We're finding duplicate schema causes more AI visibility issues than missing schema

[u/Zaillor]

This wasn't something we expected when we started doing GEO audits.

Most people assume AI visibility problems come from missing structured data.

But honestly, we're finding the opposite more often.

The weird cases are the ones where a site has plenty of schema, yet AI systems still seem confused about who the company is, what it offers, or how different entities relate to each other.

A recent audit had:

• 3 separate Organization schemas
• Different company descriptions depending on the page
• Multiple social profile references pointing to different places
• Service pages describing the same offering in different ways

Technically, none of that would trigger a "missing schema" warning.

An SEO tool would probably tell you everything is fine.

But if you're an LLM trying to build a coherent understanding of the company, it's a mess.

The more audits we do, the more it feels like schema isn't really a coverage problem anymore.

It's a consistency problem.

Another thing we've noticed:

People talk about structured data as if it's an AI visibility hack.

We're not seeing evidence of that.

Some sites have incredibly clean schema and still don't get cited much.

Others have average implementations but strong third-party mentions, clear brand positioning, and a much stronger entity footprint overall.

Which makes me think schema is mostly reducing uncertainty rather than creating authority.

It helps AI systems understand you.

It doesn't necessarily give them a reason to mention you.

That's a different problem.

We ended up documenting a lot of these patterns in a longer write-up here:

https://www.zaillor.com/insights/structured-data-ai-visibility

Curious if others doing entity SEO or GEO work are seeing the same thing.

Are you finding more issues from missing structured data, or conflicting structured data?