This concept paper introduces the complementary concepts of Decision Independence and Decision Isolation in memory-driven artificial intelligence systems. It proposes a unified conceptual framework for understanding how long-term memory, continual learning, and accumulated contextual information may influence decision-making processes in adaptive AI systems. The contribution is intentionally conceptual and implementation-agnostic. No algorithms, system architectures, engineering mechanisms, or proprietary methods are disclosed. The purpose of the work is to establish terminology, identify a conceptual research gap, and support future scientific discussion regarding trustworthy memory-driven AI systems.