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Last updated: March 2026

We checked 30 UK SME websites across nine industries for AI-readable signals. Law firms were the only industry to score zero on every single measure.

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TL;DR

• 3 UK law firm websites were included in our check of 30 SMEs
• All three had: no schema markup, no Organisation schema, no Person schema, no FAQ schema, no sameAs links, no llms.txt, no FAQ content, and no detectable About, Contact or Privacy pages at standard paths
• Law firms were the only industry in our sample to score zero across every signal we measured
• This is notable because legal services depend heavily on individual expertise, trust and reputation — exactly the qualities AI systems try to assess when generating recommendations
• We are not suggesting these firms are invisible to AI, but the structured signals that help AI systems understand them are absent

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What we checked

As part of a broader check across 30 UK SME websites, we included three law firm websites:

• Law firm A — an online legal consultancy
• Law firm B — a full-service law firm
• Law firm C — an independent London law firm

For each site, we checked:

• llms.txt file presence
• robots.txt AI crawler configuration
• Schema markup (any type)
• Organisation schema
• Person schema
• FAQ schema
• sameAs social profile links
• FAQ content (question-style headings)
• About page at /about
• Contact page at /contact
• Privacy policy at /privacy or /privacy-policy
• Terms page at /terms

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The results

Signal	Law firm A	Law firm B	Law firm C
llms.txt	No	No	No
Schema (any)	No	No	No
Organisation schema	No	No	No
Person schema	No	No	No
FAQ schema	No	No	No
sameAs links	No	No	No
FAQ content	No	No	No
About page (/about)	No	No	No
Contact page (/contact)	No	No	No
Privacy (/privacy)	No	No	No
Terms (/terms)	No	No	No
Blocks AI crawlers	No	No	No

All three firms had a robots.txt file and none were blocking AI crawlers — so their content is technically accessible to AI systems. But none of the structured signals that help AI systems interpret that content were present.

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Context: how law firms compared to other industries

Signal	Legal (3)	Accountancy (9)	Marketing (4)	All industries (25)
Any schema	0%	100%	100%	96%
Organisation schema	0%	78%	75%	56%
Person schema	0%	0%	0%	4%
FAQ schema	0%	11%	50%	12%
sameAs links	0%	67%	50%	52%
llms.txt	0%	22%	50%	13%
FAQ content	0%	56%	75%	64%
About page	0%	33%	50%	52%
Contact page	0%	44%	50%	56%
Privacy policy	0%	89%	100%	84%

Law firms did not just score low. They scored zero on every measure. The next weakest industry — estate agents — still had 50% schema adoption and 75% privacy policy coverage. Accountancy firms, a comparable professional services sector, had 100% schema adoption and 78% Organisation schema.

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Why this is notable for legal services specifically

Law firms present an unusual case because the qualities that make a firm successful — individual solicitor expertise, reputation, specialist qualifications, regulatory standing — are exactly the kinds of signals that structured data is designed to communicate.

Consider what a comprehensive structured data implementation could tell an AI system about a law firm:

• Organisation schema: "This is a law firm called [Firm Name], based in London, founded in [year]"
• Person schema: "The managing partner is X, who specialises in employment law and is a member of the Law Society"
• sameAs: "The firm's LinkedIn page is here, its Law Society profile is here"
• FAQ schema: "The firm answers questions about legal fees, process timelines and areas of expertise"

Without any of this, an AI system encountering a query like "Can you recommend an employment law firm in London?" must rely entirely on unstructured web content, third-party mentions, and training data to assess whether one of the firms is relevant and credible. The firm's actual website provides no structured help in this process.

A note on URL paths

Our check looked for trust pages at standard paths (/about, /contact, /privacy, /terms). Law firm websites commonly use different naming conventions — /our-people, /our-firm, /get-in-touch, /legal-notices. This means these firms almost certainly have equivalent content somewhere on their sites. The signal gap is not about missing content — it is about that content not being at the standardised locations where automated systems commonly look, and the absence of structured data that would make the content machine-readable regardless of where it sits.

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The professional services comparison

Comparing law firms to accountancy firms — another professional services sector where individual qualifications and trust matter — highlights the gap:

Signal	Law firms	Accountancy firms
Organisation schema	0%	78%
sameAs links	0%	67%
FAQ content	0%	56%
About page	0%	33%
Contact page	0%	44%
Privacy policy	0%	89%
llms.txt	0%	22%

Accountancy firms are not perfect — they still have significant gaps (0% Person schema, 11% FAQ schema). But they are measurably ahead of law firms across every signal. The likely explanation is platform choice: many accountancy firms use WordPress with SEO plugins that generate structured data by default. Law firm websites are more likely to be custom-built or use specialist legal website platforms that may not include these features automatically.

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What this does not mean

We want to be clear about the limits of this data:

• It does not mean these firms are invisible to AI. AI systems can and do recommend law firms based on unstructured content, training data, and third-party sources. The absence of structured signals does not guarantee absence from AI responses.
• It does not mean structured data would solve everything. A law firm with Organisation schema but poor content, no reputation, and no third-party presence would not suddenly dominate AI recommendations.
• This is three firms, not the entire legal sector. Our sample is small and was selected from search results, not a systematic survey of UK law firms. Larger firms with bigger digital marketing budgets may have stronger implementations.
• Law firms may have good reasons for their current approach. Legal websites operate under regulatory constraints (SRA rules on marketing claims, for example) and may prioritise different aspects of their online presence.

What the data does show is that the structured signals we checked — the ones designed to help machines understand business entities — were entirely absent from the law firm websites in our sample. Whether that matters today, or will matter increasingly as AI-driven discovery grows, is a question each firm will need to assess for itself.

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Methodology

• Sample: 3 UK law firm websites as part of a broader check of 30 UK SME websites across nine industries
• Date: 12 March 2026
• Checks performed: llms.txt presence, robots.txt AI crawler rules, schema markup (any, Organisation, Person, FAQ, sameAs), FAQ content via question-style headings, trust pages at standard URL paths (/about, /contact, /privacy, /privacy-policy, /terms)
• Limitations: Three firms is a very small sample and results should not be generalised to all UK law firms. Trust page detection only checked standard URL paths — equivalent content at non-standard paths would not be detected. Schema detection was based on homepage HTML source only. This is observational research, not a representative survey.

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FAQ

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Does this mean AI won't recommend these law firms?

No. AI systems draw from multiple sources including training data, third-party mentions, directory listings and unstructured web content. The absence of structured signals does not mean a firm will be excluded from AI responses. However, it does mean that AI systems have fewer explicit signals to work with when assessing and describing the firm.

Why do law firms score so much lower than accountancy firms?

The most likely explanation is platform choice and technical configuration rather than a deliberate decision. Many accountancy firms use WordPress with SEO plugins that generate schema markup by default. Law firm websites are more likely to use custom platforms or specialist legal website providers that may not include these features. The result is the same — absent structured signals — but the cause is probably technical rather than strategic.

Should law firms add structured data to their websites?

That is a decision for each firm. What our data shows is that the structured signals designed to help machines understand business entities are currently absent. Whether adding them would improve AI-driven discovery is not certain, but it would ensure that machine-readable entity information is available should AI platforms choose to use it.

What structured data is most relevant for law firms?

Organisation schema (firm name, practice areas, location, founding date), Person schema for partners and key solicitors (name, qualifications, specialisms, Law Society profile), sameAs links to LinkedIn, Law Society directory entries and Chambers profiles, and FAQ schema for pages addressing common client questions about fees, process and areas of expertise.

Are larger law firms better at this?

Our sample included only three firms and was not designed to compare firm sizes. Larger firms with dedicated digital marketing teams may have stronger structured data implementations, but we did not test this. A broader study across firm sizes would be needed to assess whether scale correlates with structured data adoption in the legal sector.

Is this a problem specific to law firms?

Law firms were the weakest in our sample, but other industries also had significant gaps. Dentists had 0% Organisation schema. Estate agents had 25%. The gap is most pronounced in industries that have not historically prioritised structured data or where website platforms do not generate it by default.

What should a law firm do first?

Based on our findings across all 30 sites, the most impactful first steps would be: (1) adding Organisation schema with firm name, location, practice areas and social profile links; (2) adding Person schema for senior partners connecting their names, qualifications and roles to the firm entity; and (3) ensuring About, Contact and Privacy pages exist at standard URL paths. These represent foundational entity signals that are currently entirely absent.

Could regulatory constraints explain the low scores?

Possibly in part. The SRA regulates how law firms market themselves, which may make some firms cautious about structured data claims. However, Organisation schema (business name, location, practice areas) and Person schema (solicitor name, qualifications, role) are factual statements rather than marketing claims, and would not typically raise regulatory concerns.

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This research was conducted by Rank4AI as part of our ongoing work understanding how UK businesses appear in AI-powered search platforms. We publish original data alongside curated industry statistics to help UK businesses make informed decisions about AI search visibility. Our findings are observational and should not be taken as guarantees of specific outcomes.

For more on AI visibility for professional services, see our guides on AI search for professional services, identity clarity, and the Five Signal framework.

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