Is AEO Just Recycled SEO? What's Actually New

Mostly, yes. In our judgment about four-fifths of what is sold as AEO (answer engine optimization) is ordinary SEO under a new label, and Google's own guide points the same way: it calls optimizing for its AI features "still SEO". The new part is smaller and more useful: measuring by sampled prompts, earning proof on pages you do not own, and testing each engine separately. The 80/20 split is our opinion, not a measured share.

We sell an AI visibility audit, so we gain if you believe AEO is a separate discipline. That is why every claim below links to engine documentation or a published study, and why our own data is labelled small and self-selected. For the SEO team's transition plan, read AEO vs SEO: what changes; for definitions of AEO, GEO and SEO, see AEO vs GEO vs SEO.

Is AEO just rebranded SEO?

For the most part, yes. A quick test: would this advice have appeared in a 2018 SEO audit? If so, it is recycled. Sorting today's common AEO advice that way gives a short list of what is new and a long list of what is not.

Why does so much AEO advice overlap with SEO?

Because engines retrieve before they write. Google's AI features use retrieval-augmented generation over its Search index plus "query fan-out", extra related searches the model issues for the user. ChatGPT search and Perplexity run crawlers of their own. If a page cannot be fetched, indexed and understood, no answer can use it.

• Access is the first gate. OpenAI says sites opted out of OAI-SearchBot will not be shown in ChatGPT search answers. Perplexity says PerplexityBot exists to surface and link sites in its results, not to train models.
• For most brands that gate is already open. In AEOeye's crawler access study (384 robots.txt files read on 3 October 2026; a convenience sample, not the web), 1 of 193 SaaS sites blocked any AI retrieval bot. 27 of 38 news publishers did.
• So a missing recommendation is rarely a crawl problem. Crawlability is recycled advice, but it is table stakes, not the explanation.

The label also survives for commercial reasons. Wikipedia reports a 2025 Forrester argument that AEO differs significantly but not fundamentally from SEO, and that advocates exaggerate the gap to sell new tools. Be sceptical of anyone, us included, whose product needs the difference to be large.

What is genuinely new in AEO?

Three things have no SEO equivalent: you measure by sampling instead of reading a rank, you need proof on pages you do not control, and each engine sources differently. Everything else is craft an SEO team already has.

How do you measure something with no rank?

You sample it. In a SparkToro and Gumshoe.ai study, 600 volunteers ran 12 prompts through ChatGPT, Claude and Google's AI 2,961 times in late 2025. The chance that two responses from ChatGPT or Google's AI listed the same brands was under 1 in 100. The authors still called visibility percentage across dozens to hundreds of repeated prompts a reasonable metric.

Our own audit records show why the baseline matters. Across 127 completed audits and 892 engine answers (June to September 2026), brands were named in 17.6% of answers, and when a brand was ranked it was first in 71.4% of 147 ranked mentions. The sample is small and self-selected, and engines are unevenly represented, so we do not rank engines with it. It says only that being named at all is the hard part.

Why does proof on other people's pages matter more?

AI engines lean harder on independent sources than Google's results do. In a September 2025 preprint, a search-enabled GPT-4o drew 72.7% of cited domains for US software prompts from earned media, such as reviews and independent publishers. Google's results were 45.4% earned and 43.7% brand-owned, against 26.7% brand-owned in the AI answers.

That is link building's cousin, not its twin: the target is the page an answer cites. It is also getting harder to engineer. In our study, 27 of 38 news publishers (71.1%) blocked at least one AI retrieval bot, so check an outlet's robots.txt before paying for a placement.

Do all engines source the same way?

No, so one test is never enough. In the same preprint's consumer-electronics test, Claude and GPT took about 94% of cited domains from earned media. Perplexity took about 53%, with roughly 32% brand-owned and 15% social. Those were 2025 models, so treat it as a reason to re-test, not a ranking.

Which AEO advice should you ignore?

Ignore anything that treats AI visibility as a trick: special files, schema shortcuts, rewriting pages for machines, and padding. Google's guide lists several of these as things you can skip, and the data we found agrees.

• llms.txt as a lever. Google says Search ignores these files. llmstxt.org describes a proposal used most heavily for software documentation. Create one only if it is nearly free; our position is here.
• Schema as a citation shortcut. Ahrefs, which sells AI-visibility tracking, matched 1,885 pages that added JSON-LD between August 2025 and March 2026 against 4,000 controls and found no major uplift on Google AI Overviews, AI Mode or ChatGPT. Caveat: those pages were already heavily cited. Keep schema for rich results.
• Chunking and rewriting for machines. Google says you need not split content into tiny pieces or write a special way for AI. We still open sections with the answer, but for human skimmers, not for a parser.
• Stuffing and page-per-prompt content. The GEO paper found keyword stuffing offered little to no improvement, and 10% worse than baseline on Perplexity.ai. Google says content created for every fan-out variant to manipulate results violates its scaled content abuse policy.
• Paid mentions and tools with "inside" data. Google says inauthentic mentions are less helpful than they look and that third-party tools have no access to its internal ranking data.

We learned the cost of volume ourselves. On 24 September 2026 we retired 234 of our own posts and merged 27 duplicates after Search Console showed about half of 496 posts were unrelated to AI visibility, with 0 clicks in 90 days. On 3 October 2026 we merged another 165 pages into 42. One strong page per question is our position, not a measured result.

What should you actually do differently?

Keep your SEO, add a measurement loop, and fix the gaps it shows. These five steps are in order because each one decides whether the next is worth doing.

1. Confirm access. Check robots.txt and your CDN or firewall for OAI-SearchBot, PerplexityBot, Claude-SearchBot and Googlebot. In our study, 24 of 88 e-commerce homepages (27.3%) challenged our self-identified crawler, which robots.txt never shows. Our robots.txt generator writes the rules.
2. Write a prompt set. Draft a few dozen real buyer questions that do not name your brand.
3. Sample every engine. Run each prompt several times per engine and record whether you are named, which competitors appear and which URLs are cited. The free AEOeye audit asks three unbranded questions in ChatGPT; as of October 2026 the $29 report adds Claude, Gemini, Google AI and Perplexity and ten questions. It is a snapshot, not a daily tracker. See measuring AI visibility for the method.
4. Read the cited pages. If an answer cites your page, add specifics: figures, dates, sources. If it cites someone else's, earn accurate inclusion there.
5. Re-run the same prompts. Change one thing at a time, so a shift in the share of answers that name you has a cause.