What's Actually Missing?
Let’s move past the cliché: it’s not due to “bad data in, bad data out.”
It’s bad governance in, bad outcomes as a result.
Most contact centers skipped a crucial step: creating ownership, standards, and accountability for knowledge before launching AI pilots. Instead, they ran “co-pilot pilots” without structure — no defined roles, no governance framework, and no funding to sustain continuous improvement of accurate information.
The result? Fragmented truth, low containment, and models that fail faster than leaders can manage.
It’s not a model problem. It’s a leadership gap.
Leaders need to stop delegating “knowledge” to a system or a project and start managing it like a strategic asset. That means budgeting for:
Dedicated roles: Knowledge program owners, data stewards, and AI knowledge analysts.
Training and certification: Knowledge-Centered Service (KCS) or similar frameworks to sustain a culture of accuracy.
AI knowledge strategy projects: Funded initiatives to design retrieval logic, governance layers, and tagging automation.
Change management: Cross-functional alignment so operations, CX, and IT own truth together.
This is how organizations evolve from AI pilots to organizational scale of AI ROI.
If you’re still running “AI co-pilot” experiments, 2026 must be the year you prove knowledge maturity.
You’re ready to scale when answer accuracy consistently exceeds 80% or AI containment remains above 50–60% for top intents, without escalation growth, depending on your use case.
That’s the signal your governance and content lifecycle are stable enough for broader deployment.
AI isn’t completely failing. Humans are failing to govern knowledge with the same rigor they apply to finance or compliance.
We're helping contact centers close that gap.
Our GenAI-Ready Knowledge Article Assessment identifies weaknesses in your content structure, governance, and readiness to scale responsibly. Most clients in 2025 are scoring well under the passing mark. As a result, their AI assistants don't return the answers.
Because before AI can perform, leaders must own the truth it runs on.