According to @godofprompt, leading AI engineers at OpenAI, Anthropic, and Microsoft are shifting from traditional RAG (Retrieval-Augmented Generation) systems to graph-enhanced retrieval methods, placing knowledge graphs at the core of their architectures (source: x.com/godofprompt/status/2009545112611893314). This trend significantly improves information retrieval accuracy, context understanding, and reasoning capabilities in enterprise AI solutions. Businesses can leverage graph RAG for advanced document search, dynamic recommendation engines, real-time analytics, and robust compliance monitoring, offering new competitive advantages. The thread outlines seven actionable ways to deploy graph RAG over standard vector search, highlighting immediate opportunities for companies to enhance AI-powered productivity and unlock scalable data insights.