Last updated: March 2026
Why Law Firms Are Particularly Exposed
Legal queries have always been high-intent — someone searching for a solicitor has a problem that needs solving and is ready to engage. What has changed in 2025 and 2026 is where that search now happens. A growing proportion of legal searches are moving to AI platforms because the AI can give a more useful answer than a list of ten law firm websites. “Who is a good criminal defence solicitor in Manchester?” asked to ChatGPT produces a recommendation. Asked to Google, it produces a map pack and organic results. The AI answer is more directly useful — which is why AI-referred traffic converts at 14.2% compared to 2.8% for traditional organic.
The firm that appears in the AI answer gets that enquiry. The firm that doesn’t is invisible to a channel that is growing as a proportion of total legal research. And unlike traditional SEO, where multiple firms can rank on page one, AI answers typically recommend one firm, or at most two. The commercial stakes of getting this right are higher than for any previous search transition.
Most law firms are failing this test — not because their legal expertise is insufficient, but because their digital infrastructure does not meet the AI discovery pipeline’s requirements. Here is what is going wrong and how to fix it.
Failure 1: No LegalService Schema
AI systems use structured data to identify and categorise what a page is. A law firm’s practice area pages that have no schema markup are treated by the AI’s knowledge graph component as generic web content — they may be retrieved and extracted for information, but they are not recognised as pages describing a specific legal service provided by a specific firm.
LegalService schema explicitly declares: this page describes a legal service, this is the type of law, this is who provides it, this is the jurisdiction, this is the area served. That declaration is what allows an AI system to answer “who is a good employment solicitor in Birmingham?” with your firm’s name — because it can verify from structured data that your firm is an employment law provider in Birmingham, rather than inferring it from marketing prose.
The fix: implement LegalService schema on every practice area page, with a minimum of name, serviceType, provider (linked to your firm’s Organisation entity), areaServed (specific cities and regions, not just “UK”), and a description written for AI extraction rather than marketing. Connect each LegalService entity to your Organisation entity via the provider property and @id references.
Failure 2: No Practitioner Person Schema
AI systems evaluating whether to recommend a law firm for a specific matter type check whether the firm has identifiable, credentialed practitioners in that area. A firm page that says “our team of expert solicitors” without individual practitioner data gives the AI nothing to verify against.
Person schema for each solicitor — connected to the firm’s Organisation entity, including their SRA number (which verifies that they are a qualified solicitor), their areas of practice, and links to their professional profiles on the Law Society website and LinkedIn — provides the verification signals that AI systems need to recommend the firm with confidence.
We implemented this for Olliers Solicitors — a criminal defence firm we have worked with since 2015. Practitioner schema connecting named solicitors to the firm’s entity, with SRA numbers and area-of-practice declarations, contributed directly to their appearance in AI answers for high-value criminal defence queries including voluntary police interview and serious fraud defence.
Failure 3: Inconsistent NAP Across Legal Directories
AI systems cross-reference law firm information across multiple sources before recommending them. The Law Society Find a Solicitor directory, Chambers and Partners, The Legal 500, Google Business Profile, Bing Places, and Trustpilot are all sources the AI uses to verify a firm’s identity and credentials. When information is inconsistent across these platforms — different phone numbers, different addresses, different firm names (Ltd vs Limited, for example) — the AI’s confidence in the entity drops.
A consistency audit across all major legal directories and business platforms is typically one of the first tasks in a law firm AI visibility engagement. It is unglamorous work, but the entity confidence it builds is foundational to everything that follows.
Failure 4: Practice Area Pages Not Structured for AI Extraction
Most law firm practice area pages are structured for human readers: a narrative introduction about the firm’s expertise, some information about the relevant law, a few case outcomes, and a call to action. This structure does not work for AI extraction.
AI systems extract paragraphs that open with a clear, standalone answer to the question being asked. A drink driving page that opens “Our specialist drink driving solicitors have years of experience defending clients across England and Wales” is not extractable as an AI answer to “what is the penalty for drink driving in the UK?” A page that opens “The penalty for drink driving in the UK depends on the severity of the offence and whether it is a first offence. Limits and penalties are as follows…” is immediately extractable and citable.
Restructuring practice area pages so each H2 section opens with a standalone answer — before providing the firm’s commentary on it — is one of the highest-leverage content changes for law firm AI visibility. The AI Citation Checklist gives the six criteria for assessing each section against AI extraction requirements.
Failure 5: No Bing Indexing Coverage
Many law firms have strong Google Search Console coverage but have never set up Bing Webmaster Tools. ChatGPT Search and Microsoft Copilot both retrieve from Bing’s index. A firm’s pages that are absent from Bing simply do not exist for those platforms, regardless of their Google rankings.
For law firms, this is particularly consequential because Microsoft Copilot is integrated into Microsoft 365 — meaning that when in-house legal teams or corporate clients research external counsel from their work computers, they are increasingly using Copilot. A firm absent from Bing is invisible to that discovery pathway entirely.
Setting up Bing Webmaster Tools, auditing coverage, and submitting priority pages via IndexNow takes a few hours and typically resolves the most significant Bing indexing gaps within two to four weeks.
Where to Start
For most law firms, the priority order is: entity architecture and LegalService schema first (this is the foundation everything else depends on), Bing indexing coverage second (fast fix with immediate impact on ChatGPT and Copilot), practice area content restructuring third (the largest piece of work, highest content-level impact), and authority building across legal directories fourth (slower work that compounds over six to twelve months).
The Law Firm SEO service page explains how we approach this across all five layers for firms including Olliers Solicitors. The AI Visibility Audit provides a precise diagnosis for your specific firm — mapping which layers are failing, on which platforms, with a sequenced remediation plan.
