Published 18 September 2026
Every few months a new acronym arrives promising that search has been reinvented and your current work is obsolete. AEO and GEO have been getting that treatment for about a year now.
The honest position is less dramatic and more useful: the foundations of all three are the same, the target is different, and the measurement is where most teams get lost. Here is what actually changes.
The one-line version
SEO competes for a position in a ranked list of links. AEO competes to be the source an assistant quotes when it composes a direct answer. GEO competes for presence and framing inside longer generated summaries — including how your category gets described when you are not the subject of the question.
That is the whole distinction. Everything else is implementation detail, and most of that detail is shared.
What all three still require
Crawlable, well-structured pages. An assistant cannot cite what it cannot parse, and the parsing bar is higher, not lower, than it was for classic crawling.
Genuine expertise expressed specifically. Generic content did badly in search before generative answers and does worse now, because a summarising model has no reason to quote a page that says what every other page says.
Clean entity data — consistent naming, real authorship, corroborating mentions elsewhere. Engines need to be confident enough about who you are to put your name next to a claim.
Schema markup. It does not make you worth quoting, but it makes you easier to parse correctly, and the cost of adding it is close to zero.
What genuinely changes: the unit of success
In SEO, the unit is a ranking for a query. You can watch it, chart it, and mostly reproduce it.
In AEO, the unit is a citation. You are either the source the answer was composed from or you are not, and there is no position four to settle for. This makes results lumpier: you can be cited for a question you never targeted and absent from one you optimised hard for.
In GEO, the unit is closer to share of narrative. When someone asks an assistant to compare options in your category, are you in the set being compared, and is the description of you the one you would have written? Both halves matter, and the second half is the one most teams never check.
What genuinely changes: how you measure
Rank tracking does not transfer. Assistants are non-deterministic — the same prompt can produce different sources on consecutive runs — so a single observation tells you nothing.
What works is sampling. Fix a set of buyer prompts, run them across the major assistants on a schedule, and record how often you are cited, what you are cited for, and who is cited instead. Trends across weeks are meaningful; any individual response is noise.
Pair that with the boring stuff that still works: branded search volume, direct traffic, and whether your commercial pages are still earning visits. Generative answers reduce clicks on informational queries whether or not you invest — the response is to be the cited brand in those answers and keep your commercial pages sharp.
What this means for sequencing
If your technical foundation is weak, fix it first. It is the shared dependency for all three, and it is the only part with predictable returns.
If your content is thin, AEO and GEO will not rescue it. A model summarising your category has no incentive to quote a page with nothing specific in it.
If both are solid, the incremental AEO and GEO work is mostly restructuring what you already know into answerable units, building corroboration, and standing up the measurement. That is a quarter of work, not a replatform.
And if someone offers you guaranteed placement in AI Overviews, walk. There is no submission process and no ads product for it.