True, Relevant, and Wrong: The Applicability Problem in RAG

RAG systems promise to reduce AI hallucinations by grounding responses in trusted documents, but this fails at scale when organizations accumulate multiple policy versions across regions, dates, and eligibility tiers. The core problem shifts from citation accuracy to applicability—determining which correct information governs a specific situation, as systems often blend contradictory but individually accurate sources into misleading "franken-answers."