RAG vs Fine-Tuning: Which Approach Should You Choose?

As organizations adopt Generative AI, one of the most common questions is: Should I use Retrieval-Augmented Generation (RAG) or Fine-Tuning? Both approaches improve the capabilities of Large Language Models (LLMs), but they solve different problems. Choosing the wrong approach can increase costs, complexity, and maintenance efforts. In this article, we'll explore how RAG and Fine-Tuning work, their advantages, limitations, and when to use each. Understanding RAG Retrieval-Augmented Generation (R