How Semantic AI & Knowledge Graphs Can Turn M365 Environments Into a Smart Knowledge Hub
Much in the way a maze can include passageways that help people navigate where they want to go quickly, organizations need to transform the static data in their SharePoint libraries into a Microsoft 365 knowledge hub that links related information across various formats and storage locations. Using tools such as knowledge graphs, companies can map and tag the various terminologies used in the company so that when people use various terms when looking for the same document, the mapping understands that they are looking for the same thing.
Semantic AI also allows users to benefit from smarter search and better information exchange. For example, with quality metadata from the automated tagging, it optimizes the enterprise’s search environment and returns results instantly. The search looks for content based on meaning (aka semantics), not just keywords. It also allows people to narrow down results with tailored facets and delivers information quickly and efficiently.
For example, let’s say a marketing person is interested in doing a campaign aimed at the financial services domain and was looking for information about money management accounts. Most likely, there are many documents in various formats on this topic scattered across the SharePoint libraries, and after a standard SharePoint search is done, they receive a lengthy list of results showing every document with the word “money” or “management” in the title.
Instead, using semantic search, users can choose from some predefined search domains that deliver relevant results in seconds. Rather than producing pages and pages of results, it will show the most relevant documents and include a summary of what each one is about as well as a preview of the selected tags. Semantic search also enables individuals to refine their search criteria and narrow down the results based not only on the document-level metadata generated by the system but also on semantic concepts related to the documents.
Why Knowledge Graphs Are the Future for Microsoft Teams and Copilot
Using automatic concept tagging, Term Store synchronization, and semantic search will improve the end-user experience within SharePoint. For companies that use SharePoint extensively, semantic search will save a lot of resources, avoid missed opportunities, enable quicker decision making, and nurture other AI initiatives.
As an organization grows and uses tools such as Microsoft Teams, the sheer number of channels, chats, and files will exacerbate the problem further, making finding information more difficult while impacting productivity. AI-powered productivity tools such as Microsoft Copilot are helping to reduce repetitive work and make collaboration smoother. However, these AI assistants can fail to deliver effective replies, producing misleading results or offering vague suggestions.
By automatically tagging files and making them accessible directly on the Teams platform, users will receive more trustworthy and accurate answers to questions thanks to the knowledge graph that powers it. In this way, by improving search, tagging, and knowledge linking within the Microsoft ecosystem, M365 environments evolve from a cluttered document space into an organized, smart Microsoft 365 knowledge hub.