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Lawyers rank lowest on AI visibility — half have no structured data

2026-07-21 · Martin Nymann · 5 min reading

118 Danish law firm websites scanned: lowest score across three sectors, 51% without schema.org and 31% without H1 in raw HTML. Here’s what the figures show.

Of the three Danish sectors we analysed on 21 July 2026, lawyers fare the worst when it comes to AI reading their websites. 51 per cent of 118 law firm websites have no structured data, 31 per cent lack an H1 heading in raw HTML, and 16 per cent have too little readable text without JavaScript. The median score is 70, compared with 85 for the plumbing sector.

Where does the legal sector stand from a technical perspective?

Signal Lawyers (n=118) Accountants (n=147) Plumbing (n=200)
No structured data51%41%29%
Without H1 in raw HTML312214%
Without a meta description2527%17%
Less than 150 words of readable text16%7%5
Median score (0–100)707585

Why does this affect lawyers more?

We don’t have data to explain the reason — only the measurement. But the pattern points to design-heavy sites: 16 per cent with less than 150 words of readable text is three times as many as for plumbers, and this is typical when content is loaded using JavaScript. An AI crawler does not run JavaScript and therefore sees an almost empty page.

The same applies to the missing H1 headings. If the page has a visually large heading but is marked up as

rather than

, a human sees a heading — the machine does not.

What does structured data mean for a law firm?

Structured data (schema.org) is machine-readable information in the page’s code: who you are, where you’re based, what services you offer, opening hours and reviews. Without it, the AI has to deduce this from the body text — and is more likely to get things wrong, for example with departments, addresses and areas of specialism.

For a lawyer, this is particularly relevant when it comes to areas of specialism. ‘Corporate lawyer’ is a question that an AI can only answer accurately if the specialism and geographical location are specified in a machine-readable format somewhere.

This article is based on the same dataset as our main analysis of 465 Danish company websites, where you can find the full methodology and all the figures.

Methodology

Data was collected by Geoa on 21 July 2026. We retrieved the homepages of 465 Danish company websites without running JavaScript — exactly as GPTBot, ClaudeBot and PerplexityBot do — and measured six technical signals: readable text, llms.txt, robots.txt access for AI crawlers, structured data (schema.org), H1 heading and meta description. The breakdown is 200 plumbing firms, 147 accountants/bookkeepers and 118 solicitors.

Important caveat: the sample consists of search-visible businesses — those that rank in local searches — not a random cross-section of the industry. The figures therefore describe the industry’s most visible businesses. A representative sample would, in all likelihood, look worse, not better. We therefore consistently write ‘of those scanned’, not ‘of all Danish’.

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