Expiration-Aware Enterprise AI: Keeping Answers Aligned with Changing Policies

An enterprise assistant can retrieve a relevant policy and still provide the wrong answer if the rule no longer applies. Publication dates, effective dates, regional exceptions, and stored summaries can point to different versions of the same instruction. This paper specifies a conceptual architecture that treats policy applicability as a condition for releasing an answer. It separates the date governing a business event from the date information entered the system, records dependencies between policies and derived content, and rechecks evidence before delivery. The proposed workflow combines an authoritative policy register, temporal retrieval, dependency tracking, and a release gate. A fictional reimbursement example illustrates future-effective changes, historical questions, and outdated memories. An evaluation protocol compares these controls with similarity-based retrieval and periodic refresh. Reliable policy assistance requires more than frequent indexing. Claims need applicable evidence and interpretation checks; reused answers need valid dependencies. The architecture remains unvalidated; its effectiveness depends on accurate metadata, complete change detection, and clear policy ownership.

Artificial Intelligence