A controlled maintenance loop
Preserve provenance
Draft from approved internal sources and keep references attached. That makes review faster and reduces unsupported answers.
Use staleness as a workflow signal
Flag articles when source documents change, answer quality drops or support teams repeatedly override the same guidance.
Measure knowledge quality
Track deflection, successful search rate, article correction rate, unresolved-query clusters and time from gap detection to approved update.
Frequently asked questions
Can AI update a knowledge base automatically?
It can draft changes, but publishing should usually require approval because errors can propagate to many users or downstream AI systems.
How does AI find knowledge gaps?
Common signals include repeated failed searches, recurring support questions, low-confidence answers and frequently corrected articles.
Should an AI chatbot use the same knowledge base?
Usually yes if it is approved and current, but the retrieval and answer layer should preserve citations and handle missing information explicitly.