Research
State of AI Visibility 2026
A benchmark view of how answer engines cite brands, which source types win, and where teams should focus their first month of AEO work.
Benchmark themes
Answer-first pages win
Pages that state the answer early and support it with structure are more citation-ready than generic long-form content.
Third-party evidence still matters
Many engines rely on reviews, benchmark pages, and category guides to validate claims before naming a brand.
Cross-market divergence is real
Localized engines often rely on a different source map than global mainstream models for the same category.
How operators should use the report
- Prioritize money pages and comparison pages before broad blog production.
- Align content, entity, and PR work instead of treating AEO as a content-only problem.
- Track by prompt clusters and source types, not just by a single visibility score.
What to do in the first 30 days
- Pick one high-intent prompt cluster where your brand should already appear.
- Review the cited pages and domains that currently shape the answer.
- Ship the smallest useful fix first, usually a comparison page, category explainer, FAQ update, or stronger third-party proof.
- Measure again with the same prompt set instead of changing the benchmark every week.
Frequently asked questions
Common questions about this workflow, use case, or research area.
What should a team do first after reading this report?
Start with one prompt cluster that directly affects demand, then compare your cited sources and page coverage against the strongest competitor before changing anything else.
Why is this benchmark more useful than a single visibility score?
Because it shows the source types, engine differences, and recurring page patterns behind the number, which is what actually tells you what to fix.
Next Step
Check your own brand against these patterns
If this page matches what you are seeing, run a free audit to review prompt coverage, competitor gaps, and the sources shaping AI answers in your category.