Answer Engine Optimization (AEO) is the practice of getting your content cited in the direct answers AI systems give, instead of only ranking as a blue link. The "answer engines" are tools like Google's AI Overviews and AI Mode, ChatGPT, Perplexity, Claude and Gemini, all of which read the web, synthesize an answer, and cite a handful of sources. AEO is the work of becoming one of those cited sources.
What Google says
“There are no additional requirements to appear in AI Overviews or AI Mode, nor other special optimizations necessary.”
Why this matters for AI Overviews
Search is splitting into two jobs. The classic job, rank a page and earn the click, still exists. The new job is to be the source an answer engine quotes when it writes the answer for the user. For a growing share of questions, the answer engine is the destination and the citation is the only visibility you get.
Here is the honest part, the part most "AEO" pitches skip: for Google's AI Overviews specifically, there is no separate optimization layer. That quote above means there is no AEO checklist that unlocks Google's AI answers, no file to ship, no schema type to add, no setting to flip. The same content and links that earn strong organic rankings are what make you eligible to be cited. We went through the most common myths about this in the AI Overview myths, and most paid "AEO" tactics are on that list.
Across the other answer engines (ChatGPT, Perplexity and the rest) the mechanics differ, but the direction is the same: they cite sources they can find, trust, and easily lift a clear answer from. AEO done honestly is mostly just good, genuinely useful content a model could not have written from common knowledge, made easy to quote.
How to fix it
There is no switch to flip, but there is real work that helps:
- Answer the actual question, early and plainly. Lead with a direct, self-contained answer a model can lift in one or two sentences, then expand. Burying the answer under 800 words of preamble makes you hard to cite.
- Earn genuine authority, not inauthentic mentions. Real citations, real expertise, real links. Google has been explicit that chasing fake mentions backfires.
- Structure for extraction. Clear headings, short paragraphs, lists and tables where they fit. This helps both rich-result eligibility and an engine pulling a clean quote.
- Cover the sub-questions. Answer engines fan a query out into related questions. Pages that genuinely cover the topic, not one keyword, get cited across more of them.
- Measure whether it is working. You cannot optimize what you cannot see. Track which prompts cite you, and which competitors get cited instead, with an answer-engine tracker like MentionScout. For the Google side specifically, the AI Overview Checker audits your eligibility against Google's own rules.
The order matters. Do the content and authority work first. The tools tell you whether it landed.
Common mistakes when implementing the fix
- Buying an "AEO package" that ships files or schema for Google. There is nothing to ship; see the myths.
- Optimizing blind. Treating AEO as a checklist instead of measuring real citations means you never learn what actually got you cited.
- Writing for the model instead of the reader. Commodity content a model already knows does not earn a citation. The bar is content the model could not have produced itself.
