Free tool, not actively developed; no accounts. AEO Platform no longer sells subscriptions.

Use case

From SEO to AEO

Bridge the gap between traditional search optimization and AI engine optimization.

Quick answer
SEO teams have spent years building search visibility through keyword optimisation, link building, and technical SEO. But AI engines process and select content differently, meaning high Google rankings do not guarantee AI visibility. Without a structured migration path, SEO teams can spend effort on the wrong priorities and miss the AI visibility opportunity.
Expected outcomes

What you can achieve

Technical
readiness confirmed before content work
Gap list
of keywords that rank but are absent in AI answers
Reusable
SEO assets adapted rather than rebuilt
One workflow
with AEO checks inside SEO processes
How it works

How to approach from seo to aeo

1

Audit your SEO-to-AEO readiness

List your existing SEO assets and decide which translate to AI visibility, which need adaptation, and what gaps exist.

2

Fix technical foundations

Ensure AI crawlers can access your content: review robots.txt, publish llms.txt, and verify structured data covers AI extraction needs. The free AI-readiness check covers these technical signals.

3

Map SEO vs AI visibility gaps

Turn your top keywords into buyer questions, run them in AI engines, and identify high-ranking pages that do not appear. These are the highest-return migration opportunities.

4

Adapt content for AI consumption

Apply answer-first formatting, strengthen expertise signals, and improve content extractability on priority pages.

5

Integrate AEO into SEO workflows

Add AI visibility checks to content briefs, technical audits, and performance reporting. Build AEO into your existing processes.

6

Measure dual-channel performance

Review search rankings and AI visibility checks side by side. Make sure optimisation for one channel does not come at the expense of the other.

The solution

How to approach it

A phased migration keeps the work manageable. Phase one is technical foundations: confirm that AI crawlers can reach your content, publish llms.txt where it fits, and check that structured data covers what AI engines extract. The free AEO Platform AI-readiness check covers this step. It looks at robots.txt and AI crawler access, sitemap, llms.txt, schema and structured data, and FAQ and comparison pages. It does not read live AI answers.

Phase two is the gap review. Take your top keywords from Google Search Console and turn each into the question a buyer would ask an AI engine. Run those prompts by hand in the major engines and mark the keywords where you rank well on Google but do not appear in AI answers. These are your best migration opportunities, because the authority already exists.

Phase three is content adaptation: answer-first formatting, clearer expertise signals, and better extractability on the priority pages. Phase four is integration into your normal workflow: add an AI engine check to content briefs, add AI crawler access to technical audits, and keep a monthly prompt review next to your keyword reports.

Throughout, measure both channels side by side so that a change for one does not hurt the other.

Example queries

Queries to monitor

“What is the difference between SEO and AEO?”
“How do I optimise for AI search engines?”
“Does AEO replace SEO?”
“How to prepare for AI-powered search”
“SEO strategies that work for AI engines”
FAQ

From SEO to AEO FAQ

Relevant engines
Free AI-readiness check

Can AI crawlers read and cite your site?

Run the free check to see technical signals: AI crawler access, sitemap, llms.txt, schema markup, and FAQ and comparison pages. It does not read live AI answers. No account needed.