AI SEO
vs traditional SEO
Traditional SEO works towards a position on a list. AI SEO works towards inclusion and accurate representation in a generated answer. They rest on much the same foundations — accessible pages, clear entities, credible authority, content that genuinely answers something — and diverge on two things that matter more than the label: what counts as success, and what counts as evidence that anything changed. That second one is where most of the confusion in this market lives.
Free, roughly ninety seconds, no card and no access to your systems.
Two objectives, one foundation
| Traditional SEO | AI SEO | |
|---|---|---|
| Goal | Rank highly enough to earn the click | Be one of the few sources an answer is built from |
| Competitive shape | A list with many slots | A sentence with two or three names |
| Content emphasis | Covering a topic thoroughly and matching intent | Stating a specific answer in a passage that survives being lifted out |
| Authority emphasis | Links and domain-level signals | Whether independent sources corroborate the specific claim |
| Identity | Helpful, especially locally | Decisive: ambiguity is answered with a hedge |
| How you know it worked | Position, impressions, clicks — comparatively stable series | Harder: no rank to track, responses vary between runs |
Most of the work is the same work
It is worth resisting the framing that a new discipline has replaced an old one. Technical accessibility, sound information architecture, pages that load and render, structured data that accurately describes what a page is, consistent business information, and content that answers a real question — all of that serves both objectives and none of it has been superseded.
Several of those foundations became more important rather than less. A retrieval request has less patience than an indexing crawler: it does not wait for a client-side render or follow a chain of redirects to find the substance. Teams that invested in clean, fast, well-structured sites are in a better position now than they were, not a worse one.
The honest summary is that AI SEO is mostly a change of objective applied to a familiar body of work, plus two genuinely new emphases: making a business unambiguous as an entity, and getting its claims supported somewhere other than its own website.
Evidence, and why this is where people get sold things
Traditional SEO has an unusually good feedback loop for a marketing discipline. Positions can be tracked, impressions and clicks are reported, and while attribution is never perfect, there is a stable series to look at. You can be wrong about why something moved, but you can at least see that it moved.
AI search offers nothing equivalent. There is no position. Asking an assistant the same question twice can produce different names, and phrasing the question differently can produce a different set again. Nothing is published about how sources are selected, so a supplier cannot show you a mechanism either.
That vacuum is what fills the category with confident, unverifiable products: factor lists nobody can validate, "share of voice" charts built by smoothing noise into a line, and case studies asserting a causal link that cannot be demonstrated because the counterfactual is unobservable.
What to actually do first
- Fix anything that blocks measurement. Pages that cannot be fetched or whose substance appears only after a render are invisible to retrieval, and no downstream work on them can be verified.
- Make the organisation unambiguous. One name, one description, one set of identifiers, agreeing across your site and the records that describe you. Cheap, structural, and frequently the largest single movement in a re-measurement.
- Answer questions in liftable passages. Usually editing rather than writing: the answer is often present and merely never stated plainly.
- Get corroborated. The slowest item, dependent on other parties, and the one that most changes how you are described rather than whether you are found.
- Keep doing the SEO fundamentals. They feed both objectives, and abandoning them to chase a new label is how businesses lose the traffic they already had.
What is evaluated, and what is refused
OG01 reads a domain from outside and scores four cards — Brand Intelligence, Search Intelligence, AI Readiness and AI Risk & Exposure — which combine into a composite Authority Rating. Traditional search performance is not discarded in that model; it sits inside Search Intelligence, because retrieval and positioning remain an input to what an assistant can find.
What is refused: any claim to know how a model ranks sources, any promise of a citation, mention or ranking, and any figure presented as a measured standing inside a third party's system. The Authority Rating is OG01's own measurement and is not a Google, OpenAI, Microsoft, Anthropic, Perplexity or xAI metric.
Remediation is a separate five-card product — the four scoring cards plus Local Intelligence, which is a remediation workstream and does not feed the composite rating.
Practical questions
Should we stop investing in traditional SEO?
Can our existing SEO team do this work?
Why not just track our position in AI answers?
Does AI SEO work faster or slower than traditional SEO?
Will more content improve AI visibility?
Do all the AI engines behave the same way?
A free reading returns your Authority Rating across the four scoring cards and the first things working against you.