Statistics Last updated: May 2026

Speakable Schema Used by Fewer Than 10% of Websites

Speakable schema delivers 127% citation increase but is used by fewer than 10% of websites. The biggest competitive gap in AI schema.

OM
Oliver Mackman
AI Search Analyst

Speakable schema delivers a 127% increase in AI citation rates but is used by fewer than 10% of websites. This is the largest gap between impact and adoption in AI search optimisation. Speakable marks specific content sections as suitable for extraction and text-to-speech. It tells AI platforms "this is the answer you should cite."

Less than 10% of sites use Speakable schema - SEOCompare stat card

What Speakable schema does

Speakable is a schema property that marks specific page sections as suitable for audio playback and direct extraction. It was originally designed for voice assistants. It has become relevant for AI search because it identifies the most citable, extractable portions of your content.

When an AI platform encounters Speakable markup, it receives a clear signal. The content creator considers this paragraph the definitive, self-contained answer. This reduces the AI's need to evaluate which part of the page to cite. You have already done that work for it.

The 127% citation increase

Pages with Speakable schema see a 127% increase in AI citation rates compared to equivalent pages without it. The mechanism is straightforward. Speakable removes ambiguity about which content to extract. It makes it easier for AI to cite your page with confidence. Easier citation equals more citations.

The 127% figure is substantial but less dramatic than FAQPage's 350% increase. Speakable has a unique advantage though. It can be applied to any content type on any page. FAQPage only applies to question-and-answer content. This makes Speakable more broadly applicable.

Why adoption is so low

Several factors explain the sub-10% adoption rate:

  • Low awareness - most web developers and SEO professionals have never heard of Speakable
  • Voice-first perception - many assume Speakable is only for voice search and smart speakers
  • No Google rich result - unlike FAQPage, Speakable does not generate a visible rich snippet in Google, so there was no traditional SEO incentive to implement it
  • Limited tooling - popular schema generators and WordPress plugins rarely include Speakable as an option
  • AI search is new - the citation benefit has only recently been documented

How to implement Speakable

Speakable is added as a property within your Article or WebPage schema. It uses CSS selectors to point to specific content sections:

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "Your Article Title",
  "speakable": {
    "@type": "SpeakableSpecification",
    "cssSelector": [".answer-capsule", ".key-finding"]
  },
  "author": {
    "@type": "Person",
    "name": "Author Name"
  }
}
</script>

The cssSelector property points to the CSS classes applied to your most citable paragraphs. In the example above, any paragraph with the class answer-capsule or key-finding would be marked as speakable content.

Best practices

PracticeWhy it matters
Mark 1-3 sections per pageToo many speakable sections dilute the signal
Choose self-contained paragraphsThe marked content should make sense when extracted alone
Lead with the answerSpeakable paragraphs should start with the key fact or answer
Include specific dataNumbers, percentages, and concrete claims are more citable
Combine with answer-capsule stylingVisual formatting that matches your schema markup

The competitive window

Fewer than 10% of websites use Speakable. Early adopters have a clear competitive advantage. As AI search grows and more businesses discover this schema type, the advantage will narrow. The window to implement Speakable and capture the 127% citation lift while competitors are unaware is now.

Read our complete schema markup guide for AI search ยท See all AI search statistics

OM

Oliver Mackman

AI Search Analyst, SEOCompare

Oliver leads SEOCompare's editorial and comparison research. With over a decade in digital marketing, he oversees agency evaluation, tool testing, and AI search data analysis.

Last reviewed: 7 April 2026

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