AEO vs SEO: What Changes, and Where GEO Fits

Answer engine optimization (AEO) is the work of making your content the answer a search feature or assistant gives, rather than one of the links it ranks. It shares almost everything underneath with SEO: the page has to be crawlable, indexed, useful and trusted. Google's documentation on AI features says that to appear as a supporting link in AI Overviews or AI Mode, a page must be indexed and eligible to be shown with a snippet in regular Search. No SEO, no AEO.

What differs is everything that sits on top. SEO targets a ranked list of links and succeeds on position and clicks. AEO targets the places that return one answer (featured snippets, People Also Ask, voice results and AI answers) and succeeds when your words are the quoted answer or your page is the cited source, whether or not anyone clicks. That pulls the content toward a direct answer first, headings phrased as questions and structured data that matches the visible text. And it has to be measured differently, because a rank tracker cannot tell you whether you were the answer.

Where AEO came from

The term predates ChatGPT. It grew up around featured snippets, which Google describes as "special boxes where the format of a regular search result is reversed, showing the descriptive snippet first." It also grew up around voice. When Google explained featured snippets in January 2018, it tied them to the growth of voice assistants, where a list of ten links does not work, and said that for spoken results "we cite the source page in the spoken result."

That is AEO in its original form: one answer, one named source. Generative AI stretched the term to cover AI Overviews and chat search, which is where the confusion with GEO starts.

What AEO shares with SEO

Google is blunt about the overlap. Its guide to optimizing for generative AI features names both acronyms and says: "From Google Search's perspective, optimizing for generative AI search is optimizing for the search experience, and thus still SEO." The same guide says you can ignore tactics like "chunking" content, creating AI text files such as llms.txt, or "pursuing inauthentic mentions."

What carries over unchanged:

• Access. Crawlers must be able to reach the page, and it must be indexed.
• Quality. Google's guide pushes "non-commodity" content: expert or experienced takes that go beyond common knowledge.
• Trust. Named authors, a real organization behind the page and sourced claims matter on every surface.
• Page experience. A cluttered page that hides its main content disappoints visitors whether they arrive from a link or an answer.

So is AEO just SEO? For Google's systems, largely yes. For planning and reporting, no. The target, the metric and the measurement differ enough that a team optimizing only for rank will miss what is happening on the answer surfaces.

What actually differs

The target surface

SEO aims at the ranked list. AEO aims at the boxes and summaries above and around it, and those are now the norm rather than the exception. Semrush's study of more than 10 million keywords found AI Overviews on 6.49% of queries in January 2025, peaking at 24.61% in July and settling at 15.69% by November. It also found People Also Ask alongside 90.03% of AI Overviews, so the answer surfaces tend to arrive together.

They are also spreading beyond simple questions. In the same study, informational queries made up 91.3% of AI Overview triggers in January 2025 and 57.1% by October, with commercial and transactional searches taking a growing share.

The success metric

SEO counts position and clicks. AEO counts whether you were the answer. The two diverge because the answer keeps the reader.

Pew Research Center tracked 900 US adults' Google searches in March 2025. Users who saw an AI summary clicked a traditional result in 8% of visits, against 15% when there was no summary, and clicked a link inside the summary in just 1% of visits. Ahrefs, using December 2025 data on 300,000 keywords, found the presence of an AI Overview correlated with a 58% lower average clickthrough rate for the top-ranking page.

The consequence: a page can win the answer and lose the click. If your only metric is traffic, you will read a win as a loss. Being the quoted source still carries your framing and your name to the reader, which is the point of AEO.

The content shape

Search features lift passages, not pages. A page built for extraction looks different from one built only to rank:

• The answer sits in the first sentence or two under a heading that states the question.
• Steps are numbered lists; comparisons are tables.
• Each section can be read on its own without the paragraph before it.
• Structured data describes what is visibly on the page, and nothing more.

That last point needs care, because a lot of AEO advice oversells markup. Google says site owners cannot mark a page as a featured snippet: its systems decide whether a page "would make a good featured snippet" and elevate it. For AI features, it says there is no special schema.org structured data to add. And the FAQ rich result, long the poster child of AEO markup, was limited to "well-known, authoritative government and health websites" in 2023 and no longer appears in Google Search from May 7, 2026. FAQPage markup can still help other systems read your questions and answers. It will not win you a box.

Voice-specific markup is narrower still. Google's speakable structured data is in beta and works for US users with Google Home devices set to English, for English-language news publishers. For most B2B sites, voice answers come through the same featured snippets as everything else.

The measurement

SEO has mature tools: rank trackers and Search Console clicks. AEO needs three views:

• Snippet and People Also Ask ownership. Which of your target queries show your text as the answer.
• Google's AI features. Google launched generative AI performance reports in Search Console on June 3, 2026 and says they reached all websites worldwide as of August 31, 2026. They show impressions, pages, countries, devices and dates for AI Overviews, AI Mode and AI features in Discover. They report impressions, not clicks.
• Chat engines. For ChatGPT, Perplexity and Gemini you measure from the outside, by running a fixed set of prompts on a schedule and recording whether you are mentioned and cited.

The third view needs volume. SparkToro's research across 2,961 prompts found ChatGPT and Google AI Overviews returned the same list of brands less than 1% of the time on repeated runs. A single check tells you almost nothing; a rate across many runs tells you where you stand.

AEO vs SEO vs GEO at a glance

Where GEO fits

Generative engine optimization (GEO) comes from research rather than practice. The Princeton paper that named it describes generative engines as systems that "satisfy queries by synthesizing information from multiple sources and summarizing them using LLMs," and reports that GEO methods can boost visibility "by up to 40%" in their responses.

The useful way to read it: GEO is the part of AEO aimed at generative engines. The distinction that matters is extraction versus synthesis.

• A featured snippet extracts one passage from one page. You either own the box or you do not.
• A generative answer synthesizes several sources and may name several brands. You can be one of five citations, mentioned without a link, or absent, and the result changes from run to run.

That changes two things. The metric becomes a rate (how often you are mentioned or cited across many prompts) rather than a yes or no. And access becomes engine-specific: OpenAI's crawler documentation says sites opted out of OAI-SearchBot "will not be shown in ChatGPT search answers," while Perplexity's documentation says PerplexityBot is "designed to surface and link websites in search results on Perplexity." Google AI Overviews, by contrast, run on Google's index and ordinary Googlebot access.

For how the GEO layer changes content strategy as a whole, see GEO vs SEO. For engine-by-engine tactics, including which sources each engine leans on, see how to get cited by ChatGPT, Perplexity and AI Overviews. The short version for this article: every GEO tactic is also an AEO tactic, and none of them work on a page that fails basic SEO.

Where to put effort, by query type

The acronyms matter less than the query. Sort your target queries by what the searcher wants, then weight effort accordingly.

• Definitions and quick facts ("what is X", "when did Y launch"). Lean AEO. One clear answer satisfies the searcher, so aim to be that answer and expect few clicks.
• How-to questions. AEO and SEO together. The summary gets lifted; people who need the full steps still click. Use a numbered list with a one-line answer above it.
• Comparisons and research questions ("X vs Y", "how do teams handle Z"). Lean GEO. Generative engines assemble these answers from several sources, so third-party mentions and a clear comparison table on your own page both count.
• Commercial queries ("best X for Y", "X alternatives", "X pricing"). Lean SEO, but watch the Semrush trend above: AI Overviews are appearing on more commercial searches, so track these on the answer surfaces too.
• Branded queries. SEO first, plus accuracy. Check what the engines say about your product, because a wrong answer about your pricing or features costs more than a lost ranking.

A simple rule: if a two-sentence answer would fully satisfy the searcher, optimize to be that answer. If the searcher needs to compare, evaluate or act, optimize for the click as well.

Checklist: make a page answer-ready

Run this on any page you want quoted:

1. State the question. Use it, or a close paraphrase, as an H2 or in the title.
2. Answer in the first two sentences under that heading, in plain declarative language. Detail comes after.
3. Make sections stand alone. Each should make sense if lifted without the paragraph before it.
4. Use lists for steps and tables for comparisons. They are the formats search features lift most cleanly.
5. Source every factual claim with a link to the primary source. In the Princeton study, citing sources, adding quotations and adding statistics were the top-performing methods.
6. Answer the neighbouring questions. Google's AI features use query fan-out, "issuing multiple related searches across subtopics and data sources," so cover the People Also Ask questions around your main one.
7. Keep structured data honest. Mark up only what is visible, and treat it as description, not a ranking lever.
8. Check crawler access for Googlebot, OAI-SearchBot and PerplexityBot in your robots.txt.
9. Use snippet controls deliberately. data-nosnippet keeps a passage, such as a pricing caveat, from being quoted out of context.
10. Keep the date and facts current. Engines that search live compare your page with whatever was published last.

Then measure. Veritas tracks four AI engines (ChatGPT, Perplexity, Gemini and Google AI Overviews) every two weeks, with on-demand checks, on every plan. It turns the gaps it finds into GEO and AEO recommendations inside the editor, where drafts are written with a citation on every knowledge-based claim. The AEO and GEO tool covers the recommendations; the AI Overview tracker covers Google's answers.

Closing

AEO vs SEO is a smaller fight than the search results suggest. The foundations are the same, and Google says so. The difference is where you aim and how you keep score: rank and clicks for the list, quotes and citations for the answer. GEO is the same idea applied to engines that write their answers from several sources.

Treat the three as one piece of work with three scoreboards. Write the answer first, source it, keep the page crawlable, and measure each surface on its own terms.

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Want to see where AI answers mention and cite you, and where they do not? Get started with Veritas.

Related reading: Schema Markup for the AI Search Era: What Still Matters · Generative Engine Optimization (GEO): A 2026 Guide.