Artificial intelligence is becoming a game changer for the energy industry—with potential across the entire value chain, from forecasting and grid stability to customer service. In this interview, we talk to Anne Rethmann, CFO of Thüga AG, Germany's largest association of municipal energy and water suppliers. She explains where the greatest potential lies for the next technological quantum leap and why companies should prioritize a company-wide AI-supported forecasting and control system in their AI journey.
Where do you see the greatest potential for artificial intelligence in operational processes at Thüga AG - for example in maintenance, network management or customer service? :
RETHMANN At the end of 2024, we developed a strategic orientation guide on AI strategy for our partner companies. In addition to a structured methodology for creating their own AI strategy, we also looked at the fields with the highest potential along the value chain of energy suppliers. It quickly became clear that there is potential along the entire value chain. A lot is currently happening at the municipal utilities in the area of sales and customer service; various solutions are already being used here. But there are also links between energy generation, grids and trading. There is particularly high potential in the area of forecasting: predictive maintenance, load forecasts, weather impact, market developments/trading forecasts. In grid management, on the other hand, AI can analyze grid stability in real time and optimize load flows.
It quickly became clear that there is potential along the entire value chain.
To what extent do you think AI can really revolutionize the operational management of companies in the next five years? :
RETHMANN In the next five years, AI will not only support operational management but will take over autonomously in many areas. We are talking about real-time decisions based on complex data streams - be it for grid stabilization, load distribution or maintenance planning. The revolution lies not only in technology, but also in the speed, scalability and precision with which processes can be optimized. However, this requires a profound change in data quality, system integration and governance.
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