: Technology alone is not enough. Organizational transformation is and remains the decisive success factor. 

From AI hype to real value 

Building a new application is only the first step. On the path to scaling, lifecycle management, identity and access management, security, compliance, and governance must all be consistently taken into account. Release management, testing, and continuous improvement processes add further complexity. “The companies that invest in the right foundation today will benefit from AI to its full extent tomorrow,” says Andre Bechtold, president and head of SAP Industries & Experiences. 

For companies, this means overcoming fragmented data silos and developing an integrated data strategy. Legacy systems must be integrated into a modern data and AI platform on which AI models can genuinely create value. Torsten Welte, head of Energy & Natural Resources Industries at SAP, summarizes it as follows: “AI is fundamentally transforming the energy industry. The business must understand what is technologically possible. And IT must understand what the business needs.” 

SAP Business Suite can provide the essential foundation for this. AI is already natively embedded in the suite in the form of Joule. This can open up concrete use cases for the energy industry: in the area of asset management and predictive maintenance, utilities can proactively manage assets and grids before disruptions occur. The Utilities Customer Self-Service Agent, in turn, enables 24/7 self-service for customers and can reduce service costs by up to 90%. 

Distributed energy requires intelligent networking 

The topic of distributed energy resources (DER) remains of central importance. In the past, energy flowed in only one direction: from the power plant to consumers. In the future, it will be bidirectional. Consumers that generate their own energy will actively feed it back into the grid. 

DER describes precisely this principle: the generation of electricity through millions of decentralized resources such as solar panels, EV chargers, heat pumps, and battery storage systems by consumers and so-called prosumers. These assets generate vast amounts of data. Their orchestration represents one of the key challenges of the energy transition. 

The SAP Distributed Energy Resources solution provides a platform for a single source of truth: technical assets, commercial contracts, and customer data are brought together in a coherent data model. This helps create the foundation for new business models such as smart tariffs, dynamic pricing, energy sharing, and demand response.

SAP consistently relies on a growing partner network built around its own data platform. Markus Bechmann, global VP and co-head of Industry Business Unit Utilities at SAP, describes it this way: “Dynamic pricing and smart tariffs are no longer distant concepts. They are the business models of tomorrow. With SAP, energy providers already have the technological foundation today to seize these opportunities.” 

SAP Experience Centers: experiencing AI, not just discussing it 

To make AI tangible, SAP Experience Centers offer visitors the opportunity to experience AI in real-world scenarios beyond classic demo environments. One central example is the SAP Energy Park in Walldorf. Using real infrastructure on the campus, SAP demonstrates how the company itself is implementing the energy transition. This includes e-mobility, intelligent asset management, and energy communities. 

A new chapter for the energy industry 

The SAP for Energy & Utilities Conference in Toulouse has once again demonstrated that AI in the energy industry is no longer a topic for the future. However, the path from pilot project to company-wide transformation requires more than technological enthusiasm. To meet the challenges of the energy transition, what is needed—alongside technological innovation—is a solid foundation of data, processes, and organization.