Direct answer
The short version.
Generative engine optimisation improves the chance that AI search systems can discover, understand and cite a page. The practical foundation is the same as durable SEO: crawlable text, clear answers, original evidence, internal links, accurate entities and structured data that matches visible content.
Key takeaways
Keep these three decisions.
- Use search fundamentals before GEO tactics.
- Put useful answers and evidence in crawlable text.
- Measure cited pages and qualified outcomes.
The operating problem
GEO is often sold as a collection of new files or special schema. Google states that its AI search features use existing search foundations and do not require special AI markup. Technical additions cannot rescue thin, duplicated or untrustworthy content.
A practical system
Map real customer questions, publish a direct answer before deeper explanation, identify who is speaking and support claims with primary sources or owned evidence. Keep key facts in HTML, connect related pages, use accurate Article and Breadcrumb markup and allow relevant search crawlers in robots.txt.
What to measure next
Monitor indexed pages, branded and non-branded search, referrals from AI products where available, cited URLs, assisted conversion and the questions that produce qualified visits. Treat visibility as a portfolio signal because AI responses vary by query and context.
Primary and authoritative references
Sources used for context.
Frequently asked questions
Two useful follow-ups.
Is GEO different from SEO?
GEO focuses on how generative systems retrieve and cite information, but it relies heavily on the same crawlability, relevance, authority and content-quality foundations.
Is special AI schema required for Google AI Overviews?
Google says there are no additional technical or structured-data requirements beyond normal Search eligibility and best practices.