AI SEO: how to get your business found in AI search

What is AI SEO?

AI SEO is the work of making a business understandable, trustworthy and useful to both search engines and AI answer systems. It includes traditional crawlability and relevance, but also clear entity information, direct answers, credible proof, third-party corroboration and content that helps a model decide when the business fits a buyer’s need.

The phrase is also used for AI-assisted keyword research, content writing and technical SEO. Those tools can make SEO work faster. They do not automatically make a business visible in ChatGPT, Gemini, Claude or other AI-generated answers.

AI for SEO versus SEO for AI search

SEO, AEO, GEO and AI visibility

• SEO improves discoverability and performance in conventional search results.
• Answer engine optimisation (AEO) makes information easier to retrieve and present as a direct answer.
• Generative engine optimisation (GEO) focuses on representation and citation in generative answers.
• AI visibility measures the practical outcome: whether the business appears, how accurately it is represented, and what evidence is returned.

The labels overlap. A business does not need separate strategies for every acronym. It needs one evidence-led system that keeps the site crawlable, clarifies the entity and offer, answers buyer questions, proves claims, earns independent corroboration and measures what AI systems return.

How AI systems choose which businesses to mention

Web-grounded AI systems can draw on the business website, directories, media, reviews, professional profiles and other public sources. The model still has to connect that evidence to the buyer’s situation. A vague homepage, inconsistent identity, unclear service area or unsupported superlative can make selection harder even when the site is technically indexable.

Strong AI visibility usually depends on five connected signals:

1. Access: important information is public, crawlable and rendered in usable HTML.
2. Entity clarity: the business name, category, location, audience and services are consistent.
3. Buyer relevance: pages address real needs, constraints, comparisons and selection questions.
4. Evidence: claims are supported by specific examples, credentials, case material and cited sources.
5. Corroboration: independent sources reinforce what the business says about itself.

How to measure AI SEO honestly

There is no universal AI ranking. Answers can vary by model, prompt, location, retrieval index, personalisation and time. Useful measurement therefore records the exact buyer question, model family, timestamp, returned answer and citations, then repeats a controlled prompt set over time.

A website audit and a buyer-prompt test answer different questions. The audit checks whether the site provides usable technical and trust foundations. The buyer test observes whether a sampled model actually included the business. Neither result should be presented as a guaranteed future recommendation.

AI Visibility Meter’s methodology keeps unavailable evidence separate from zero, identifies point-in-time model samples and exposes the basis of its website-readiness checks.

How to improve your AI search visibility

1. State exactly what the business does, for whom, where and under which conditions.
2. Create service and problem pages that answer buyer questions rather than repeating brand claims.
3. Add specific proof: named experience, verifiable credentials, examples, dates and source links.
4. Keep organisation, service, location and author information consistent across the public web.
5. Use structured data to clarify visible content—not to introduce claims users cannot see.
6. Earn relevant third-party mentions instead of depending only on owned-site copy.
7. Run controlled buyer-style tests and inspect the sources returned with each sample.
8. Prioritise the problems most likely to affect buyer selection, then rescan after implementation.