FAQ – CiteByAI
FAQ
Clear answers to common questions about AI discoverability and citation readiness.
These answers explain how AI-driven search systems interpret, trust, and reference websites, and how CiteByAI approaches preparation for that environment.
What does “being cited by AI” mean?
Being cited by AI means your website is selected as a source when an AI system generates an answer, summary, or explanation. Instead of showing lists of links, many AI tools reference a small number of sources they understand and trust. Citation depends on clarity, structure, and credibility signals rather than traditional rankings alone.
Is this the same as SEO?
No. Traditional SEO focuses on ranking pages in search results, while AI-driven search focuses on interpreting meaning and selecting sources to reference. CiteByAI works on structural clarity, semantic consistency, and trust signals so AI systems can accurately describe and reference a website.
What is AI discoverability?
AI discoverability describes how easily AI systems can identify what a website is about, interpret its content, and decide whether it is safe to reference. It includes content structure, page intent clarity, entity signals, internal consistency, and machine-readable data such as schema.
What makes a website “AI-readable”?
A website is AI-readable when its purpose and content can be interpreted without ambiguity. This typically includes clear headings, consistent terminology, logical page structure, explicit page intent, and supporting structured data that reinforces meaning.
Do you guarantee citations or rankings?
No. AI systems change frequently, and citation decisions vary by model and query. The goal is to remove preventable reasons a site may be ignored or misunderstood and to improve the likelihood that it is eligible to be trusted and referenced.
What does the AI Readiness Review include?
The AI Readiness Review assesses how AI systems are likely to interpret your website, where ambiguity or missing signals may reduce trust, and whether improving AI discoverability would be worthwhile. It focuses on understanding, structure, and credibility rather than keywords or rankings.
What changes typically improve AI understanding?
Improvements often include clarifying page intent, strengthening internal consistency, improving information hierarchy, adding appropriate schema, and reinforcing entity and trust signals. The aim is to make interpretation predictable and reduce the risk of misrepresentation or exclusion.
How long does it take to see results?
It varies. Some changes improve how AI systems interpret a site immediately, while broader effects depend on crawling, indexing, and how AI tools refresh their understanding over time. The focus is on building durable signals rather than short-term visibility spikes.
If you have a specific question not covered here, the AI Readiness Review provides tailored feedback based on how AI systems currently interpret your site.