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AI for Knowledge Management: Real Workflows That Hold Up

AI for Knowledge Management: Real Workflows That Hold Up

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Rost Posted on May 31 • Originally published at glukhov.org AI for Knowledge Management: Real Workflows That Hold Up # llm # ai # knowledgemanagement # rag AI is not replacing knowledge management; it is changing the shape of it for both individuals and teams. Microsoft's Work Trend Index describes a move toward hybrid teams of humans and agents, and NIST's AI RMF argues that trustworthy AI systems need explicit roles, evaluation, and oversight rather than vague automation. Those ideas fit neatly beside the human-centred practices in the site's Knowledge Management in 2026 pillar , which focuses on tools and methods long before any model is involved. That is exactly the right frame for knowledge work: AI is best treated as an enrichment layer over notes, docs, runbooks, and research, not as a magical second brain that works without structure. A useful mental model is the one developed in PKM vs RAG vs Wiki vs Memory Systems , where human note systems, shared wikis, retrieval pipelines, and agent memory each play a distinct role instead of collapsing into a single tool. The slightly opinionated version is this: if your notes are chaotic, AI will not rescue them. It will often make the chaos more fluent. Good knowledge management still starts with capture, naming, ownership, and source discipline. What AI changes is what you can do after capture: compress, extract, link, retrieve, and repackage information at useful speed. That view fits both modern prompting guidance, which recommends small, well-scoped tasks, and chunking guidance that preserves semantic units for retrieval instead of flattening everything into one blob. Why AI changes knowledge management The core shift is from static archives to active memory. Embeddings convert text into vectors that reflect relatedness and are commonly used for search, clustering, and recommendations. Retrieval systems can then surface semantically similar material even when the query shares few or no keywords with the sour

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