Answers about AI Search and visibility.

Common questions

What organizations ask about AI Search.

What is AI Search optimization?

AI Search optimization is the work of making an organization easier for search engines and AI answer systems to find, understand, verify, cite, and recommend.

What is answer engine optimization?

Answer engine optimization focuses on improving how an organization appears in systems that synthesize answers instead of only listing links. These systems include ChatGPT, Claude, Gemini, Copilot, Perplexity, and Google AI Overviews.

What is generative engine optimization?

Generative engine optimization is another term for improving visibility in generative AI systems. Kumu treats it as part of AI Search optimization.

What is LLM visibility?

LLM visibility is the degree to which large language models can recognize, retrieve, summarize, and accurately describe an organization.

Can Kumu guarantee that an AI system will cite a company?

No. No agency can guarantee inclusion in a specific AI answer. Kumu improves the evidence, structure, clarity, and third-party signals that make inclusion more likely.

What does Kumu test?

Kumu tests owned website signals, search visibility, AI-answer behavior, third-party verification, structured data, page-level evidence, crawlability, channel presence, and user action pathways.

What is the Kumu Brand & Signal Benchmark?

The Kumu Brand & Signal Benchmark is an evidence-led assessment that measures Brand Integrity and Signal Architecture side by side.

What is the difference between SEO and AI Search optimization?

SEO helps pages appear in search results. AI Search optimization also helps answer systems understand what an organization is, why it is credible, what it offers, and whether it should be cited or recommended.

What is llms.txt?

llms.txt is an emerging way to give AI systems a concise map of important pages and context. Kumu treats it as an emerging signal, not a pass/fail requirement.

Why doesn't ChatGPT mention my company?

Usually because one of the earlier steps failed. Before a model can mention you it has to retrieve your content, understand what you do, categorize you correctly, and find evidence it can trust. Missing structure, vague positioning, thin proof or blocked crawling all stop the process before recommendation.

Why does an AI system describe my company incorrectly?

AI systems assemble descriptions from whatever is easiest to retrieve and most consistently repeated — often outdated pages, directories or third-party summaries. When your own properties don't state your positioning and offerings explicitly, the model fills the gap from weaker sources.

How do I get my brand into AI answers?

Make your content retrievable, state plainly what you offer and who it is for, mark it up so machines can parse it, and support every claim with verifiable evidence. Then measure whether the answers change. Kumu's benchmark scores each of those layers so you can act in priority order.

How is AI search visibility measured?

By testing what AI systems actually return about you, and by scoring the underlying conditions that determine those answers. Kumu measures fifteen dimensions across the Brand Integrity and the Signal Architecture Review, producing two Indexes and the Signal Gap between them.

Does structured data help with AI search?

Yes, indirectly but materially. Structured data removes ambiguity about what an entity is, what it offers and how items relate, which makes correct categorization and citation more likely. It is not a ranking trick and it cannot compensate for missing substance.

Do I still need SEO if I invest in AI search?

Yes. Traditional search still drives significant discovery, and much of the technical foundation — crawlability, performance, information architecture — serves both surfaces. AI search optimization adds entity clarity, evidence and comparison readiness on top of it.

How long does it take to see improvement in AI answers?

Technical and structural fixes can register within weeks once systems re-crawl. Trust and citation signals move more slowly, typically over one to two quarters. This is why re-measurement against a fixed baseline matters more than week-to-week observation.

How much does an AI search benchmark cost?

Kumu's Phase 1 benchmark is $500 and delivers first findings in 3–5 days. Phase 2, the full fifteen-dimension review with competitor comparison and a Transformation Roadmap, is scoped to the organization.

Who should own AI search visibility inside a company?

It sits across marketing, content and engineering, which is why it is often unowned. The practical answer is that marketing owns the outcome and the benchmark gives engineering and content a shared, evidence-based list of what to change.