This year, leading experts from the energy industry met again at the SAP for Energy & Utilities Conference – this time in Toulouse in the south of France. During the three days of the conference with keynotes and case studies, the topic of AI was omnipresent.
AI works when the foundation is right
The Energy & Utilities sector is investing heavily in AI. Executives around the world are turning to artificial intelligence to increase efficiency, develop new business models and prepare for the energy transition. A successful proof of concept is often the first milestone, but it only marks the beginning. The real challenge lies in scaling pilot projects across the entire company.
The time and effort factors of a complete implementation are often underestimated. It takes around six months to build a reliable data foundation. Another twelve months pass before the first results are reflected in the form of a measurable return on investment. Large-scale scaling can also take another three years. The reasons for this are varied:
- Inflated expectations.Many people use AI in everyday life for simple tasks and expect similarly smooth effects in complex corporate environments.
- Legacy infrastructure.Historically developed system landscapes cannot be transformed overnight.
- Regulatory complexity.Compliance requirements are particularly high in regulated industries such as electricity, gas and water supply. They must be taken into account right from the start in every architectural decision.
- Lack of AI-specific talent.What is needed are people who really understand both business and AI. This bridge between IT and the department 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 added value
Building a new application is just the first step. On the way to scaling, lifecycle management, identity & access management, security, compliance and governance must be consistently considered. Added to this are release management, testing and continuous improvement processes. “If you invest in the right foundation today, you will fully benefit from AI tomorrow,” says Andre Bechtold, President and Head of SAP Industries & Experiences.
For companies, this specifically means overcoming fragmented data silos and developing an integrated data strategy. Legacy systems need to be integrated into a modern data and AI platform on which AI models actually add value. Torsten Welte, Head of Energy & Natural Resources Industries, sums it up like this: “AI is fundamentally changing the energy industry. Business must understand what is technologically possible. And IT must understand what the business needs.”
The SAP Business Suite can provide the decisive foundation for this. AI is already natively embedded in the suite in the form of Joule. This opens up specific areas of application for the energy industry: In the area of asset management and predictive maintenance, utility companies are able to proactively manage systems and networks 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 percent.
Decentralized energy needs intelligent networking
The topicDistributed Energy Resources (DER)remains of central importance. Previously, energy only flowed in one direction: from the power plant to the consumers. In the future it will be bidirectional. Consumers who generate energy themselves actively feed it into the grid.
DER describes exactly this principle: the generation of electricity by millions of decentralized resources such as solar systems, EV chargers, heat pumps and battery storage for consumers and so-called prosumers. These assets generate huge amounts of data. Their orchestration represents one of the central challenges of the energy transition.
The SAP solution for Distributed Energy Resources offers a platform as a single source of truth: technical assets, commercial contracts and customer data are brought together in a coherent data model. This creates the basis for new business models such as smart tariffs, dynamic pricing, energy sharing and demand response. SAP consistently relies on a growing partner network around its own data platform. Markus Bechmann, Global VP and Co-Head Industry Business Unit Utilities, describes it like this: “Dynamic pricing and smart tariffs are no longer distant concepts. They are the business models of tomorrow. With SAP, energy suppliers already have the technological basis to take advantage of these opportunities.”
Experience Centers: Experience AI, not just discuss it
To make AI tangible, SAP provides a series of Experience Centers in which AI can be experienced in real scenarios beyond classic demo environments. A key example is the SAP Energy Park in Walldorf. Using real infrastructure on campus, SAP shows how the company is implementing the energy transition itself. These include e-mobility, intelligent asset management and energy communities.
A new chapter for the energy industry
The SAP for Energy & Utilities Conference in Toulouse showed once again that AI in the energy industry is no longer a topic of the future. But the path from pilot to company-wide transformation requires more than technological enthusiasm. In order to overcome the challenges of the energy transition, in addition to technological innovation, a solid foundation of data, processes and organization is needed.
