Three letters that describe one shift
Traditional SEO is not dead — but it is no longer the whole game
Search engine optimisation, as practised since the early 2000s, is the work of helping a web page appear high in a list of blue links produced by a search engine. The signals are familiar: keywords, backlinks, page speed, mobile usability, and clean HTML. None of these signals have stopped mattering. What has changed is that the link list is no longer the only place the result of a query is shown. A growing portion of users now read a single AI-generated answer, click no link at all, and only sometimes notice which websites the answer was drawn from. Traditional SEO is one input into that answer rather than the destination of the search.
Generative engine optimisation is the discipline of being cited inside an answer
Generative engine optimisation, often shortened to GEO, is the practice of structuring a website so that large language models such as those behind ChatGPT, Claude, Gemini, Copilot, and Perplexity reliably extract, summarise, and cite its content when answering user questions. The output is not a ranked list. The output is a paragraph of synthesised prose with a small set of source attributions. A page wins by being the source the model chose to read and quote, not by sitting in third place on a search results page.
Answer engine optimisation focuses on direct, structured answers
Answer engine optimisation, or AEO, is closely related to GEO but with a narrower frame. AEO is about formatting content so that an answer engine — Google's AI Overviews, Perplexity, Bing's Copilot, voice assistants — can lift a clean, factual response straight off the page. That favours short definitions, direct comparisons, FAQ blocks, tables, and clearly labelled sections. AEO predates GEO; it grew out of the rise of featured snippets and voice search and now anchors a large part of what AI assistants do when they need a quick fact rather than a long synthesis.
AI optimisation extends the same logic to autonomous agents
Beyond chatbots, the next layer is the autonomous agent — a piece of software that visits websites on behalf of a person, compares options, fills forms, and sometimes completes purchases. AI optimisation, or AIO, is the work of preparing a site to be read, queried, and acted on by such an agent. It includes everything in GEO and AEO plus a stricter focus on machine readability: clean APIs, structured product feeds, predictable navigation, accessibility, and freshness signals. By 2030, McKinsey estimates agentic commerce could orchestrate $900 billion to $1 trillion of US business-to-consumer revenue alone, and $3 to $5 trillion globally — a shift the road-to-AGI timeline tracks as it unfolds.
Google's position: this is still SEO
In May 2026 Google published its first formal guidance on optimising for generative AI search. The position is direct. From Google's perspective, being visible in AI Overviews and AI Mode is the same work as being visible in classical Google Search, using the same crawl, the same index, and the same quality systems. GEO and AEO are noted as useful industry shorthand for a real shift in user behaviour, but Google does not treat them as separate disciplines. Most of what follows in this course is standard SEO done with discipline, plus a few agent-specific additions where the reader is in fact a machine. Lesson 16 sets out where the official Google line and the vendor frameworks from Vercel, Microsoft, and Tealium actually disagree.
When was the last time you asked a chatbot a question instead of typing the same query into a search engine? What changed about the answer, and what changed about which websites you ended up trusting?