When AI Doesn’t Get a Second Chance: Evidence Rather Than Plausibility for Defense and KRITIS

AI agents provide plausible answers—flexible, yet reinterpreted for each query. In defense and KRITIS environments, this is not enough: what matters here is not the most probable decision, but one that is traceable and repeatable. Prof. Dr. Heiko Beier demonstrates how data-driven reasoning orchestration generates an automated derivation for every decision—following the logic of the connected data and derived in a traceable manner from the interaction of distributed data points, rather than in isolation from individual raw data points. Using use cases such as situational awareness assistants, he illustrates exactly what this means for security-critical decisions.