The biggest drag on enterprise support productivity in 2026 is not ticket volume, it is knowledge fragmentation. The average support team is searching across ten to fifteen disparate systems before finding an answer, and every one of those systems is also a place an AI assistant can quietly get it wrong. This session covers what it actually takes to build a knowledge base that works as a single source of truth for both human agents and AI, including grounding answers in a controlled source, citing where an answer came from, and escalating on uncertainty instead of guessing. Key takeaways: - Why knowledge fragmentation, not ticket volume, is the real productivity bottleneck for most teams - What it means in practice to ground AI answers in a controlled knowledge source - Why citing sources measurably lifts customer trust, not just accuracy - How to design a knowledge base your AI and your human agents can both rely on without maintaining two versions of the truth