A traditional rank tracker can tell a Miami personal injury firm that it holds position three for “car accident lawyer Miami.” It cannot tell that firm whether ChatGPT mentions it when a prospective client asks for the best lawyers after a rideshare crash. That is the gap an AI visibility audit example is built to expose.
AI search does not operate like a familiar list of ten blue links. ChatGPT, Google AI Overviews, Gemini, Perplexity, and Bing Copilot synthesize answers from sources they consider useful, credible, current, and relevant to the question. Your business may rank well in Google and still be absent from the answer your next customer sees first.
This practical example shows what an audit looks like, what the findings mean, and how a business should turn them into a focused AEO plan.
The business in this audit
For this example, assume we are auditing a fictional Miami personal injury law firm called Harbor Point Injury Law. The firm has a solid website, 42 Google reviews, location pages for Miami and Coral Gables, and first-page organic rankings for several broad injury terms. Lead volume is steady but inconsistent.
Its goal is not simply to appear more often. The firm wants to become a cited, recommended source when people ask AI platforms high-intent legal questions, especially questions asked before a user searches for a specific firm by name.
The audit tests 30 prompts across five intent groups: local attorney recommendations, accident-specific legal questions, fee and process questions, trust and reputation questions, and location-based queries. Prompts are tested in multiple AI platforms, documented with the date, response format, citations, competitor mentions, and accuracy notes.
That last part matters. AI answers can change by location, account settings, browsing availability, and platform updates. A single prompt is not a verdict. Patterns across a meaningful query set are what reveal the opportunity.
AI visibility audit example: the findings
The first result is straightforward: Harbor Point Injury Law is barely visible in AI-generated answers despite respectable traditional rankings.
| Metric | Audit result | | — | — | | Prompts tested | 30 | | Brand mentioned in any answer | 6 of 30 | | Brand cited or linked as a source | 2 of 30 | | Correct business details when mentioned | 4 of 6 | | Competitor firms mentioned | 11 firms | | Prompts with no useful local firm recommendation | 9 of 30 |
At first glance, six mentions may not sound disastrous. But the query-level breakdown tells the real story.
Local recommendation prompts
Prompts included questions such as “Who are reputable personal injury lawyers in Miami?” and “What law firms handle serious car accident cases near Brickell?”
Harbor Point appeared in two of eight results. Both mentions came in Bing Copilot responses that pulled from local listings and review signals. The firm did not appear in ChatGPT or Perplexity for any broad local recommendation prompt.
Three competitors appeared repeatedly. Each had stronger third-party validation: consistent legal directory profiles, recent local media mentions, practice-area pages with clear answers, and more frequent review activity. One competitor did not outrank Harbor Point organically for the broad head term, but it was the most commonly recommended firm in AI responses.
The lesson is clear: AI visibility is not a recycled organic ranking report. Authority signals across the web can determine who gets surfaced.
High-intent accident questions
The firm was tested on queries such as “What should I do after a Lyft accident in Miami?” and “Can I sue if a distracted driver caused my accident in Florida?”
Harbor Point was cited once, but only because an older blog post was used as a supporting source. The article had good legal information, yet it buried the answer under a long introduction and lacked a clear author bio, updated date, FAQ structure, or references to related Florida-specific guidance.
Meanwhile, AI platforms often cited government sources, legal publishers, and competitors with narrow, well-structured pages. This does not mean every law firm needs to outrank state agencies. It means the firm needs content built around the specific questions clients actually ask, with direct answers that are easy for both people and answer engines to interpret.
Trust, process, and fee prompts
The biggest missed opportunity appeared in questions such as “How much does a Miami injury lawyer charge?” and “How do I know if a personal injury lawyer is legitimate?”
Harbor Point did not appear in any of these six responses. Its website had a generic “No fee unless we win” statement, but no transparent explanation of contingency fees, case costs, timelines, consultation expectations, or client communication standards.
This is a content gap with commercial value. Prospects often ask trust questions before they are ready to contact a firm. If AI tools answer those questions with a competitor’s explanation, that competitor gains credibility before the searcher ever reaches a law firm website.
Brand accuracy issues
When the firm was mentioned, two responses showed outdated information. One gave a former office address, while another described the firm as handling immigration law because of an old directory listing.
This is not a minor cleanup task. Incorrect entity data creates friction for users and reduces confidence in the business. An audit should identify every visible inconsistency across the company website, Google Business Profile, major directories, social profiles, press mentions, and legal listings.
Why the firm is losing AI citations
The audit did not reveal a single technical failure. It revealed a predictable authority problem spread across content, structure, and third-party signals.
First, Harbor Point’s most useful practice-area pages were written for broad keywords, not natural-language questions. They discussed car accidents generally but did not answer narrower situations involving rideshare crashes, uninsured drivers, construction-zone collisions, or Florida comparative negligence. AI systems need clear evidence that a source directly addresses the user’s question.
Second, the site lacked strong entity signals. Attorney bios were thin, author attribution was inconsistent, and several pages did not connect attorneys to their credentials, practice focus, office location, or relevant case experience. For professional services, that missing context can make a business harder to trust and classify.
Third, competitors had more corroboration outside their own websites. They were quoted in local publications, listed consistently in authoritative directories, and referenced in recent community or legal content. AI tools frequently rely on this wider web footprint when deciding which brands deserve mention.
Finally, the firm’s structured data was incomplete. Basic local business markup existed, but attorney, legal service, FAQ, review, and article schema opportunities were either missing or improperly implemented. Structured data is not a magic citation button. It does, however, reduce ambiguity and help search systems understand what a page, person, service, and business represent.
The 90-day action plan from the audit
The right response is not to publish dozens of generic AI-written articles. It is to fix the highest-impact gaps in sequence.
Month one: correct the entity foundation
Start by resolving address, category, practice-area, and contact-data inconsistencies everywhere they appear. Update Google Business Profile details, legal directories, social profiles, and sitewide contact information. Expand attorney bios with verifiable credentials, bar admissions, practice focus, and local relevance.
At the same time, implement accurate structured data for the firm, attorneys, office locations, services, reviews where eligible, and core educational pages. This creates a cleaner foundation for search engines and AI systems to interpret the brand.
Month two: build answer-first practice content
Prioritize pages around the prompts where competitors are being cited and the firm is absent. For this example, that means a Miami rideshare accident page, a Florida distracted-driving claim guide, a contingency-fee explainer, and a page explaining what happens after an injury consultation.
Each page should lead with the answer, address local and legal nuance, identify the qualified author or reviewer, and connect to related service pages. The goal is not to force a brand mention. The goal is to publish the clearest credible source for the question.
Month three: strengthen external proof
The firm then needs credible off-site validation. That may include accurate directory profiles, local press opportunities, expert commentary, community involvement, legal associations, and earned mentions from relevant publications. Quality matters more than volume. A pile of low-value links will not create the trust signal a professional service brand needs.
Continue monitoring the original prompt set each month. Track mentions, citations, competitor frequency, answer accuracy, source types, and new query opportunities. AI visibility moves, so the strategy must move with it.
What success should look like
A realistic first-quarter goal is not to appear in every AI response. Some questions will appropriately favor government agencies, large publishers, or sources outside your category. The target is measurable progress on prompts that match your services, market, and buyer intent.
For Harbor Point, a strong early outcome would be growing from six mentions to 12 or more, correcting all known misinformation, earning citations for accident-specific education, and appearing more often in Miami recommendation responses. Those gains should be viewed alongside organic traffic, branded search growth, consultation quality, and lead volume.
An AI visibility audit gives a business something more useful than another ranking screenshot: a clear picture of who answer engines trust, where competitors are winning the conversation, and what work will change the result. If your customers are already asking AI for recommendations, the best time to measure your presence is before your competitors become the default answer.