Chunking is the process of dividing large bodies of text or datasets into smaller, manageable segments that AI systems can process more effectively. This technique is critical for retrieval-based methods like RAG, where the model needs to search and reference specific parts of a dataset quickly. Proper chunking improves both the speed and accuracy of AI responses, especially in scenarios involving long documents, multi-turn conversations, or enterprise knowledge bases.