Is AEO the same as SEO? Differences in 2025

Updated 4th September 2025

No. SEO optimises for search engine rankings through backlinks, keywords, and site authority. AEO optimises for AI citations through entity clarity, passage-level answers, and third-party validation (Wikipedia, Reddit, industry forums). You need both: SEO gets you indexed and ranked, AEO gets you cited and recommended in AI Overviews, Copilot, and Perplexity.

I keep hearing SEO agencies say "AEO is just SEO with a fancy name." Their argument: AI models pull from top-ranking Google pages, so just do good SEO and you're sorted. This fundamentally misunderstands how AI agents work.

Here's what's actually happening: AI agents don't just scrape the top 10. They generate dozens of synthetic queries from your single question (query fan-out). They pull passages based on semantic similarity, not keywords. And they personalise results based on your search history and context. Two people asking the same question get different answers. According to Ahrefs' analysis of 15,000 AI responses, on average only 12% of AI-cited URLs rank in Google's top 10. The other 88%? They're winning on passage-level relevance, entity clarity, and freshness.

The gap will only widen. As AI agents evolve from retrieving information to taking actions (booking, buying, comparing), traditional SEO's "rank for keywords" playbook becomes even less relevant. You need both approaches, but pretending they're the same thing is why most B2B sites are invisible to AI despite ranking well.

So while high-quality content is the common denominator across both SEO and AEO, the tactics, techniques and procedures (TTPs) to succeed are different. It's like Google Ads versus LinkedIn Ads. They're both advertising platforms with shared concepts and technologies. You need a base understanding of advertising for both. But a winning Google Ads strategy doesn't translate to a winning LinkedIn Ads strategy. Same with SEO and AEO.

Search isn't just "ten blue links" anymore. Buyers increasingly get a single, AI-assembled answer at the top of the SERP or inside a chat UI. It comes with a handful of source links. Google confirms AI features still rely on the same index, crawler, and best-practice guidance as classic search. SEO fundamentals remain non-negotiable. But answer engines select passages and snippets, not just pages. They attach citations differently too. Google AI Overviews link out, Bing Copilot footnotes sources, Perplexity always shows references. If you're only optimising for rankings, you'll miss the answer box. If you're only optimising for answers, you'll lack the authority to be chosen.

What we learned (so far)

1. SEO fundamentals still power AI answers. Crawlability, content quality, and E-E-A-T signals remain table stakes.
2. AI picks passages, not just pages. Clear, self-contained answers are more likely to be extracted and cited.
3. Third-party validation matters more than backlinks. AI models heavily weight Wikipedia mentions, Reddit discussions, and community forums when selecting sources.
4. Entities and structure decide eligibility. Named entities + schema = faster machine understanding and fewer attribution errors.
5. Measure mentions, not just positions. Track Share of Voice and citation rate across AI engines alongside rankings.
6. Heavy client-side rendering risks invisibility. If content isn't in the HTML, some engines won't see it (practical AEO finding).

Definitions: AEO vs SEO in one page

SEO (Search Engine Optimisation): The practice of making your site discoverable, indexable, and trusted so it ranks and earns clicks. Work spans technical SEO, information architecture, content strategy, and authority building. Core outputs: rankings, impressions, organic sessions, assisted conversions.

AEO (Answer Engine Optimisation): The practice of making your content answer-ready and citable. AI systems can then extract, ground, and attribute it inside Google's AI features, Bing Copilot Search, Perplexity, and voice responses. Work spans entity alignment, answer-first formatting, Q&A clusters, structured data, and passage-level optimisation. Crucially, it includes third-party validation through Wikipedia presence, Reddit discussions, and industry communities. Core outputs: citations, mentions, and Share of Voice.

Thesis: AEO complements SEO with different objectives. SEO targets rankings and clicks. AEO targets citations and recommendations where buyers now get instant answers.

How AI answers get built (and where SEO still matters)

Below is a light-on-jargon view of modern answer engines (as of August 2025). It's general enough to cover Google AI Overviews, Bing Copilot, and Perplexity, and aligns with their public docs.

Model mechanics (under the hood)

1. Query understanding & expansion. The system interprets intent and fans out into sub-questions ("what, why, risks, steps"), ensuring coverage of the whole task. Variants and synonyms are explored to widen recall.
2. Retrieval (dense & lexical) and re-ranking. It pulls candidate passages from a web index using combinations of classic information retrieval (IR) methods like BM25 and embedding-based retrieval. A learned re-ranker promotes passages that better match intent and evidence signals (definitions, steps, comparisons).
3. Entity disambiguation & knowledge signals. Knowledge graph data helps resolve entities (e.g., "Apple Inc." vs the fruit) and provides prior context about organisations, products, people, and relationships.
4. Passage-level scoring. Systems score chunks (paragraphs, list items, table rows) rather than entire pages. Scoring features include proximity to a question-like heading and definitional phrasing. They also look for units, dates, citations, and structural cues like lists and tables.
5. Synthesis with grounding and attribution. A draft answer is composed, then grounded against sources to reduce hallucinations. UI layers display citations: Google links out from highlighted terms, Bing Copilot uses footnotes, Perplexity shows a source list for every answer.
6. Freshness & controls. Recency cues (updated timestamps, new crawl dates) can affect selection. Standard web controls (e.g., `nosnippet`) also govern snippet reuse in AI surfaces.

Where SEO still matters most:

• Crawlability & access. Googlebot/Bingbot must fetch your content. Slow responses, blocked resources, or content that only appears after heavy JS can harm inclusion.
• E-E-A-T & intent match. Rater guidance continues to prioritise experience, expertise, authoritativeness, and trust, especially for sensitive topics.
• Featured snippet patterns. The same signals that power featured snippets (short, direct, structured answers) often drive AI extractions.
• Entity clarity. Explicit Organization/Person/Product markup and consistent on-page naming reduce ambiguity and mis-attribution.

Ship knowledge in single-serving portions. Short, labelled, self-contained answers an assistant can pick up and credit.

Practical differences: workflows, formats, KPIs

Comparison table

30-second AEO play (ship this this week)

1. Pick five buyer questions. Use PAA, sales calls, support logs to pick real ones.
2. Add an answer block per page. Question as H2, 2-sentence answer immediately below.
3. Mark it up. Add FAQPage or HowTo schema where real. Validate and ship.
4. Make it citable. Ensure the answer makes sense pasted out of context.
5. Refresh dates. Update stats and add a visible `` element.

Engine patterns we actually observe (what gets cited)

From our ongoing AEO work and benchmarking, we consistently see:

• Listicles and comparisons over-index. List-style and comparison pages are disproportionately cited by answer engines. They're tidy to extract (titles, bullets, tables).
• Definitions, steps, and tables travel well. Short definitions (40-80 words), numbered procedures, and row-level comparisons are frequent lift-outs.
• Freshness helps, within reason. Recently updated content is chosen more often when topics are time-sensitive.
• JS-heavy pages underperform. Content that relies on client-side rendering is less likely to be selected than equivalent static HTML.
• New content can be cited fast. We commonly see 48-72 hours from publish/update to first inclusion for narrow queries (varies by engine and crawl).

These are operational observations rather than hard rules. Your mileage will vary by topic and authority. They align with public guidance: structure, clarity, and eligibility win.

AEO Measurement Mini-Framework (how to know it's working)

What to measure

• Share of Voice (SoV). % of monitored prompts where your brand is present in the answer (any engine).
  • By engine: SoV-AIO, SoV-Copilot, SoV-Perplexity.
  • By intent: definitional, comparative, how-to, pros/cons.
• Citation Rate. Average number of explicit citations to your content per answer (where citations exist, e.g., Copilot, Perplexity).
• Engine Coverage. How many engines have cited you at least once for a monitored topic cluster.
• Passage Win Rate. % of tested Q→A blocks that have been observed as the cited passage at least once (helps you tune wording and placement).
• AI Referrals & Assisted Conversions. Sessions originating from AI surfaces (where referrers are exposed), plus downstream conversions attributed to AI-exposed users.

How to sample

• Build a query set of 50-150 buyer-relevant prompts across 4 types: what is, how to, X vs Y, best tools for Z.
• Weekly sweep across AIO, Copilot, Perplexity (logged-out where possible). Note presence, citation count, and which passage was lifted.
• Quarterly re-baseline the query set as products or messaging change.

Targets (initial)

• SoV (any engine): 20-30% within 90 days for long-tail clusters.
• Passage Win Rate: ≥40% for your top 25 Q&A blocks after two iteration cycles.
• Engine Coverage: ≥2 engines citing you for each priority topic cluster.

Attribution notes

• Clicks may be lower than classic SERP CTR. Intent is higher. Track branded search lift and direct traffic alongside AI referrals.
• Use UTM parameters where links allow (e.g., Perplexity often preserves outbound URLs) to separate AI-sourced sessions.

"AEO is just good SEO"… and other objections

• "Google says we don't need a new framework." Google says this about their AI Overviews specifically. But ChatGPT, Perplexity, Claude, and others are entirely separate platforms with their own retrieval systems, training data, and ranking signals. Even if Google's advice were universal (it's not), operationalising for answers still changes the work: prioritise passage-level clarity, Q&A blocks, citability, and citation KPIs.
• "Won't this cannibalise clicks?" Sometimes. But being the cited source builds recall and trust. The clicks you do get tend to be higher intent. Absence from the answer = zero visibility.
• "FAQ/How-To schema was dialled back, why use it?" Google reduced rich-result display for FAQ/How-To (UI choice), but structured data still helps machine understanding and can support AI selection. Use it for meaning, not for the badge.

Discovered's POV: how we integrate AEO with your SEO

We help teams win where decisions now happen: inside AI answers and SERPs. We don't need to replace your agency or in-house SEO. We add the scaffolding that makes your best content citable.

What we ship

• Entity-first architecture. Align brand, product, and people entities. Fix Organization schema.
• Answer patterns. Templates for definitions, comparisons, pros/cons, steps, and featured-snippet blocks. Answer-first and copy-safe.
• Structured data coverage. Article, Organization, BreadcrumbList, FAQ/HowTo where warranted.
• Measurement that fits 2025. Dashboards for Share of Voice, citation rate across AI Overviews / Copilot / Perplexity, and PAA presence.

If you want a pragmatic plan for your top 10 buyer questions, book an AEO Strategy Call or request an AEO+SEO audit. We'll help your brand become the answer.

Pitfalls & edge cases

• Heavy client-side rendering. If your main content requires JS to render, some answer engines won't see it. Pre-render important pages (SSR/SSG).
• Ambiguous entities. If your brand or product name collides with a common noun, add disambiguation on page (e.g., "Acme (B2B payments platform)").
• YMYL topics. Expect higher trust thresholds and stricter source selection.
• Out-of-date stats. Stale numbers are less likely to be lifted. Date your facts and refresh quarterly.
• Regional variance. Features vary by country and login state. Test from your key markets.

Frequently Asked Questions

Is AEO a separate discipline from SEO? They're complementary but distinct disciplines. Like Google Ads versus LinkedIn Ads, they share foundational concepts but require different tactics, inputs, and success metrics. SEO targets rankings through backlinks and keywords. AEO targets citations through entity clarity and third-party validation.

How do I know if AEO is working? Track Share of Voice, citation rate, engine coverage, and AI referrals. Iterate on Q&A blocks until your passage win rate improves.

Do I need schema for AEO? Strictly, no. Practically, yes. It improves machine understanding and eligibility. Use Article, Organization, BreadcrumbList, and FAQ/HowTo where genuine.

What content formats get cited most? Short definitions, numbered steps, comparison tables, and listicles. Each section should stand alone as a copy-safe answer.

Will this change our voice? It shouldn't. We keep your tone. We structure it so machines can recognise and reuse your best paragraphs.