Energy is becoming a data coordination problem
More variable generation, flexible demand, storage, new loads and distributed assets create a system that cannot be managed by expanding physical infrastructure alone. Digital infrastructure becomes central because it connects measurement, forecasting, optimisation and response. The Commission’s work on digitalisation and AI in energy is a policy signal that this is moving from experimental technology language into system design.
The risk is false precision
AI can improve forecasting, anomaly detection and operational decision support. It can also obscure uncertainty when data quality, model boundaries or incentives are poorly understood. The energy system is a high-consequence environment. The right question is therefore not whether a model predicts an outcome, but whether operators can understand its assumptions, test its behaviour and retain authority during abnormal conditions.
What Manfred is watching
The strongest signals will combine policy, standards, operational deployment and investment in data architecture. Look for trusted data exchange, secure interoperability between system operators and distributed assets, and evidence that digital tools improve reliability or flexibility in real use. The system becomes strategically interesting when digitalisation increases practical control, not merely analytical sophistication.