Most companies already have the pages they need to be cited in AI answers. They just are not written in a way an engine can use. AI content optimization is the work of fixing that: reworking existing pages, passage by passage, so they answer the questions buyers ask answer engines.
This post gives the method, shows a real rewrite our own crew proposed for one of our pages, and explains how to measure whether a change worked. For how Attensira runs this end to end, see content optimization.
What does AI content optimization actually change?
Not keywords, and not page length. It changes passages: the few sentences an engine lifts into an answer. A page is optimized for AI answers when, for each question it should answer, it has a passage that:
- answers the question in its first sentence;
- names its subject instead of saying "it" or "this";
- includes the condition, number or date that makes it precise;
- makes sense with nothing around it;
- says something true that other pages do not.
Everything else on the page, such as navigation, design and long-form explanation, still matters to people. It matters much less to the engine's choice of what to quote.
What is the method?
1. Start from a question you lose
Not from a page. Pick a question buyers ask, where answers name competitors and not you, or name nobody. That gives the work a target and a way to measure it.
2. Find the page of yours that should answer it
Often you already have one: a feature page, a blog post, a docs article. If you do not, the job is a new page, not optimization.
3. Read what the winning answers lean on
Ask the question several times on the engines you care about and read the sources the answers cite. What do those pages say that yours does not? Usually it is one of three things: a direct definition, a specific number, or a section devoted to exactly that question.
4. Rewrite one passage
Add or replace one passage on your page so it answers the question better than the sources the engine uses today. One passage, not the whole page, so you can tell what changed.
5. Ship and measure
Publish the change, then re-read the same question over the following weeks and compare with the weeks before. Count answers, not impressions.
What does a real rewrite look like?
Here is one from our own workspace. On 2026-10-01 our crew proposed a passage rewrite for an old share-of-voice post on our blog. The proposal came with its evidence.
The question it targeted: "how to measure share of voice in AI answers", a question we track.
The evidence: across 42 ChatGPT answers read for that question, the answers were decided entirely by other companies' explainers, and nothing of ours was among the sources. Our post covered share of voice for organic search, social and paid, with no section about AI answers, so there was no passage an engine could lift.
The passage as it stood on the page:
Before you even think about plugging numbers into a formula, you have to get the raw materials right. Your share of voice calculation is only as good as the data you feed it.
The proposed passage:
Before you even think about plugging numbers into a formula, you have to get the raw materials right. Your share of voice calculation is only as good as the data you feed it. AI answers are a channel too, and the raw material there is the answer set itself: share of voice in AI answers is the number of sampled answers that named your brand, divided by the number of answers read, measured against the same total for every rival named in them. A brand being named in the prose and being listed in the citations are two different events, so count them separately.
Notice what it does. It keeps the original sentences, so nothing the page already said is lost. It adds a definition that answers the tracked question directly, in words an engine can lift. And it adds one distinction, named versus cited, that most explainers skip.
It also shows the limits of the method. The proposal is still waiting in our inbox, the frame at the top, because nobody on our side has acted on it yet; an unshipped rewrite changes nothing. And this rebuild has since replaced that post with a new one, how to calculate share of voice, written around the same gap.
What makes a rewrite worth citing?
Engines choose between passages. Yours has to be the better one for the question. Three things make the difference most often:
- Directness. A definition in the first sentence beats a definition in the fourth paragraph.
- Specificity. A number with its sample size, a condition with its plan, a date beside a fact.
- Originality. Something only you can say: your data, your test, your policy. Google's own guidance on helpful content asks whether a page provides "original information, reporting, research, or analysis".
The GEO paper by Aggarwal and colleagues measured rewrites like these on generative engines and reported that methods such as adding statistics, quotations and citations could raise a source's visibility by up to 40% in their tests. The specific numbers belong to their setup. The direction holds: what a passage contains decides whether it is used.
