AEO vs SEO differences now come down to where visibility is won: SEO targets rankings and SERP features, while AEO targets citations, mentions, and links inside AI answers such as ChatGPT, Perplexity, Google AI Overviews, and Google AI Mode. Semrush Blog published that framing on September 30, 2026. The change it describes is practical rather than semantic: search teams now have to measure whether content is findable in answer systems as well as on results pages.
Two days earlier, on September 28, 2026, Semrush Blog published a separate guide that folded AI crawler access, structured content, AI mentions, citations, and Share of Voice into SEO best practice. Semrush Enterprise also published research saying it analyzed the top 10,000 domains in its AI Visibility Index and found a 0.86 to 0.87 correlation between the number of keywords a domain ranked for and the number of AI citations it received across analyzed AI platforms. Semrush Enterprise says the finding is correlation, not causation, which matters because it does not prove that improving rankings alone causes more AI citations.
What AEO vs SEO differences mean
AEO means optimizing for inclusion in AI-generated answers, while SEO means optimizing for visibility in search engines and their SERP features. Semrush Blog draws that line in its September 30 guide: AEO is about citations, embedded URLs, brand mentions, and AI answers, while SEO is about rankings, featured snippets, People Also Ask, local packs, knowledge panels, AI Overviews, and AI Mode. The overlap is large because Google AI Overviews and Google AI Mode sit between conventional search and generated answers.
AI search visibility is not the same as a blue-link ranking. A page can rank well in Google and still fail to appear in a ChatGPT, Perplexity, or Google AI Mode answer. Semrush Blog says AI systems may trust the same domains that perform in Google, but they often cite deeper subpages, documentation, or blog posts instead of the exact ranking URL.
How AI citations are selected
AI citations are selected from systems that appear to weight domain trust, topical fit, extractable content, and retrieval context, not only the page that ranks highest in Google. Semrush Enterprise reports that domains with an Authority Score of 81 or higher received around nine times the median citation share of domains scoring 60 or below. That supports the practical view that authority still matters, but the source is careful to say its analysis does not establish causation.
Semrush Blog's AI Mode study gives the mechanism more shape. It says 92% of Google AI Mode queries in the study had a sidebar with links, 7% had additional links below the generated response, and 1.7% had no links. The same study says AI Mode's sidebar averaged seven unique domains, compared with three in AI Overviews, and that commercial and transactional queries produced the longest and most detailed responses across the platforms studied.
The effect for publishers is that a domain can gain AI visibility without the exact page winning the traditional result. Semrush Blog says LLMs may trust the same domains as Google organic results while citing different URLs inside those domains. For SEO teams, that makes internal coverage, documentation quality, and page-level clarity more important than tracking one canonical ranking URL for a query.
Where the evidence is still thin
The strongest evidence here is directional, not conclusive. Semrush Enterprise gives a large-domain study and a clear correlation range, but it does not say that backlinks, rankings, or Authority Score directly cause AI citations. Semrush Blog's AI Mode study describes observed link placement and domain patterns, but the evidence supplied here does not include the full query set, vertical breakdown, or platform sampling method.
Practitioner sentiment also points to a demand-side problem, but it is not a measurement source. In r/TechImpact on October 3, 2026, one poster said Google results now require digging through ads, AI results, forums, and SEO content, and two top comments expressed frustration with Google or suggested using another search engine. That Reddit thread shows a familiar complaint among users and site owners, but eight comments cannot establish how search behavior has changed at market level.
What search teams should check
Search teams should audit whether pages can be crawled, parsed, trusted, cited, and measured across both Google and AI systems. Semrush Blog's September 28 guide names specific checks: robots.txt for search and AI bot access, Google Rich Results Test for markup, author bios for credibility, Product and Offer markup for commerce, and tracking for rankings, AI mentions, citations, and Share of Voice. The useful move is to test the content system, not rewrite every page for an abstract AI audience.
| Check | File or metric | Why it matters |
|---|---|---|
| Bot access | robots.txt | Semrush Blog says search and AI crawler access is part of the technical foundation for visibility. |
| Structured data | Google Rich Results Test | Clear markup helps search and AI systems extract facts, entities, products, offers, and page meaning. |
| Commerce readiness | Product and Offer markup | Semrush Blog says agentic search and commerce need accurate pricing, specs, inventory, and identifiers. |
| AI visibility | Mentions, citations, Share of Voice | Semrush Blog says teams should measure beyond rankings and traffic when AI answers affect discovery. |
A practical content review should look for pages that answer a task in extractable form. Use logical headings, short passages that can stand alone, schema where it matches the content, and original evidence that gives another system a reason to cite the page. Semrush Blog also says author bios, reputable sources, real examples, and data support E-E-A-T signals, which remain part of the trust layer for both search and AI visibility.
What this changes for visibility
The inference for marketers is that search visibility now has two reporting layers: ranked URLs and cited entities. Organic position still matters because Semrush Enterprise found a strong correlation between keyword footprint and AI citations, but AI systems can cite different URLs within the same trusted domain. A dashboard that stops at rank, impressions, and organic clicks will miss cases where the brand appears in AI Mode, ChatGPT, Perplexity, or AI Overviews without producing a conventional click.
For paid media and content planning, the strongest supported conclusion is narrower: commercial and transactional queries deserve closer AI monitoring because Semrush Blog says those queries triggered the longest and most detailed responses in its platform study. That does not prove AI answers reduce ad clicks or organic clicks in those categories. It does mean teams bidding on commercial queries should compare Google Ads terms, organic landing pages, AI answer citations, and competitor brand mentions for the same products or services.
The next trigger to watch is measurement, not a named Google rollout in the supplied evidence. Teams should rerun the same query set after major content changes, robots.txt edits, schema updates, or shifts in Google AI Mode link presentation. If Semrush, Google, or another primary source publishes platform-level citation data with methods and dates, that will be the point where AEO moves from an adjacent workflow to a more auditable channel.