AI search has no page two. When someone asks ChatGPT, Gemini, Claude, or Perplexity a buying question, the answer names a few brands and the rest do not exist. Here is how to show up in AI search, step by step, starting from wherever you are now.
Collect the twenty questions your buyers actually ask, in their words, with their context. Run each through the four assistants in fresh sessions. Score yourself: named, misdescribed, or absent, and note who wins instead. This baseline turns AI search from anxiety into a work list.
Assistants extract answers, so structure for extraction: one clear topic per page, question-shaped H2s, direct first-sentence answers, FAQ schema, accurate Organization and Product markup, and an llms.txt file mapping your key pages. Technical hygiene does not win answers alone, but its absence quietly disqualifies you.
Every buying journey is a chain of questions: what is this, what does it cost, which is best for my case, who should I trust. Publish direct answers across the whole chain. Brands present early in the conversation, at the “what is this” stage, keep getting named when the conversation reaches “who should I hire.”
Check what Perplexity and Gemini cite for your category: review platforms, listicles, comparison posts, community threads. That citation set is the actual battlefield. Earn presence in those exact sources, and keep your descriptions consistent across them so corroboration compounds.
Model updates and competitor content rewrite AI answers without warning. Re-run your question set weekly, watch mention rates and framing, and treat drops as incidents. This loop, measure, fix, verify, is what Aethon runs as a platform across all four assistants, with the execution work included.
Baseline your visibility across the four assistants, structure your site for quotability, publish direct answers across the buyer question chain, build presence in the sources assistants cite, and monitor continuously.
AI answers weigh consensus and quotability over rankings. Strong SERP positions with weak third-party corroboration commonly produce AI invisibility.
Perplexity and Gemini respond fastest because they cite live sources. Landing in the review sites and articles they cite can change answers within weeks.
The basics: clean structured data, FAQ schema, crawlable content, and an llms.txt file. Aethon’s free llms.txt generator covers the last one in minutes.
Monitoring. Answers shift with model releases and competitor moves, so continuous measurement plus quick remediation is the durable strategy.
To appear in AI answers, give the assistants something worth quoting and somewhere to find it: pages that answer real buyer questions in the first lines, facts kept current everywhere retrieval looks, presence on the review sites and comparison articles ChatGPT, Gemini, Claude and Perplexity cite, and coverage of the situations that precede purchase, not just the keywords that follow it. Then verify monthly, per assistant. The complete playbook is in how to get recommended by AI assistants.