According to @godofprompt, Microsoft has reported a 40% improvement in answer quality when utilizing graph-based Retrieval-Augmented Generation (RAG) compared to pure vector search, citing significant advancements in enterprise AI applications (source: @godofprompt, Jan 9, 2026). OpenAI is leveraging knowledge graphs internally for code, documentation, and user support systems, enhancing context and accuracy. Similarly, Anthropic’s Claude Code product constructs a graph representation of a codebase before generating answers, enabling deeper understanding and more precise responses. This rapid adoption of knowledge graph-powered solutions by leading AI companies underscores a market shift toward context-rich, graph-driven retrieval methods, presenting new business opportunities for enterprise knowledge management and AI-powered support tools.