SEO and AEO are siblings in the same family of practices but optimise for different surfaces and outcomes. SEO targets ranking links on a search results page. AEO targets being cited inside the AI-generated answer itself. Most brands need both through the rest of the decade. And both are the first phase of a bigger shift: from being ranked and cited to controlling how AI understands your organisation.
When someone searched in 2015, they typed a query and got ten blue links. SEO optimised which links appeared and in what order. When someone asks in 2026, they get a synthesised answer composed from many sources at once. AEO optimises which sources the AI selects when composing that answer. The work is technically related; the outcome metric is fundamentally different.
| Dimension | SEO | AEO |
|---|---|---|
| Surface | Google, Bing search results pages | ChatGPT, Perplexity, Gemini, Claude, Copilot answers |
| Goal | Rank in a list of links | Be cited inside the synthesised answer |
| Primary metric | Rank position, organic clicks, traffic | Citation rate, share of voice, accuracy |
| Competitive set | Other pages on the same query | Other brands AI considers authoritative |
| Click outcome | User visits your page | User often gets the answer with no click (zero-click) |
| Content shape | Long-form pages with keywords and links | Answer-shaped pages with extractable facts and FAQ blocks |
| Authority signals | Backlinks, domain rating, page authority | Entity recognition, third-party source presence, structured data |
| Most influenced by | Owned content + backlinks | Owned content + 74-92% from third-party sources (Wikipedia, Reddit, G2, news) |
| Update cadence | Daily/weekly visible movement | Daily, but with model-specific drift over time |
| Tooling | Ahrefs, Semrush, Moz, Search Console | Specialist AEO platforms (Kodiac, HubSpot AEO, Profound, Peec, Otterly, others) |
Many of the practices that make a brand visible to search engines also make it visible to AI. Strong SEO foundations make AEO easier and faster to ship.
Schema.org markup helps both Google rank a page and AI extract a fact from it. Organization, Product, FAQPage, HowTo, Article, and BreadcrumbList all do double duty.
Clear writing, precise headings, and explicit fact statements reward both search engines and AI retrievers. Vague prose damages both.
Backlinks still matter for SEO and continue to matter as authority signals for AI systems. Trade press coverage builds both ranking and citation worthiness.
A site that's fast and easy to crawl is rewarded by Googlebot and by GPTBot, ClaudeBot, PerplexityBot, and the rest. The cost of getting this wrong is doubled.
Some AEO disciplines have no SEO counterpart. These are the areas where SEO teams typically need to add new capability, not just adjust existing practice.
SEO teams traditionally focus on owned content. AEO recognises that the majority of how AI describes a brand comes from third-party sources. University of Toronto research found AI search engines cite earned media (Reddit, Wikipedia, G2, Hacker News, news) 74-92% of the time across categories. Source-level monitoring and intervention is a new discipline most SEO teams have not previously owned.
SEO is dominated by Google in most markets. AEO requires continuous tracking across at least five major AI systems - ChatGPT, Perplexity, Gemini, Claude, Copilot. Each has different source preferences and different update cadences.
SEO content patterns favour comprehensive long-form pages. AEO rewards independent extractability - the first 1–2 sentences must answer the question, key facts must stand alone, and FAQ blocks must map directly to actual buyer queries. The content shape is genuinely different.
SEO targets pages ranking. AEO requires the AI system to recognise your brand as an entity and treat it as authoritative for your category. That's Wikipedia, Wikidata, Knowledge Panel, consistent NAP data, and authoritative third-party mentions - an entity engineering layer above content.
SEO and AEO both optimise how you are found. Neither, on its own, gives you control over what AI knows about you. Organisations have lost control over how AI understands them — that is the problem underneath every visibility score. Kodiac is the control layer for AI-mediated discovery, built as three phases of one journey.
Phase 1 · Understand what AI is doing
See how AI currently understands your organisation — diagnosis, benchmarking and prioritised recommendations across the major AI systems.
Learn more →Phase 2 · Influence what AI does
Actively improve how AI understands you — structured content, schema, taxonomy, knowledge graphs, governance and API delivery across your existing systems.
Learn more →Phase 3 · Become the system AI depends on
Participate directly in AI-mediated decisions — a governed Brand Agent serving trusted, real-time answers over MCP and trusted APIs.
Learn more →The audit is Phase 1: see how AI understands you before you change anything. Free three-layer audit. AI visibility score across 5 systems. 10-dimension Website Score. Top 10 third-party sources. No credit card.
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