The Structured Data Gap That Keeps Accountants and Solicitors Out of AI Search
Most accountant and solicitor websites read fine to a person but say nothing to ChatGPT or Google's AI Overview. Here is the exact code layer that turns your firm into a fact a model can quote.
A prospective client asks ChatGPT to recommend a solicitor for a house purchase in Manchester and the assistant names three firms with specific practice areas and named partners. A fourth firm handles the exact same work but never gets mentioned, not because the work is worse, but because nothing on its website tells a model what the firm actually does or who does it.
Your Website Reads Fine To A Person And Says Nothing To A Model
Most accountant and solicitor websites are written for a person scanning the page with their eyes. The prose reads naturally: experienced team, trusted advice, tailored service. None of that is written in a form a language model can lift out and repeat as fact. The words exist. The structure that tells a model what those words mean usually does not.
1. What Structured Data Actually Does For AI Search
Structured data is a layer added to the page code that labels facts explicitly: this is the firm name, this is the practice area, this is the person's job title, this is their qualification. A model reading a page with that layer does not have to guess what a sentence means. It reads the label and treats the value as fact. A page without it forces the model to infer meaning from ordinary sentences, and inference is where firms get skipped.
- A business type label that states the firm is a legal or accounting practice, not just a generic company
- A named person entry for each solicitor or accountant, including their job title and the body they are qualified with
- A question and answer block for the exact questions clients actually ask, matched word for word to how people search
- A service area list naming the specific towns and regions the firm covers, not just head office
2. The Three Labels That Matter Most For A Firm
Not every label is worth the effort. Three make the biggest difference for a professional services firm. The business type label tells a model this is a legal or accounting practice and where it operates. The person label tied to each named solicitor or accountant states their qualification body and registration detail, the same kind of proof that makes a credential line work in prose. The question and answer label matches a client's exact phrasing to an exact answer, which is precisely the format AI Overviews and ChatGPT pull from most often.
| What most firm sites publish | What AI search can actually quote |
|---|---|
| Experienced team of solicitors dedicated to client care | Nothing specific enough to attach to a person or a fact |
| A labeled entry naming Jane Whitfield, Solicitor, regulated by the Solicitors Regulation Authority, number 123456 | A precise claim it can quote with a name attached |
3. Where It Belongs So A Model Actually Finds It
Structured data placed only on the homepage misses every practice area page a model might land on instead. Add the firm level labels site wide, then add a person label on every page where that solicitor or accountant is named, and a question and answer label on every page built around a specific service. A model reads each page as its own source. It does not follow links to piece together a fact from three different places.
A label in the page code is not decoration for search engines. It is the only way to hand a model a fact it would otherwise have to guess at.
The Takeaway
AI search rewards firms that make their facts explicit rather than firms that simply write well. Three labels, the business type, the named person with their qualification, and a question and answer block matched to real client language, do more for how ChatGPT and Google's AI Overview describe a solicitor or accountant than another page of polished prose ever will.