AI assistants on your own documents: what they are and where they help

“Should we be using AI?” is one of the questions owners ask most. For many growing businesses, the most useful answer is also one of the least flashy: an assistant that answers questions from your own documents.

What it is

General AI chatbots answer from what they learned on the public internet. They know nothing about your leave policy, your product specifications or the terms of your supplier contracts, and they will sometimes make up a confident answer anyway.

An assistant built on your own documents works differently. When someone asks a question, it first searches your documents for the relevant passages, then writes an answer based on those passages, and shows which documents it used. The technical name for this is retrieval-augmented generation (RAG). In practice, it means the answer comes from your information, and anyone can check the source.

Where it genuinely helps

The best uses share a pattern: the same questions asked often, answered from documents that already exist.

• Internal policies and procedures. “How do I claim travel expenses?”, “What is the approval limit for purchases?”
• Product and technical information. Specifications, compatibility, installation guides, for sales and support teams.
• Onboarding. New staff asking the questions they would otherwise interrupt someone to ask.
• Contracts and terms. Finding what a supplier or customer agreement says about notice periods or payment terms.

Where it is the wrong tool

• Calculations and financial figures. Use your reporting system, not a language model, for numbers.
• Decisions without review. An assistant can draft and find; a person should decide.
• Messy or outdated documents. If the documents contradict each other, so will the answers. Cleaning up the source is part of the work.

Keeping data safe

• Access follows permissions. The assistant should only use documents the person asking is allowed to see.
• Know where the data goes. Use services whose terms state that your data is not used to train public models, and keep it in services you control.
• Show sources. Every answer should show where it came from, so people can check it.
• Allow “I don’t know”. A well-built assistant says when the documents do not contain an answer, rather than guessing.

Run a pilot, not a programme

Start with one team and one set of documents, with a clear measure of success: questions answered, time saved, or fewer interruptions for a particular person. Run it for a few weeks, measure, and only then decide whether to expand.

Start from the problem

The businesses that get value from AI start with a specific, repeated problem and ask whether AI is the best fix, not the other way round. Often, the bigger win is ordinary automation: see our guide to automating invoices and expense claims.

Our data, automation and AI work covers both: automation where the task is repetitive and rule-based, and AI assistants where the task is answering questions from documents, each justified by the time it saves.