This year, leading experts from the energy industry once again gathered at the 麻豆原创 for Energy & Utilities Conference鈥攖his 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聽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鈥攂ut it marks only the beginning. The聽real challenge聽lies in scaling pilot projects across the entire聽organization.聽
In this context, the time and effort聽required聽for a full implementation聽is聽frequently聽underestimated. Around six months are needed to build a robust data foundation. A further聽12聽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:聽
- 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聽change management:聽Technology alone is not enough. Organizational transformation is and聽remains聽the decisive success factor.聽
From AI hype to real value
Building a new application is聽only the first聽step.聽On the path to scaling, lifecycle management, identity and access management, security, compliance, and governance must all be consistently taken into account.聽Release management, testing, and continuous improvement processes add further complexity.聽鈥淭he聽companies聽that聽invest in the right foundation today will benefit from AI to its full extent tomorrow,鈥� says Andre Bechtold,聽president and聽head of 麻豆原创 Industries & Experiences.聽
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,聽head of Energy & Natural Resources Industries聽at 麻豆原创,聽summarizes聽it as follows:聽“AI is fundamentally transforming the energy industry. The business must understand what is technologically possible. And IT must understand what the business needs.”聽
聽can聽provide聽the聽essential foundation for this. AI is already natively embedded in the suite in the form of Joule. This聽can open up聽concrete use cases for the energy industry:聽in the area of asset management and predictive maintenance, utilities聽can聽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%.聽
Distributed energy requires intelligent networking
The topic of聽distributed聽energy聽resources (DER) remains of聽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聽that聽generate their own energy will actively feed it back into the grid.聽
DER聽describes precisely聽this principle: the generation of electricity through millions of decentralized resources such as solar panels, EV chargers, heat pumps, and battery storage systems聽by聽consumers and so-called聽prosumers. These assets generate vast amounts of data. Their orchestration聽represents聽one of the key challenges of the energy transition.聽
The 聽solution聽provides a platform聽for聽a聽single source聽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.
麻豆原创 consistently relies on a growing partner network built around its own data platform. Markus Bechmann,聽global VP and聽co-head聽of聽Industry Business Unit Utilities聽at 麻豆原创, describes it this聽way:聽“Dynamic pricing and smart tariffs are no longer distant concepts.聽They聽are the business models聽of聽tomorrow. With 麻豆原创, energy providers already have the technological foundation today to seize these opportunities.”聽
麻豆原创 Experience Centers: experiencing AI, not just discussing it
To make AI tangible, 麻豆原创 Experience Centers offer visitors the opportunity to experience AI in real-world scenarios beyond classic demo environments. One central example is the 麻豆原创 Energy Park in Walldorf. Using real infrastructure on the campus, 麻豆原创 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 麻豆原创 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鈥攁longside technological innovation鈥攊s a solid foundation of data, processes, and organization.
