How to Get Found by Google and AI Search

Classic SEO optimises for a click: rank on page one, earn the visit, let your page do the convincing. Generative Engine Optimisation (GEO) optimises for something upstream of the click — being the source an AI system quotes, paraphrases, or names when someone asks ChatGPT, Perplexity, or Google's AI Overviews a question in plain language instead of typing keywords into a search box.

If you're an early-stage founder with no dedicated SEO hire, the practical question isn't "how do I do GEO." It's "how much of this is a new job, and how much is the same job with a slightly different scoreboard." Mostly the latter. This guide covers the part that's genuinely different — entity signals and citation-friendly structure — and where it still just comes down to writing something worth quoting.

GEO vs. SEO: two names for adjacent problems

SEO's unit of success is a ranked position that someone clicks. GEO's unit of success is a sentence that gets reused — sometimes with a link back to you, often without one. That distinction matters for how you set expectations, but it doesn't mean you need a second content operation.

AI answer engines are not reading some separate, AI-only version of the internet. They're drawing on the same crawled, indexed pages that rank in ordinary search results, plus a wider net of forums, review sites, and community discussion that search engines have always partially used too. A page that already ranks reasonably well on Google is, more often than not, a much easier page for an AI system to trust and cite than one that's invisible to search entirely. Practically: fix your SEO first. Don't treat GEO as a parallel track that competes for the same two hours a week.

Where they genuinely diverge is the win condition. You can be the correct, cited answer to a buyer's question and never see a visit — the AI system answered the question in its own interface and the person moved on. That's not a failure of the content; it's a different kind of exposure, closer to a mention in a trusted publication than a landing page visit. Decide up front that you're optimising for both outcomes, not just the one you can see in your analytics. The one trap to avoid either way: answering thirty adjacent questions with thin, machine-written pages just because it's suddenly cheap to produce them. A dozen genuinely thorough pages beat a hundred shallow ones for both citation and ranking.

Why AI engines check who else mentions you

A search engine will rank your own homepage for your own company name without asking anyone else's opinion. An AI answer engine trying to describe your product to a stranger behaves more cautiously: it looks for some corroboration that you are who your website says you are. If your own site is the only place on the internet describing what you do, you are a harder fact to confidently repeat, no matter how well the page is written.

• Get listed where your category already gets discussed. If you're B2B SaaS, that's usually G2 or Capterra — free to set up, and worth a handful of real customer reviews rather than zero. Review platforms and comparison sites are exactly the kind of third-party corroboration an AI system leans on when deciding whether to name a small, unfamiliar vendor.
• Say the same thing about yourself everywhere. Your one-line description on your homepage, your LinkedIn company page, your G2 listing, and your directory profiles should describe the same category and the same core claim in consistent language. Contradictory self-descriptions across the web make you a less confident citation, not a more interesting one.
• Let people talk about you where they already talk. A founder answering questions honestly in a relevant subreddit, forum, or community thread is a real signal — those sources get pulled into AI answers more than most companies assume, and they can't be faked with better on-page copy.
• Put a real name behind the writing. A named author with a visible bio and a plausible reason to know the subject reads as a stronger source than an unattributed company blog post — to a human deciding whether to trust it, and to a model trained on which sources tend to hold up. It costs one line at the top of the page.

The same logic applies to backlinks and press, just under a less fashionable name. A guest post on a partner's blog or a mention in an integration marketplace listing isn't a dramatic win on its own, but it's another independent source repeating the same facts about your company — exactly the pattern an AI system checks for before it treats a small, unfamiliar vendor as a safe name to mention.

None of this replaces having good content on your own site — it's a precondition for that content being trusted once it exists. Structured data (Organization schema on your homepage, in particular) helps a machine parse the entity you already are; it does nothing for an entity that has no corroborating presence yet. Get the presence first, then make it easy to parse.

The structure that actually gets quoted

Once the entity signals are in place, the on-page work is mostly the same discipline good writing has always required, sharpened for a reader that extracts single passages rather than reading top to bottom.

• Answer in the first two or three sentences. State the direct answer to the question in your heading before you explain, qualify, or set the scene. Both a featured snippet and an AI answer engine are looking for the shortest span of text that fully answers the query — bury it under three paragraphs of preamble and you've made yourself uncitable regardless of how good the rest of the page is.
• Phrase headings the way a person actually asks the question. Extraction works on overlap between the query and your heading or the passage beneath it. A heading like "Pricing" gets skipped; "How much does [category] software cost for a 10-person team?" gets matched.
• Answer the obvious follow-up questions too, on the same page. A page that only answers the headline question gets used once. A page that also answers the two or three things a person would naturally ask next gives an AI system more reusable passages from the same source, which compounds your odds of being the one it reaches for again.
• Use specific, checkable claims instead of vague ones. "Cuts onboarding time" is easy to summarise past. "Cuts onboarding from nine days to two" is a concrete detail worth repeating verbatim, because it's exactly the kind of specificity that makes an AI-generated answer sound credible rather than hedged.
• Link related pages into an actual cluster. Ten pages on adjacent questions, cross-linked to each other, read as depth on a topic rather than one opportunistic page — and give an AI system more of your own pages to pull a follow-up answer from instead of reaching for a competitor's.

Schema markup (Article, FAQPage, Organization) is worth adding, but keep the expectation honest: it doesn't guarantee a citation. What it does is make your content unambiguous to parse — the difference between a machine guessing at what a passage means and being told outright. That's a small, mechanical edge on top of the actual writing, not a substitute for it.

The unglamorous foundation still applies

None of the above matters if the basics aren't in place: a fast, mobile-friendly site; pages that load without a wall of pop-ups; clean, descriptive URLs and titles; and internal links that help both a human and a crawler understand how your pages relate to each other. AI answer engines still depend on the same crawled, indexed web that search engines do — you cannot skip the foundation and jump straight to entity-building and answer-first headings.

If you're not sure where you stand, search your own most important buyer questions yourself, logged out. If you don't appear anywhere on the first page — organic results or AI overview — that's the actual starting point, not the keyword research spreadsheet.

Make sure the crawlers you want aren't already blocked

AI answer engines don't read your site with Googlebot. OpenAI crawls with GPTBot and OAI-SearchBot, Anthropic with ClaudeBot, Perplexity with PerplexityBot, and Google runs a separate directive called Google-Extended that governs whether Gemini and AI Overviews can draw on your content — distinct from the Googlebot line that governs your ordinary search ranking. Allowing one says nothing about the others, and most robots.txt files were last touched years before any of these existed.

Sites block these crawlers by accident more often than on purpose. Bot-management defaults on Cloudflare and similar CDNs, and some managed-WordPress security plugins, have at times treated AI crawlers the same as scraper traffic and quietly challenged or blocked them — no error a human visitor would ever see, and nothing that shows up unless you go looking. If you sit behind a CDN or a host-level firewall, that setting is worth five minutes of checking, not an assumption you carry over from your last audit.

Two checks cover it. Open yoursite.com/robots.txt and look for a Disallow line naming GPTBot, ClaudeBot, PerplexityBot, or Google-Extended — remove it unless you deliberately want that vendor excluded. Then ask ChatGPT or Perplexity to summarise one of your own pages by URL. If it can't, something between the crawler and your content is broken, and no amount of better writing or schema fixes that.

llms.txt — a proposed file listing your key pages for AI systems to read — comes up in the same conversation. It isn't an established standard the way robots.txt is, and no major AI crawler is confirmed to require it. Add one if you have five spare minutes; don't reorganise your week around it.

How to tell if any of this is working

You don't need a dedicated AI-visibility tracking tool at this stage, and buying one before you have enough published content for it to be worth watching is a way to spend money instead of doing the work. Two habits cover most of what you need early on.

• Check your own analytics for AI referrer traffic. Visits arriving from chatgpt.com, perplexity.ai, and similar domains show up as ordinary referrer traffic in whatever analytics you already run — no special integration required. It's usually a small number next to organic search, and that's fine; it's a leading indicator, not the whole scoreboard.
• Run your own buyer questions through each major AI system periodically. Ask the same handful of real questions your buyers ask, logged out, on a rough monthly cadence. Note whether you're named, whether a competitor is named instead, and whether the answer is even accurate about what you do. A manual spreadsheet is a perfectly good tool for this until you have a genuine volume problem.

Treat both as diagnostics that tell you whether the entity and structure work is landing, not as a monthly report you owe anyone. Watch for a trend across a quarter, not a single week's spot-check — in the first month or two you're still mostly fixing the foundation, so an absence of citations isn't a signal that GEO "isn't working." The underlying goal is unchanged from before AI answers existed: be the correct, well-supported answer to the question your buyer is actually asking.

Where FirstOrg fits in

Getting this right consistently — a credible entity presence, direct answers up top, specific facts instead of vague claims, one clean question answered properly per page — is straightforward in theory and tedious to execute at volume with no in-house SEO hire. FirstOrg's Search specialist builds every article around the real question your buyer is asking, structures it for both classic search and AI answer engines, and keeps publishing at the cadence that makes the entity and citation signals compound instead of resetting every time you go quiet for a month.