AI Search and GEO: What a Business Can Actually Control

1. Do not assume every AI answer engine works the same way

Some products retrieve live web results, some use search partners, some combine retrieval with model knowledge, and some expose citations more clearly than others. Even within one product, behaviour can change by query, market, account state, and product version.

That means statements such as all AI engines use the same RAG pipeline or schema directly increases recommendation probability should be treated with caution unless the specific system documents that behaviour.

2. Make first-party business information clear and verifiable

Publish clear descriptions of what the business does, where it operates, who is responsible for the work, what important services include, and what evidence supports key claims. Case studies, project documentation, useful FAQs, pricing context, policies, and accurate About information can all become valuable source material.

If the website contradicts the Google Business Profile, directory listings, social profiles, or other trusted sources, machines and people have a harder time deciding which version is current.

3. Use structured data as description, not persuasion

Schema.org markup can express entities and page content in a machine-readable form. Use it to describe what is actually on the page, not to insert facts that the public site does not support.

Stable @id values can help keep Organization, Person, Service, Article, Product, and other nodes consistent across a site. The value comes from clarity and accuracy, not from stuffing every available schema property into the graph.

4. Third-party evidence matters because it is independent

Directories, reviews, trade associations, news coverage, client references, and other external sources can independently describe a business. The most useful strategy is not to manufacture mentions, but to make real business information consistent and earn credible references through real work and relationships.

Never create fake reviews, fake citations, or false local presence in an attempt to influence AI answers.

5. llms.txt can be useful context, but it is not a ranking switch

An llms.txt file can provide a concise machine-readable overview of important site resources. It is useful as a maintained context document, particularly for tools that choose to read it.

Do not claim universal adoption or guarantee that publishing the file will cause an AI product to cite the business. The human-facing pages remain the primary source of truth.

# Example Business

> Short factual description.

## Core Resources
- Services: https://example.ca/services/
- About: https://example.ca/about/
- Contact: https://example.ca/contact/

6. Measure mentions as observations, not permanent rankings

Define a set of relevant questions, record whether the business appears, whether facts are accurate, and which sources are cited when citations are available. Repeat the observation over time under comparable conditions.

A mention in one prompt on one day is not equivalent to a stable search ranking. Treat AI visibility as a changing observation and combine it with measurable referral traffic and business outcomes where possible.