Most content still gets written for a human scanning top to bottom. Answer engines don't read that way — they extract a candidate answer, check whether it matches the question, and decide whether to quote it or move to the next source. Structuring for that extraction process is most of what AEO actually is.
Question-based headings, not keyword headings
Format your H2s and H3s as the actual questions a reader — or a model — would ask: "What is X," "How does Y work," "Why does Z matter for B2B." This isn't cosmetic. Answer engines pattern-match on headings that look like the query itself, and it's the same structure that wins Featured Snippets and People Also Ask boxes, which run on largely the same extraction logic as AI Overviews.
A quick self-test: read your own H2s out loud. If none of them sound like something you'd type into a search box, they're probably optimised for a table of contents, not for extraction.
Answer in the first 2–3 sentences
This is the single highest-leverage change most sites can make. Whatever question a heading implies, answer it directly in the first 40–60 words underneath — before background, before caveats, before "well, it depends." Expand and qualify afterward for the human reader who wants the full picture; the model has usually already extracted what it needs from that opening block.
We apply this rule to every section on our own GEO & AI Search Statistics page — each stat leads with the number and what it means, not a wind-up.
Structured formats over prose paragraphs
Lists — ordered, bulleted, and tables — are consistently easier for extraction systems to parse cleanly than dense prose. Wherever a paragraph is really a sequence of steps, a set of options, or a comparison, convert it. This doesn't mean fragmenting every sentence into a bullet; it means using structure where structure is the honest shape of the information.
FAQ schema, done properly
JSON-LD FAQPage markup tells Google's systems your content is a candidate for People Also Ask, Featured Snippets, and AI Overviews — but only when the schema matches real, visible Q&A content on the page. Every post on this blog, including this one, carries an FAQ block built the same way: a handful of genuine questions, answered directly, with matching schema generated automatically from the same content — not bolted on separately.
Authority signals that support extraction
Byline with a real author and credentials, a visible publish date and modification date, and cited sources all feed the same trust signals that influence whether a model treats your content as citable. None of this is new SEO advice — it's the same E-E-A-T fundamentals, applied with AI citation as an additional reason to bother.
What this looks like put together
Take one page on your site that already ranks reasonably and run this checklist against it: question-based H2s, an answered opening for each section, lists where the content is genuinely list-shaped, matching FAQ schema, visible dates, and an 8th-grade reading level. Most pages fail at least two of the five. Fixing the structure — without touching the underlying facts or expertise — is usually the fastest AEO win available, and it's exactly the audit we run for clients before recommending anything else. See our zero-click data case for GEO for how this fits into a broader 2026 strategy.