Practical AI / 2026 Essentials
RAG: Let AI Work with Your Business Knowledge
Retrieve relevant documents before generating an answer, and keep the source material current.
Retrieval-augmented generation, or RAG, supplies a language model with information retrieved from your documents. It can help answer questions about internal procedures without training a new model. The difficult work is preparing useful content and evaluating retrieval, not merely connecting a chatbot to a folder.
What matters
- Choose maintained documents with clear owners and remove obsolete or conflicting versions.
- Split and index content so a search can retrieve useful passages with enough surrounding context.
- Evaluate retrieval and generated answers separately, including questions the documents cannot answer.
Practical example: A staff assistant retrieves the current leave policy and links the relevant passage instead of guessing from general knowledge.
One action today: Collect ten genuine employee questions and identify the documents needed to answer them.