"Generative AI is easy!" Just ask a question, and you get an answer. Simple, right? While individuals can easily engage with AI, enterprises face a far more complex reality. To deploy Generative AI securely, at scale, and with extensibility, organizations must navigate a vast ecosystem of infrastructure, including servers, APIs, agents, tools, data sources, prompts, embedding models, vector databases, and more. This session breaks down the real challenges of enterprise AI adoption, from compliance and data security to retrieval precision and system performance at scale. We'll explore why traditional RAG struggles with massive data volumes, how Knowledge Graphs enhance AI retrieval, and how multi-LLM architectures integrate with orchestrators like LangChain and Semantic Kernel across diverse data sources.