Context is the foundation of modern knowledge management
Technology that amplifies and supports KM activities is expanding exponentially. The importance of people-centered technologies cannot be overlooked.
The start of a new year is the perfect time to look ahead at what trends will have a significant bearing on how organizations collect, curate, and share knowledge.
KMWorld recently held a webinar, Top Trends in KM 2026, with Katie Selvaraj, AI strategist at SearchBlox Software, Inc., who discussed why context is the foundation of modern knowledge management, with AI-native systems and knowledge graphs enhancing relevance and understanding.
People and technology are context-dependent, she explained. Human understanding depends on context. Context shapes reactions and decisions and the same principles apply to knowledge management.
“To unify platforms and tools, what has become increasingly important is making them AI-native,” she said. “When it comes to KM that means all of your relevant data needs to be centralized in one location.”
Retrieval augmented generation (RAG) is essential to make the most practical AI-native platforms, streamlining features and making it easy to use. RAG can retrieve text based on meaning, she explained. It involves chunking documents for greater document context.
Expanding context awareness with knowledge graphs can help eliminate RAG’s pain points, creating a web of connected data which provides context for deeper understanding, she noted.
“It connects information from various sources to create a unified view that allows users to connect information and patterns,” Selvaraj said.
GraphRAG structures data into knowledge graphs to understand relationships, enabling complex reasoning, multi-hoc queries, and traceable answers. It offers deeper understanding and accuracy.
AI mode can enable interactive conversational search. It supports follow up questions and persistent context. This empowers users to engage with data dynamically.
GenAI powers recommendation and tailored content, it can enhance search, discovery, and user journeys.
“AI can enhance interaction with data,” she said.
MCP Servers essentially bridge the gap between the AI model and the applications being used. It provides seamless integration between platforms and applications that work with your data.
For the full webinar, featuring a more in-depth discussion, Q&A, and more, you can view an archived version of the webinar here.