Why AI Misclassifies Law Firms
Too busy to read the full article? Here are the key takeaways at a glance.
TLDR: Key Takeaways: Pillar 1 Information
- Search behaviour has shifted. People are now asking AI tools for recommendations instead of Googling.
- AI often describes businesses incorrectly, with complete confidence. This is not an SEO issue. It is an interpretation issue.
- AI forms a belief about what your business is, who you serve and what you offer. Most businesses are misclassified. Misclassification happens because of vague website language, unclear category signals and outdated or inconsistent information across the web.
- When AI misunderstands you, it quietly excludes you from relevant recommendations before prospects ever reach your site. Traditional SEO cannot fix this because it improves rankings, not AI understanding.
- The first meaningful fix is to clearly state your category at the top of your homepage and core pages. Once the category is anchored, AI can correct its understanding and align your services, audiences and topics.
- Until AI interprets your business correctly, nothing downstream will behave properly: leads, visibility, positioning and conversions will all feel “off”.
- The key question today is no longer whether you rank on Google, but whether AI understands you well enough to recommend you.
The Shift in Search Behaviour
Have you noticed how the language around search has changed?
Clients are no longer saying, “I Googled it and found…”.
They are now saying things like, “I asked ChatGPT what the best option was,” or, “Perplexity suggested I look at…”
The data reflects the same shift. Google traffic remains flat or is drifting down, while visibility inside AI answers is becoming the deciding factor in whether a brand appears at all.
Early AI visibility checks showed something even more telling. AI models were describing businesses with complete confidence, but the descriptions were rarely accurate.
The centre of search has already moved.
The Problem Most Businesses Do Not See
Consider a simple example. When reviewing how several AI models described a mid-sized law firm that specialised in family law, child arrangements and financial settlements, the results were completely incorrect.
ChatGPT described the firm as a commercial practice offering corporate advisory and employment law.
Claude suggested they mainly handled conveyancing.
Perplexity placed them in the wrong city entirely.
Not one model referenced family law.
When asked, “Who are they best suited for?” the AI confidently replied:
“Small and medium-sized businesses needing commercial legal support.”
The wrong clients. The wrong specialism. The wrong category.
These kinds of errors usually come from the same issues:
- vague or broad website language
- unclear service page headings
- incomplete Google profiles
- outdated directory information
- missing category labels
- no single source of truth for AI to reference
AI fills the gaps with assumptions and builds its own version of a business. That version is often unrecognisable to the organisation itself.
This is the real issue. It is not visibility. It is interpretation.
AI cannot recommend a business confidently if it has built the wrong understanding of what that business is.
Why Traditional SEO Does Not Fix This
A common response is to treat these issues as SEO problems.
- Improve on-page content.
- Tidy up metadata.
- Update schemas
- Strengthen internal links.
- Refresh the sitemap.
Google reacts as expected. Rankings increase. Impressions rise. Crawl signals look healthy.
But the AI models do not shift.
- ChatGPT continues describing the business incorrectly.
- Claude keeps surfacing the wrong competitors
- Perplexity still relies on outdated external descriptions.
- Gemini still struggles to make clear recommendations.
This is the key point. AI is not judging the webpage. AI is interpreting the business behind it.
SEO can improve visibility in Google.
It cannot correct the mental model an AI system has already built.
There are websites that are technically excellent but still misunderstood by AI because the interpretation layer has not been addressed and no amount of traditional optimisation can resolve an incorrect belief.
What Actually Works
When AI has formed the wrong understanding of a business, the first meaningful correction is always the same. The category must be anchored clearly and explicitly.
If AI mislabels the category, every other assumption will be affected.Many websites open with broad statements such as:
“We help people navigate complex challenges,” or, “We provide tailored solutions for our clients.”
None of this tells AI what the organisation actually is.
So the model gathers whatever fragments it can find. Old directory entries. Incomplete bios. Contradictory service pages. Similar business names.
The first fix is straightforward but extremely effective. Add a clear, factual, category-defining statement at the top of the homepage and core service pages.
For example:
“Smith and Co is a family law firm specialising in divorce, child arrangements and financial settlements.”
No metaphors. No abstract positioning. Just a clean, factual classification.
AI cannot form a correct belief until it understands the type of business it is analysing. Once the category is defined, everything else begins to align:
- entities start correcting themselves
- service pages fall into the right conceptual groups
- trust signals become more coherent
- topic associations strengthen
- invented or inaccurate services disappear
- recommendations improve quickly.
The Invisible Cost of Misclassification
Businesses often lose opportunities long before they realise AI has misunderstood them.
Most leaders assume the problem happens at the point of a poor landing page or weak rankings. In reality, the loss usually happens before the prospect even reaches the site.
AI has already shaped their understanding of who the business is, what it offers and whether it is relevant.
By the time an organisation notices something is not working, the misinterpretation has often been in place for months or even years.
Across early assessments, many law firms are already misclassified.
Not slightly but completely:
- wrong category
- wrong specialism
- wrong audience
- wrong location
- key services missing
- invented services included
- priorities reversed
This is not a small mismatch. It is structural.
And the true cost is not reduced traffic. It is the absence of traffic that should have existed. It is pre-traffic rejection.
AI search has introduced a new step in the buyer journey.
Recommendation now comes before discovery.
If AI does not recommend a business, the prospect never reaches the point where the website, funnel or offer even matters.
It is the equivalent of being removed from a shelf before the customer enters the shop.
What This Means for Your Law Firm
If AI has built the wrong understanding of a business, it will be excluded from opportunities it never knew existed.
You cannot optimise your way out of a misunderstanding. You must correct the belief.
Once people understand that AI is not ranking content but forming a mental model of their organisation, everything becomes clearer.
It explains why traffic may look stable while enquiries feel wrong.
- Why high-quality leads slow down.
- Why unfamiliar competitors suddenly appear.
- Why positioning does not resonate.
- Why marketing feels disconnected from demand.
The issue does not start at the funnel. It starts before the funnel.
Until the interpretation is corrected, nothing downstream will behave as it should.
Google still works. People simply do not use it in the same way. The question now is not, “Does our website rank?”
It is, “Does AI understand us clearly enough to recommend us?”
That is the new standard for visibility. That is the work. That is the work we do.
Learn more about our GEO Engineering: The Five Pillar System to discover how your Law Firm can win in the AI search era.
