Agentic Retrieval-Augmented generation: a survey on agentic RAG

Agentic retrieval-augmented generation: a survey on agentic rag refers to a comprehensive research exploration of advanced RAG systems that embed autonomous AI agents into traditional retrieval-augmented generation pipelines. These agents leverage agentic design patterns including reflection, planning, tool use, and multi-agent collaboration to dynamically manage retrieval strategies, iteratively refine contextual understanding, and adapt workflows to meet complex task requirements. This survey methodology examines how agentic RAG transcends conventional RAG limitations by enabling flexible, scalable, and context-aware information processing across diverse applications. The survey covers foundational principles of agentic intelligence, implementation architectures, real-world applications across industries, and identifies scaling challenges while proposing future research directions for autonomous information retrieval and generation systems.