People are starting to ask AI assistants questions they used to put into a search engine: “Which project management tool works for a small charity?” or “Can this software import data from our old system?”
That shift is already visible in the UK. In a survey of more than 4,000 consumers, Which? found that just over half used AI search tools to look for products, services, or advice online. Search engines still matter, but product discovery now happens in more than one place.
For product teams, that changes who gets to explain what the product does.
The chatbot will try to answer
Ask a chatbot a product question and it will usually try to help, even when your website has little useful information. If the assistant has web search, it might draw on competitor pages, retailer listings, discussion forums, or customer reviews. If it cannot find reliable information, it might fill in the gaps with a plausible-sounding answer.
That answer could be wrong. AI systems can state false information with confidence, as OpenAI explains in its overview of why language models hallucinate.
Imagine someone asks whether your software supports single sign-on, or whether it works with a particular accounting system. Your help centre says nothing about either feature. The chatbot might find an old forum post, mistake a competitor’s feature for yours, or infer an answer from the type of product you sell.
The buyer still receives an answer. Your documentation gap does not make the question go away.
Your documentation is part of the buying journey
User documentation is usually treated as something customers need after they buy. But people also use it to judge whether a product will work for them.
They want to know what it can do, which systems it works with, how difficult it is to set up, what happens when something goes wrong, and whether it meets their organisation’s requirements. Product pages can cover the headline benefits. Documentation answers the detailed questions that help someone decide.
When that information is clear and publicly findable, it gives AI assistants a better chance of describing the product accurately. It also gives prospective customers somewhere to check the answer for themselves.
That matters even when an AI-generated answer includes links. Pew Research Center found that people were less likely to click through to websites on Google results pages that showed an AI summary. In its study, users clicked a traditional search result on 8% of visits with an AI summary, compared with 15% of visits without one.
What should product teams make easy to find?
Start with the questions a potential buyer is likely to ask before they commit. Make the answers accurate, specific, and available without a login.
That might include:
- Which features are included, and which require an add-on?
- Which operating systems, browsers, integrations, and file formats are supported?
- What does implementation involve?
- What permissions or technical requirements are needed?
- What are the product’s limits?
Use the same product names and terms across your website, help centre, and sales materials. Keep pages up to date. If a feature changes, update the information a buyer could find about it, including older pages that still appear in search results.
You cannot control every answer a chatbot gives. You can make reliable source material easier to find, so the answer has something accurate to draw on.
Documentation has a marketing job
AI assistants are becoming another route through which people discover and compare products. They do not replace search engines, product pages, reviews, or conversations with sales teams. They add another voice to the buying process, and that voice will use the information it can find.
Your documentation is one of the few places where you can explain the product in detail, in your own words, and keep that explanation current. If those answers are missing, someone else’s description might fill the gap.
Good documentation helps customers use the product. It also helps them decide whether to choose it in the first place.
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