Private AI in the Energy Sector
Data · Availability · Behaviour — three controls for KRITIS-grade deployment
What this event is about
AI is moving into operational processes across the energy industry — load forecasting, market-communication classification, tariff guidance, trading signals, balancing-group support. Over time, a lot of this will seep into processes that fall under the KRITIS (critical infrastructure) regime. At that point the requirements change — and the standard cloud-API reflex from the marketing department is no longer enough.
Anyone embedding AI deep into a utility, a direct marketer, a municipal utility or a distribution grid operator must have three things under control at the same time: the data, the availability and the behaviour. Miss one and the solution does not hold for KRITIS-adjacent processes — no matter how good the language model looks from the outside.
What's actually at stake
Why this is not "just" about GDPR when market-communication records, balancing-group data, master contract data or trading positions flow into third-party models. Competitive substance, not only privacy — and why "we won't store / won't train" is contractually backed, not technically enforced.
Supply logic, not cloud scepticism
If AI enters KRITIS processes, its availability cannot sit in a foreign jurisdiction. What sanctions, model deprecations and compute scarcity concretely mean — and which European providers (Hetzner, OVH, STACKIT, OTC, Ionos) form a controllable alternative.
Predictability is not an add-on
System-prompt architecture, RAG with source references instead of hallucination, audit trail by design, model-version control. The operational prerequisite for an AI system to be allowed into an energy process at all.
Who this is for
Decision-makers, IT leadership, compliance and data-protection officers across the four core actor groups of the German-speaking energy industry. Prior AI/architecture knowledge is helpful but not required.
Municipal utilities
Sales · Customer service · KRITISDSOs
Grid · KRITIS obligationsGenerators
Generation · Portfolio · TradingDirect marketers
Trading · Market integrationSpeaker
Dr. Andreas Martens
For over 15 years, has led data and AI programmes across the DACH energy industry — at Uniper, Trianel, Enercity and other utilities and direct marketers. Current focus: privately hosted AI architectures that stay within the company's security perimeter, remain auditable, and actually hold up in KRITIS-adjacent processes.
Registration
You will receive the access link by email no later than the day before the event.
Registration received — thank you.
We'll reply within one business day with the access link and a calendar invite.
Questions in advance: contact@qurix.tech