The shared mechanic under all three

Before the differences, the thing they have in common, because it is where most of the work lives. Every one of these engines does the same core move. It takes a question, retrieves a small set of passages it judges relevant and trustworthy, and then writes an answer that names two to seven sources inside it. Your entire job, on each engine, is to be one of those named sources. Not to rank tenth. Not to be technically indexed. To be in the short list the engine actually pulls from when it composes the answer.

That framing matters because it tells you the work is plural. There is no single switch that gets you cited everywhere. Each engine retrieves from a different place, weighs signals differently, and refreshes on its own clock. So you cover the factors they share, which is most of them, and then you meet each engine on the one or two things it does its own way. Here is how the three break down.

ChatGPT: the one to measure first

ChatGPT works from a web index plus live browsing and retrieval. When someone asks it a question, it can pull from what it has already crawled and, when it decides the question needs current information, fetch fresh pages in the moment. Two crawlers matter here: GPTBot, which builds the index, and OAI-SearchBot, which handles the live search side. If your robots.txt blocks either, you have quietly removed yourself from the source pool.

Prioritize ChatGPT because it drives the traffic. ChatGPT drives roughly 87.4% of AI referral traffic (Conductor, 2026), which means for most businesses it is not one engine among several, it is the engine, and the others are the tail. Measure it first, fix it first, and only then spread your attention. Getting named in ChatGPT is usually the single highest-leverage outcome in this entire chapter.

Perplexity: fresh, structured, easy to cite

Perplexity is built around real-time retrieval. It leans hard on live search and shows its sources openly, right there beside the answer, which tells you what it rewards. It favors pages that are fresh, clearly structured, and easy to quote: a direct answer near the top, clean headings, facts stated plainly rather than buried in a paragraph. Recency helps more here than on most engines, and clean structure helps a citation land where a wall of text would not.

Two crawlers to allow: PerplexityBot, which indexes, and Perplexity-User, which fetches a page live when a user's question sends it there. Let both in. Then give Perplexity what it likes, an answer it can lift cleanly and a page it can trust visibly, and you become an easy pick rather than a hard one.

Google AI Overviews and AI Mode: Gemini over Google's index

Google's AI Overviews and its conversational AI Mode both run on Gemini over Google's own index, and both lean heavily on experience, expertise, authoritativeness, and trustworthiness, the framework Google calls E-E-A-T, with real weight on verifiable authorship. The reach is large: Google AI Overviews appear on roughly 48% of queries, a 58% year-over-year rise (BrightEdge, 2026). Allow Google-Extended, the crawler that governs whether your content can feed these AI experiences, separate from classic Google indexing.

One trap to know. AI Overviews and AI Mode are not the same surface and do not cite the same sources. AI Overviews and AI Mode share only about 13% of their cited sources (Ahrefs, 2026), so being named in one is no guarantee of the other. Treat them as two targets that happen to share an engine, and check each on its own.

What every engine needs from you

Under the per-engine detail sits a short list of prerequisites that apply to all three. Get these right and you are eligible everywhere; miss one and you are invisible somewhere.

  • Let the crawlers in. A surprising share of sites block AI bots in robots.txt by accident, often left over from a default template. If GPTBot, OAI-SearchBot, PerplexityBot, Perplexity-User, or Google-Extended is disallowed, you cannot be cited, full stop.
  • Lead with the answer. Engines extract; they do not read patiently. Put the direct answer near the top of the page, in plain language, before the buildup.
  • Keep verifiable authorship. A named author with real credentials is a trust signal all three read. It is not cosmetic: 96% of AI citations come from pages with verifiable authorship (Wellows, 2026).
  • Be corroborated off-site. Engines lean toward sources that other credible sources agree with. A claim only you make is weaker than a claim the wider web backs up.

Freshness and revisiting

These engines re-crawl, and they do it on their own schedules. That is good news, because it means updated, clearly dated content can move you into the answer faster than classic SEO ever did, where a change might take weeks to matter. When you revise a page to answer a question better, date the update and keep the answer current. On the retrieval-heavy engines especially, fresh and correct beats old and thorough.

The honest limits

No engine can be made to name you on command. Each one changes how it sources answers, sometimes without warning, and none of them publishes a formula. So the method is not to chase a single engine's quirk. It is to cover the shared factors well, be genuinely the clearest and most corroborated answer, and then measure each engine separately so you can see where you are named and where you are not. Anyone promising a guaranteed citation is selling you something the engines themselves will not promise.

Where to go next

Off-site corroboration is the lever that carries the most weight across all three engines, and it gets its own treatment in Chapter 4 on reviews and off-site citation. Once you are meeting each engine where it looks, the next question is whether it is working, which is Chapter 6 on measuring Answer Authority. And if you want the whole method framed on one page, with the hire-us version, read the GEO agency guide.