AEO for people who already do SEO

Answer engine optimization sounds new because the interface has changed. Instead of ten blue links, a person may get one answer, comparison or recommendation built from several sources. A website visit may not follow.¹

Most of the work behind it is familiar.

Google says its generative search features use its existing Search index and its core ranking and quality systems. They may use “query fan-out,” which means running several related searches to build one response. But a page still has to be accessible, understandable and useful enough to retrieve. Google treats AEO and GEO as SEO applied to a changing search experience.²

That gives experienced SEO teams an advantage. They do not need to start over. They need to broaden what they mean by visibility and how they measure it.

What carries over

Technical access still comes first

If you want a page to be used as a current source, the relevant system must be able to access it directly or through its search index.²

Crawlability, indexability, canonical URLs, internal links and server performance still matter. Important information should appear in accessible text. It should not be trapped inside an image, an interaction or a script that a crawler may not run. Semantic HTML helps both machines and people understand how a page is organized. Structured data should match what visitors can see.²

The crawler details are platform-specific. Google’s AI features use the same Search foundations and controls as Google Search. OpenAI tells publishers who want to appear in ChatGPT search summaries and citations not to block OAI-SearchBot; it treats GPTBot, which is associated with potential model training, as a separate control.³

This is familiar technical SEO work. The difference is that teams now have more crawlers to check and more access choices to make.

Authority still builds over time

Answer engines make it more important to show where information came from.

Original reporting, first-hand experience, named authors, primary data and precise sources give a system something useful to retrieve. A clear point of view also helps. A page that only repeats the consensus offers little unique value. A page with a clear definition, original data or a well-supported comparison is more distinctive.⁴

Links and rankings still matter, but they are no longer the whole scorecard. Visibility can also show up as repeated inclusion in answers. Teams should track which pages are cited, which questions trigger them and which competitors appear beside them.⁴

Keywords still show what people want

Keyword research is not obsolete. It still reveals how people describe a need, how often they express it and what they are trying to do.

What is weaker is the idea that teams should optimize for one exact phrase. An answer engine may turn a long request into several related searches. It can also connect a page to a need even when the wording is different. Google advises against creating a page for every query variation and says exact-match wording is unnecessary.²

Use keywords to understand the market. Build pages around a complete decision or question.

What does not carry over unchanged

One query no longer means one fixed results page

Classic SEO reporting uses a simple model: one keyword, one results page and one rank. An answer may instead draw from several searches, passages and types of sources. It may also change as the user adds more detail.²

This means “rank for the keyword” is often too narrow a brief. A better brief asks:

• What decision is the person trying to make?
• Which factual sub-questions must the system resolve?
• What evidence could our organization uniquely supply?
• Which page should be the canonical source for each claim?

The click is not the only unit of success

A citation creates visibility even when no visit follows. That does not prove the citation changed a decision, but click-only reporting will not record the exposure. Traffic remains important, but it no longer tells the whole story.¹

In a Pew Research Center analysis of browsing behavior from 900 U.S. adults in March 2025, people clicked a traditional result in 8% of visits to Google pages with an AI summary, versus 15% when no AI summary appeared. They clicked a source inside the summary in only 1% of visits. The study is a snapshot, not a universal forecast, but it demonstrates why click-only reporting can miss a large part of the new discovery journey.¹

The scorecard should now include visibility in answers, share of citations, referred visits and business results.

“AI hacks” are not a strategy

There is no magic schema type for AI answers. There is no ideal paragraph length, and teams do not need to rewrite every page as a robotic question and answer. Clear headings and direct prose help readers and can also help retrieval. Breaking content into arbitrary “chunks” does not.²

The same caution applies to manufactured mentions and mass-produced pages aimed at every possible prompt. These tactics create volume, not authority.

Three things to change this quarter

1. Audit every place an answer engine gets information

Start with the pages that explain the business, its products and its strongest claims. For each one, verify:

• the intended URL is crawlable, indexable and canonical;
• important content is available in rendered, accessible text;
• titles, headings, bylines, dates and internal links make the page’s purpose unambiguous;
• structured data agrees with the visible page;
• search, AI-search and training crawler policies reflect an intentional choice;
• product feeds, business profiles, inventory, pricing, shipping and returns agree with the website where relevant.

This is more than a content audit. It checks whether every system is working from the same facts. Conflicting prices, stale policies and duplicate definitions can make it harder for both people and machines to identify the current information.⁵

2. Make priority pages worth citing

Do not rewrite every paragraph for a model. Improve the pages that deserve to become references.

When a question has a clear answer, give it early. Put the evidence close to the claim. That evidence might be a method, date, calculation, primary source, named expert or specific example. Define important terms consistently. Separate facts from interpretation. Say what is unknown. Add a visible update date when the answer can go stale.

Most importantly, contribute something original. That might be data, operating experience, a useful framework, a calculator or a comparison based on clear criteria. Google says unique, expert-led content is likely to matter more over time than AI-specific optimization tricks.²

The goal is not to sound quotable. It is to be the source a careful answer should cite.

3. Measure visibility in answers as well as search

Create a repeatable set of real questions about the brand, category, product, competitors and customer problems. Record whether the brand appears, which page is cited, what the answer says about it, which competitors appear and whether the answer is correct. Run the same questions on a regular schedule and save the results. Generative answers change.

Use first-party platform data where it exists. Google Search Console now provides a dedicated Generative AI performance report showing impressions and which pages appeared in Google’s generative search experiences. Bing Webmaster Tools’ AI Performance reporting shows citations, cited URLs and sampled grounding queries across supported Microsoft AI surfaces. ChatGPT referral links include utm_source=chatgpt.com, making referred sessions measurable in analytics.⁶

No single metric is sufficient. Pair visibility with qualified visits, branded demand, assisted conversions, leads and revenue. A citation is evidence of inclusion, not proof of persuasion.

A note on llms.txt

llms.txt is a proposed way to publish a short, model-friendly guide to a website. It may be useful for documentation or for services that choose to read it. It is not a universal standard, and it does not control crawler access. Google says it has no effect on visibility in Google Search.⁷

Google says it ignores llms.txt for Search and that the file neither helps nor harms visibility there. If you publish one, treat it as a low-cost experiment after the underlying site, content and measurement are in order—and give it an owner. A stale “most accurate file on the domain” is worse than an honest absence.⁷

The practical shift

SEO has always connected three things: what people need, what machines can understand and what a business can honestly say. Answer engines do not remove that work. They change where its results appear.

The page is still the asset. The link is still valuable. The visit is still where many relationships and transactions begin. But visibility can now occur inside a synthesized answer, and influence can begin before the click.

The teams that adapt fastest will not be the ones that rename SEO. They will be the ones that make their best knowledge easy to find, specific, verifiable and measurable wherever an answer is built.

Sources and further reading

• Google: Optimizing your website for generative AI features on Google Search
• Google: AI features and your website
• Google: Search Generative AI performance reports in Search Console
• Bing: AI Performance in Bing Webmaster Tools
• OpenAI: Publishers and Developers FAQ
• Pew Research Center: Click behavior when Google AI summaries appear
• llms.txt: proposal and format