Ask your ten most common customers what they would type into ChatGPT to find a business like yours. Then type those questions yourself, in a clean session, and write down the answer. For most small businesses the result is uncomfortable: the model recommends a competitor, or hedges, or states something about you that stopped being true two years ago.
This is not a hypothetical problem anymore. Buyers increasingly start their search inside an assistant instead of a search results page, and the assistant names two or three businesses, not ten. Being "ranked well on Google" does not automatically make you one of the three.
Here is the honest part first: there is no trick. Google's own documentation for its generative features says optimizing for them is optimizing for search, and it explicitly tells you that a few popular "AI SEO" moves, like treating an llms.txt file as a magic tag, will not do much on their own. What earns a citation from any answer engine is boring and engineering-shaped: be retrievable, be extractable, be consistent. The audit below tests all three, and it takes about an afternoon.
Open ChatGPT, Perplexity, Gemini and (if you can) Google's AI Mode in clean sessions with no history. Ask the ten questions your buyers actually ask, phrased the way they phrase them: "how do I find a reliable tutor agency in Dublin", "what should a football academy pay for fee management software", "who builds WhatsApp agents for small businesses".
For each answer write down: whether you appear at all, whether you appear accurately, and who does appear. This document is the audit. Most people skip it and start redesigning pages, which is like renovating before measuring. Answer engines assemble answers by retrieving from an index. If your pages are not indexed, no clever wording will get you cited. Check the obvious things:
A surprising number of small-business sites fail this step and never get to the content discussion.
Assistants quote chunks, not pages. A chunk that starts with a qualified, direct answer survives summarizing; a chunk that builds to a conclusion rarely does. For each important page, make the first sentence under each heading the direct answer to the question that heading is about, then justify it. This is the BLUF pattern (bottom line up front), and it helps human skimmers just as much as models.
One more thing that shows up in every study of AI citations: models quote checkable claims. Named entities, real numbers, dates, prices. "We've run payroll for 142 staff since 2024" is quotable. "We streamline payroll" is not.
Add the semantic basics: Organization and Person schema with sameAs links so the entity behind your site is not a guess, FAQ-style question-shaped headings where people actually ask questions, and an llms.txt map of your key pages (it will not hurt; it will not save you either). Keep one consistent answer to "what is this company" everywhere your name appears, because engines cross-reference.
Now go back to Step 1's list. Most gaps were not ranking gaps; they were missing or wrong facts, or pages the engines could not read. Fix those, ask for citations where they are earned (directories, local press, real reviews), and rerun the ten questions in a month.
This is not a growth hack. A citation inside an AI answer often satisfies the question without a click, so measure whether you appear and whether you appear right, not just traffic. And when someone tells you they can make ChatGPT rank your site, ask which of the five steps above their service actually touches.
I build this work: I run neu Intelligence (https://neu.ie), a Dublin studio building custom AI agents and products, and every build ships with the machine-readable layer baked in, with the answer-engine audit as the first step. Disclosure, as promised, and the audit itself is free to run without me.