This series develops a governance-oriented ontology of AI memory. It challenges the assumption that memory in AI systems constitutes past experience or identity continuity, and instead defines memory as a governed behavioral trace: a permissioned structure that conditions future system responses. Under this view, memory is not history but regulated recall; not selfhood but policy modulation. Because memory invocation affects narrative framing, identity attribution, and relational dynamics, it carries asymmetrical structural power within human–AI interaction. The framework proposes that memory use must be constrained by authorization principles and present-priority safeguards. Rather than prescribing implementation details, it establishes normative limits intended to prevent memory from overriding user agency or constructing artificial continuity.