10 AI Search Queries Every PR Agency Should Be Tracking for Clients

Ask a PR agency how they measure success and most will talk about coverage volume, reach, domain authority, and share of voice in traditional media. Ask them how their clients perform in AI search and most will go quiet.

That gap is a problem. In 2026, a significant and growing proportion of brand discovery happens through AI platforms. When a potential buyer, journalist, or investor asks ChatGPT, Perplexity, Gemini, or Google AI Overviews a question about your client's category, the answer they get shapes how they think about the market, and who they consider credible within it.

If you are not tracking what those answers look like, you are missing a core dimension of your client's visibility. This post gives you a practical starting point: 10 categories of AI search query that every PR agency should be running for their clients, with guidance on what to look for in each.

Why Query Tracking Is the Foundation of AI Visibility Measurement

GEO (Generative Engine Optimisation) and AEO (Answer Engine Optimisation) are not abstract disciplines. They start with a very practical question: when someone asks an AI a question that is relevant to your client's business, what does the AI say?

The only way to answer that is to run the queries systematically and record the results. Unlike traditional search, where you can check rankings in a tool, AI responses are dynamic, personalised, and inconsistent across platforms. The same query asked on ChatGPT and Perplexity can produce very different results. The same query asked twice on the same platform can differ.

This means tracking needs to be ongoing, structured, and cross-platform. But before you can track, you need to know which queries matter. Here are the 10 categories to start with.

The 10 Query Types to Track

1. Category Definition Queries

These are the queries where someone is trying to understand what a market or category is. For example: "What is [industry category]?" or "How does [product type] work?"

These queries matter because AI models use them to establish the context and vocabulary of a category. Brands that are cited in category definition responses are being positioned as foundational to the space. Track whether your client is mentioned, how they are described, and whether competitors appear more prominently.

2. Best-In-Class Queries

"What are the best [product or service category] companies?" or "Which [industry] agencies should I consider?"

These are high-intent queries from buyers who are close to making a decision. Appearing in these responses is the AI equivalent of a top Google ranking for a commercial keyword. Track frequency of mention, positioning (are they first, last, or buried in the middle?), and how the AI frames their strengths.

3. Comparison Queries

"[Client] vs [Competitor]: what is the difference?" or "How does [client] compare to [competitor]?"

Comparison queries are particularly revealing because they show how AI models characterise your client relative to their competitive set. Is your client described as the premium option, the challenger, the specialist? Is the framing accurate and favourable? These responses are often read by buyers who are already evaluating options and need a deciding nudge.

4. Problem-Solution Queries

"How do I solve [problem that the client's product or service addresses]?" or "What is the best way to [achieve outcome the client delivers]?"

This category tracks whether your client is being recommended as a solution to the problems they exist to solve. It is a direct measure of AI visibility in the moment of highest buyer intent. If a competitor is consistently named here and your client is not, that is a gap with a commercial price tag.

5. Thought Leadership and Expert Queries

"Who are the leading experts in [client's field]?" or "What do experts say about [topic the client has a point of view on]?"

These queries assess whether your client's spokespeople, executives, or published content are being recognised as authoritative sources. Earned media and original research are the primary drivers of this type of citation, which makes it directly connected to PR activity. Track changes over time and correlate with coverage placements.

6. News and Recent Developments Queries

"What is happening in [client's industry] right now?" or "What are the latest developments in [category]?"

AI platforms increasingly draw on recent news and coverage to answer these queries. This is one of the clearest connections between traditional PR results and AI visibility: a strong run of coverage in relevant publications increases the likelihood of appearing in response to news-based queries. Track this category regularly, as it shifts fastest.

7. Credibility and Trust Queries

"Is [client] reputable?" or "Can I trust [client] with [specific concern]?"

These queries reveal how AI models assess a brand's trustworthiness. The responses tend to draw on review platforms, third-party commentary, and editorial coverage. Negative coverage or reputational issues surface clearly in these responses. Tracking them regularly gives you early warning of perception problems and a baseline against which to measure reputation management work.

8. Pricing and Value Queries

"How much does [client's product or service] cost?" or "Is [client] worth the investment?"

If your client operates in a competitive market where price is a factor, these queries matter. AI responses to pricing questions often frame a brand's value proposition in comparative terms. Track whether your client is being positioned as good value, premium, or expensive, and whether that framing aligns with how the client wants to be perceived.

9. Geographic and Local Queries

"Who are the leading [category] companies in [city or region]?" or "Which [service type] agencies are based in [location]?"

For clients with a geographic focus, local AI visibility is a distinct tracking category. AI models often produce different responses to location-specific queries than to general ones, and the citations tend to draw on local press, regional directories, and location-specific content. Track across the geographies that matter to your client's business development.

10. Frequently Asked Questions in the Client's Category

These are the specific questions that potential buyers in your client's category commonly ask. For a cybersecurity firm, that might be: "How do I protect my business from ransomware?" For a fintech company: "What is the fastest way to send money internationally?"

Identifying and tracking these queries gives you a direct read on whether your client's content strategy is working. If the AI cites a competitor's blog post in response to a question your client should own, that is a content gap with a clear remedy.

How to Turn Query Tracking Into a Client Deliverable

Running these queries manually across multiple platforms is possible but time-consuming and inconsistent. The output varies by session, by platform, and over time, which makes it hard to spot trends or build a reliable baseline.

The most effective approach is to use a visibility dashboard that automates query tracking across platforms, records results consistently, and presents them alongside your other PR metrics. This turns AI visibility from a one-off audit into an ongoing reporting dimension, which is both more useful for clients and more scalable for your agency.

Presented well, a monthly AI visibility report covering these 10 query categories gives clients something genuinely new: a view of how their brand is being represented in the conversations that shape buyer perception, independent of whether anyone clicks through to their website.

That is a compelling deliverable, and one that is increasingly difficult for clients to get anywhere else.

FAQ: Tracking AI Search Queries for PR Clients

How often should PR agencies run AI visibility queries for clients?

At a minimum, monthly. Some query categories, particularly news and recent developments queries, shift quickly enough to warrant weekly tracking. The key is consistency: running the same queries at regular intervals is what allows you to identify trends and correlate changes with PR activity.

Do AI search results vary between platforms?

Yes, significantly. ChatGPT, Perplexity, Gemini, and Google AI Overviews often produce different responses to the same query, drawing on different data sources and applying different ranking logic. A complete picture of AI visibility requires tracking across all major platforms, not just one.

Can PR activity directly improve how a client appears in AI search results?

Yes. Research consistently shows that earned media in authoritative publications is one of the primary drivers of AI citations. When your client is covered in credible outlets, those placements increase the likelihood that AI models will reference the brand in relevant responses. Tracking AI visibility over time allows you to demonstrate this connection directly.

What should a PR agency do if a client is not appearing in AI search results?

Start with a content and coverage audit. Identify which query categories the client should be appearing in and cross-reference with their existing coverage and content. Gaps in AI visibility usually point to gaps in authoritative coverage on specific topics, which is exactly the kind of insight that feeds a PR and content strategy.

How do you present AI visibility data to clients who are unfamiliar with GEO and AEO?

Frame it around the questions clients already care about: are we showing up when potential buyers are looking for solutions like ours? Are we being described accurately and favourably? Are we keeping pace with competitors? The underlying methodology matters less than the business relevance of the answers.

Start Tracking Your Clients in AI Search

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