Technical SEO, on-page optimisation, local search, authority building and visibility in AI-assisted search.
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The short answer: AI search has changed the interface more than the fundamentals
Search systems increasingly generate answers, summaries and follow-up experiences, but the core requirement remains being discoverable, indexable, useful and trustworthy. For Google AI features specifically, Google says normal SEO best practices continue to apply and there are no additional technical requirements beyond eligibility for Search and snippets.
That does not make AEO or GEO meaningless. It means the useful parts are mostly disciplined information architecture, answer quality, entity clarity, evidence and technical accessibility rather than a secret new optimisation layer.
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What do AEO and GEO mean?
Answer Engine Optimisation (AEO) generally means structuring information so systems can identify and present useful answers. Generative Engine Optimisation (GEO) is commonly used for improving the chance that content is discovered, understood or cited in generative search experiences.
These labels are industry terminology, not separate ranking systems you can optimise through one universal checklist.
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1. Make important information crawlable and indexable
If a search system cannot access or index the page, the quality of the answer is irrelevant. Keep important content available in text, expose it through normal internal links, avoid accidental blocking and maintain clear canonical URLs.
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2. Give direct answers before the long explanation
For question-led pages, answer the core question early, then explain assumptions, exceptions, examples and evidence. Clear definitions, comparison tables and checklists can help both people and machines extract meaning without forcing the reader through unnecessary filler.
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3. Strengthen entities and provenance
Make it clear who the organisation is, who wrote or reviewed the material, what services or products are being discussed and how related pages connect. Use consistent organisation details and appropriate structured data that matches visible content.
Original experience, case studies, research, screenshots, measurements and first-party data create information competitors cannot reproduce by paraphrasing the same sources.
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4. Cite primary sources where factual claims depend on them
External links to authoritative sources can help readers verify important statements. For technical, regulatory or platform-specific guidance, link to the organisation responsible for the rule or behaviour whenever possible.
This is also a quality discipline: it forces the author to distinguish documented fact from interpretation.
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5. Do not invent special AI markup
Google states that sites do not need special schema.org markup, AI text files or other new machine-readable files to appear in its AI features. Structured data remains useful when it accurately describes the visible page, but there is no Google-supported “AI Overview schema”.
Similarly, an llms.txt file may be experimented with by parts of the industry, but it should not be presented as a proven Google ranking or citation requirement.
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6. Avoid scaled low-value AI content
Using AI to assist research, structure or drafting does not automatically make content poor. The risk is publishing large volumes of pages with little originality, verification or value. Google warns that scaled content generated to manipulate rankings can breach its spam policies regardless of whether humans or automation created it.
The editorial standard should therefore be accuracy, usefulness, original contribution and review, not whether a particular tool touched the draft.
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7. Measure AI visibility carefully
AI search measurement is still less mature than ordinary query and landing-page reporting. Use Search Console and analytics for the traffic and conversions you can observe, monitor branded citations in major answer engines where practical, and record material referral sources.
Do not turn anecdotal one-off prompts into a false ranking report. Generative answers vary by query wording, model, user context and time.
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A practical AI-search readiness checklist
- Important pages are crawlable, indexable and internally linked.
- Each page has a clear intent and direct answer.
- Organisation, author and service entities are consistent.
- Structured data matches visible content.
- Primary sources support important factual claims.
- Original evidence or experience is added where possible.
- Pages work well on mobile and load reliably.
- No unsupported “magic AI SEO” claims are relied upon.
- Search and conversion measurement is in place.
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Primary Google guidance
Google maintains guidance for AI features and websites, a broader generative AI search optimisation guide and guidance on using generative AI content. These documents are a useful antidote to claims that every business suddenly needs an entirely separate SEO stack.