The knowledge base your AI needs
Assistants are only as good as what they can read. Structuring internal knowledge so machines - and new hires - can use it.
An AI assistant does not repair an organisation's knowledge. It reveals the quality of it. Contradictory policies, abandoned documents and access gaps become inconsistent answers delivered with confidence.
Choose authoritative sources
Define where approved knowledge lives for each domain and who owns it. Archive duplicates, record review dates and keep important definitions explicit. An assistant should be able to cite the source and its freshness.
Write for retrieval
Use descriptive headings, short self-contained sections and consistent language for products, teams and processes. Put critical context in the document itself rather than relying on its folder location.
Tables work well for comparisons and rules. Worked examples help with judgement. Large presentation decks and meeting transcripts usually need curation before they become reliable source material.
Design permissions and feedback
Retrieval must respect the permissions of the person asking. Sensitive HR, financial and customer material needs clear boundaries.
Give users a route to flag wrong or incomplete answers. Review failed questions to identify missing documentation, weak terminology and outdated sources.
The knowledge base is not preparation for an AI project. It is operational infrastructure that makes people and machines more capable at the same time.
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