GEO vs SEO: what actually changes, what doesn't

The distinction is not a clean technical boundary: Google's AI Search guidance says existing SEO practices still apply. This article compares workflows; it does not claim that every assistant retrieves or ranks sources like Google.

The tempting frame is "GEO is the new SEO". It's half right. Most SEO fundamentals still matter, because AI answer engines read the same web Google does. But three assumptions at the heart of SEO break, and they change how you should spend effort.

Broken assumption 1: there is a ranking

Search results and AI answers present options differently. An AI answer may contain a short list, a longer comparison or links without a brand recommendation. Track mention rate, position and citations separately, then use referral and conversion data to understand their business value. None of these visibility measures alone proves a customer outcome.

This changes what "winning" even looks like as a target. An SEO roadmap can chase a page from position eight to position four and call that real progress. A GEO roadmap chasing the equivalent - going from "named in 2 of 10 runs" to "named in 3 of 10" - is directionally similar progress, but the finish line that actually matters commercially is much further out: being named reliably enough that it stops being a coin flip whether a given buyer sees you at all.

Broken assumption 2: results are stable

The same ChatGPT question can name different brands across consecutive runs. A one-off audit shows what happened in that snapshot; repeated comparable runs are needed to assess a trend. Arcanoris samples each question once per provider per audit. Monitoring or manual re-runs gather later observations, using the plan's check allowance.

Broken assumption 3: the click is the prize

SEO ends with a visit to your page. An AI answer often ends the journey right there: the user asks, reads the recommendation, and acts. Your brand needs to survive being paraphrased. If your positioning only works when someone reads your homepage hero, it doesn't work in this channel at all.

This is the assumption teams underestimate the most, because it means some of your best-converting SEO copy - the kind written to be read in full, with a careful build-up to the offer - is nearly useless as GEO material. What survives paraphrasing is a short, self-contained, factual claim: a price, a specific capability, a named use case. If a sentence needs the three sentences before it to make sense, an assistant summarizing your page will drop the setup and keep only the claim, and that claim needs to stand on its own.

What carries over intact

• Crawlability and clean HTML - AI crawlers are less forgiving than Googlebot, not more.
• Authoritative backlinks and third-party mentions - they now double as citation candidates for grounded answers.
• Clear, factual on-page copy - it was good for featured snippets; it's essential for synthesis.
• Structured data - schema.org markup helps both channels for the same reason.

How to split your effort

Don't abandon SEO - the pages that rank are disproportionately the pages AI answers cite, so SEO is upstream of GEO. What changes is measurement and targeting: add AI answer sampling to your reporting, treat cited sources as your outreach list, and judge content by whether an assistant could accurately recommend you from it alone.

In practice that's less a budget reallocation than an additional column on the same spreadsheet. Keep doing the SEO work that earns citable pages - reviews, comparisons, documentation, backlinks. Add one recurring line item that didn't exist before: sampling AI answers on a schedule, the same way you already track rankings, so a shift in what the assistants say doesn't go unnoticed for months.