Key answer: GEO (generative engine optimization) is optimising a website for AI search (ChatGPT, Perplexity, Gemini); AEO (answer engine optimization) covers answer engines (Google AI Overviews, featured snippets). The shared foundation is content accessible to AI bots in clean HTML, direct answers at the start of sections, schema.org structured data, FAQ formats, content freshness and consistent company information across sources.
Table of contents
The short answer
More and more purchase decisions start not with a list of links in Google but with an AI-generated answer. GEO (generative engine optimization) makes models like ChatGPT and Perplexity cite your company as a source; AEO (answer engine optimization) puts your content into the ready answers search engines display. The good news: both stand on the foundation of solid SEO and can be implemented systematically.
How AI chooses whom to cite
When a user asks "which studio would you recommend to build an app?", the model doesn't draw lots – it composes its answer from sources it can fetch, understand and trust. In practice, the advantage goes to sites that:
- are accessible to AI bots: not blocked in robots.txt or by anti-bot firewalls,
- serve content as clean HTML: AI search bots often don't execute JavaScript; content rendered only in the browser doesn't exist for them,
- answer directly: sections that open with the answer (not a warm-up) are easy to quote,
- are fresh: models clearly prefer recently updated content; publication and update dates matter,
- are consistent across sources: AI builds its picture of a company from directories, LinkedIn and reviews too; contradictions lower trust,
- sound expert: concrete numbers, named authors, sources next to claims.
The implementation checklist
1. Technical access. Check robots.txt and CDN settings – do GPTBot, OAI-SearchBot, ClaudeBot and PerplexityBot get in? Is your content visible with JavaScript disabled? (test with curl or by switching JS off in the browser).
2. Answer architecture. Every important section should open with 1–2 sentences of substance; phrase headings the way users ask questions; present processes as numbered lists and comparisons as tables.
3. Structured data. JSON-LD on every page: Organization/LocalBusiness, Service, FAQPage, Article with author and dates. These are "subtitles for machines" – they remove guesswork from interpretation.
4. The formats AI loves. An FAQ page, a glossary with the definition in the first sentence, pricing guides with concrete ranges. In most languages and niches, competition in these formats is still thin – a window of opportunity.
5. llms.txt. A root-directory file describing the site and its key pages in a model-friendly form. Not a mandatory standard, but it costs fifteen minutes.
6. Entity consistency. Identical company data (name, address, description) on the site, in Google Business, on LinkedIn and in industry directories.
7. Freshness and measurement. A quarterly review of key pages with a visible update date, plus a monthly manual check – does AI recommend us, and in what context?
The most common mistake: treating GEO as a separate project
GEO is neither magic nor a silo – it is the consistent extension of good craft: a fast site, clean structure, content that answers real questions, honest signals of expertise. The site you are reading was built to exactly this checklist – from clean HTML through complete schema to llms.txt.
Not sure where to start? Run an AI visibility audit with us: we'll check whether ChatGPT and Perplexity can see your company and what they say about it. And if you're building a site from scratch, we'll build you one that is ready for it.