What AI search optimization actually is
AI search optimization is the work of making a brand easier for AI systems to discover, understand, cite, compare and recommend. You will also see it called AI SEO, GEO, AEO or LLMO. The acronyms describe the same job and none of them is worth building a brand around.
It is not a separate channel bolted onto SEO. The inputs overlap heavily with technical SEO and content: crawlability, structure, clarity, third-party corroboration. What differs is the measurement, because an AI answer that recommends you may never produce a click, and a click-based report will record that as nothing happening.
The questions this work can actually answer
Most writing on this subject stops at “AI is changing search”. That is not a finding. These are the questions worth paying to have answered, and each of them is measurable.
- Does the brand appear at all for the prompts your buyers actually run?
- Which sources are being cited when it does, your site, a review platform, a competitor’s comparison page?
- Are competitors named more often, and in which parts of the evaluation?
- Are the product facts correct, pricing, tiers, integrations, limits?
- Can the assistant reach the pages that hold those facts?
- Is the brand described consistently across the places that get cited?
- Is AI referral traffic being measured separately, and does it convert differently?
| Traditional search report | AI search report | |
|---|---|---|
| Unit of visibility | Position for a keyword | Citation or mention inside an answer |
| Sampling | Rank tracker, daily | Prompt set, re-run on a fixed schedule |
| What a win looks like | Position 3 to position 1 | Named in the answer, and named accurately |
| Traffic relationship | Position predicts clicks | A recommendation may produce no click at all |
| Failure mode to watch | Ranking drop | Confidently stated wrong facts about your product |
What we can show, and what we cannot promise
The six case studies on this site all measure AI citation behaviour from raw exports, with the date and method stated. They are properties Alston owns and operates, not client accounts, which makes them reproducible and checkable, but not client references. They are presented as method evidence, nothing more.
What no agency can honestly sell is a guaranteed citation. Retrieval changes between model versions, prompts vary by wording, and a brand can lose an answer it held last month without touching its own site. The commitment worth making is measurement and a diagnosis: a baseline, a prompt set, a re-run on a schedule, and a clear account of what changed.
How the engagement runs
A baseline first: a prompt set built from your category, your competitors and the objections your sales team hears, run across the assistants your buyers use, recorded with the answers as they came back. That baseline is the report you are paying for even if you never continue.
From there the work splits into fixing what is wrong (inaccurate facts, unreachable pages, thin corroboration) and building what is missing, usually comparison and alternatives coverage plus third-party sources an assistant is willing to trust. Re-run the prompt set on a fixed schedule and the change is visible rather than argued.