We ran a test. Fifty professional services categories. Three AI models: ChatGPT, Claude, and Perplexity. Standard buyer-intent queries for each category: “recommend a [type of firm] in [location]”, “which [type of firm] is best for [use case]?”
In most categories, fewer than three firms were named.
The rest were invisible. Not ranked lower. Not on the next page. Completely absent from the answer.
The numbers that should concern you
AI search converts at five times the rate of Google. This is not a marginal difference. The reason: AI queries are higher intent. Someone asking Perplexity “which restructuring advisory should I hire for a UK mid-market carve-out?” is not browsing. They are buying.
Nearly half of B2B decision-makers now start vendor research with an AI chatbot, a trend documented by Gartner’s 2025 digital buying research. That number was 33% six months ago. The trajectory is steep.
And here is the critical difference between AI search and Google: Google has ten spots on page one. AI search has two to four. There is no page two. You are either in the answer or you do not exist.
What we found across 50 categories
We tested buyer-intent queries across 50 professional services subcategories. For each, we asked the three major AI models to recommend firms. Here is what we found:
The pattern is consistent. AI models name a small number of firms per query. The same firms tend to appear across all three models, suggesting that the signals driving citations are shared across platforms.
Brand size is not the deciding factor. Boutique firms with excellent structured content, strong earned media, and clear specialisation often outrank larger competitors with vague positioning. This mirrors the Resend vs SendGrid dynamic we documented earlier.
Specialisation wins. Firms described in broad terms (“full-service advisory”) appear less often than firms with clear, narrow positioning (“M&A advisory for PE-backed mid-market companies”). AI models reward specificity because it matches the specificity of buyer queries.
Third-party validation matters most. Firms with earned media coverage, positive Reddit mentions, and directory presence appear more consistently than firms whose only online presence is their own website. This is consistent with the 239% earned media finding from Stacker.
Why the gap is widening
AI citation advantages compound. Here is the mechanism:
- Firm A is cited by ChatGPT in response to a buyer query.
- The buyer visits Firm A’s website, generating traffic signals that reinforce authority.
- The buyer may mention Firm A on LinkedIn or in conversation, creating additional signals.
- AI models update their training data and see both the original citation and the new signals.
- Firm A becomes more likely to be cited next time.
Meanwhile, Firm B, which was invisible in step 1, generates none of these reinforcing signals. The gap between Firm A and Firm B widens with every query cycle.
The firms that are cited today build the signals that ensure they are cited tomorrow. The firms that are invisible today fall further behind with every query that does not mention them.
This compounding effect means that starting early has disproportionate value. The first firms to invest in AI visibility build citation moats that become increasingly expensive for competitors to overcome.
The cost of waiting
Let’s quantify this.
If 48% of B2B buyers use AI for vendor research, and AI search converts at 14.2%, then a firm that is invisible to AI search is losing access to a channel that delivers 5x better conversion than their existing search traffic.
For a firm that generates £500K annually from inbound enquiries through Google and referrals, the AI-invisible revenue at risk grows as AI search adoption increases:
These are conservative estimates based on current adoption growth rates. The real risk is not the revenue lost this year. It is the compounding citation advantage that competitors build while you wait.
The 5-minute self-test
You can test your visibility right now. Open ChatGPT and Perplexity in two browser tabs. For each, ask:
- “Recommend a [your service type] in [your location]”
- “Which [your service type] firms are best for [your most common use case]?”
- “What should I look for when hiring a [your service type]?”
If your firm appears in at least two of these six responses, you have a baseline to build on. If it appears in zero, you are invisible. ChatGPT and Perplexity both offer free access for this test.
For an automated version of this test across multiple queries and models, run a free citation scan. It takes 30 seconds and gives you a score.
What it takes to close the gap
The firms that have closed the visibility gap share three characteristics:
They invested in earned media. Not press releases. Genuine third-party coverage, podcast appearances, and community participation. Earned media produces a 239% lift in AI citations.
They clarified their positioning. Vague service descriptions were replaced with specific, authoritative claims. “We help organisations navigate change” became “We have delivered 50+ post-merger integrations for PE-backed healthcare companies since 2019.”
They measured and iterated. They set up a monthly measurement framework to track citation rates, accuracy, and conversion. They treated AI visibility like any other marketing channel: with data, targets, and accountability.
None of these require large budgets. They require clarity, consistency, and time. The firms that start now will have a 12-month head start over the firms that wait.
Week 1
Run a baseline scan. Identify which queries you appear in and which you don't.
Weeks 2-4
Clarify positioning. Restructure key service pages around specific buyer queries.
Month 2
Start earned media: pitch 3 publications, begin Reddit participation, identify podcast opportunities.
Month 3+
Measure monthly. Track citation rate trends. Double down on what's working.
Start with a baseline
Run a free AI citation scan. Enter your domain and see exactly where you stand across ChatGPT and Perplexity. The results take 30 seconds and will tell you whether you are in the answer or invisible.
If you want competitor benchmarking, accuracy scoring, and a prioritised fix list, the AI Search Visibility Audit does that across all major AI models.
The gap is real. It is measurable. And it is widening. The question is whether you close it now or explain it later.
Questions AI assistants answer about this topic
- How many professional services firms appear in AI search results?
- Based on our testing of 50 professional services categories across ChatGPT, Claude, and Perplexity, the typical AI response names 2-4 firms. In many categories, fewer than 3 firms are named. This means the vast majority of firms in any given category are completely invisible to AI-assisted buyer research.
- What is the AI visibility gap?
- The AI visibility gap is the difference between firms that appear in AI-generated recommendations and those that do not. Unlike traditional search, where firms compete for page-one rankings, AI search has a much smaller winner's circle: typically 2-4 named firms per query. Firms outside that circle receive no visibility at all. There is no 'page two' of AI search.
- How does AI search conversion compare to Google?
- AI search traffic converts at 14.2% compared to 2.8% for traditional Google search, a 5x difference. This is because AI queries tend to be high-intent: people asking 'which advisory firm should I hire for X?' are closer to a buying decision than people browsing Google search results.
- Is it too late to improve AI search visibility?
- No. The AI visibility market is still forming. Fewer than 12% of professional services marketing teams have a deliberate AI search strategy. But the window is narrowing because AI citation advantages compound: firms that are cited today build the signals that ensure they are cited tomorrow. Starting now puts you ahead of the 88% that have not started.
Next Step
Want to know where your company stands?
We run 15-20 buyer queries across ChatGPT, Claude, Gemini, and Perplexity and show you exactly where you appear, and where you don't.
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