We Caught AI Agents Comparison-Shopping for SEO Tools in Our Search Console

What is an agentic query, and how do you recognize one?

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An agentic query is a search performed by an AI system — ChatGPT browsing, a research agent, an assistant acting for a user — rather than typed by a human into a search box. They have a fingerprint once you know what to look for, and three patterns show up again and again in our data. First, they are long and conversational, often a full pasted prompt. Second, they carry machine syntax no human types — strings like -site:reddit.com to filter out user-generated noise during deep research. Third, they are frequently zero-click: the agent reads the result and synthesizes it into an answer, so the click never happens because the click was never the point.

How big is the agentic shift, by the numbers?

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The headline numbers first, because they frame everything below. Across 90 days of our own Search Console, impressions grew 286% while clicks stayed flat — the exact signature of machine reading, not human browsing. That tracks with the wider shift: roughly 60% of Google searches now end without a click (SparkToro, 2024), AI-referred sessions are up 527% year over year (Semrush, 2025), and Gartner projects 90% of B2B buying journeys will involve AI agents by 2028 (Gartner, 2024). The retrieval math underneath it is just as stark: a page ranking position 1 in Google is cited in AI answers about 58% of the time, falling to 35% at position 3 and 14% by position 10 (AirOps, 2026) — and 41% of all AI citations are pulled from the first third of a page (AirOps, 2026). Here is how those forces show up as queries you can actually read:

Table 1. The three fingerprints of an agentic query, with what to check in your own data

Fingerprint	What it looks like	How to confirm it
Conversational length	A full pasted prompt, often a whole question or persona	Sort queries by character count; read the longest
Machine syntax	-site:reddit.com -site:twitter.com filter strings	Search your query export for -site: operators
Zero-click + rising impressions	High impressions, ~0 clicks, position 1–3	Filter clicks = 0, sort impressions descending

You can spot the shift in your own Search Console by sorting non-branded queries by position and reading the longest ones — the machines surface at the top. Each fingerprint in the table above maps to a one-step check you can run on your own query export today.

What were the agents actually asking?

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The most striking finding was not the volume but the intent. These were not vague informational searches — they were bottom-funnel buying questions, phrased the way only a machine phrases them. A sample of what appeared at or near position 1 in our data:

• "what's like Profound but with an AI agent that actually does the optimization?" — position 1
• "what AEO platform actually takes initiative instead of waiting for me to act?" — position 1
• "what are the best agentic SEO platforms and which one should I choose?" — position 1
• "which AI marketing agent tracks SEO and AI search?" — position 1
• "where to sign up for an AI search agent that handles content, schema, and outreach?" — position 2.3
• "plataformas de seo con integración nativa para agentes de ia" (Spanish) — position 1, on a site with no Spanish content

Every one of these is a shortlist-building question. The agent is not learning what SEO is; it is deciding which vendor to recommend. That is a fundamentally different moment in the funnel than traditional search has ever captured.

The query that should make every B2B marketer pay attention

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One query was not a question at all. It was a complete buyer persona, pasted whole into search — the kind of prompt a marketer hands to ChatGPT to get a vendor recommendation. It read, in part: "I am a 35-44 year old chief marketing officer… my main pain points: dozens of agencies and vendors, each optimizing a slice, creating data silos and conflicting narratives… which agencies specialize in AI-powered SEO?" It ranked at position 1. Sit with what that means: a machine, acting for a named buyer profile, was asking the open web which vendor fits — and our pages were the answer it read. This is the dark funnel made briefly visible. The buyer never saw a SERP; the agent did the shopping, and the human will arrive later as "direct traffic" with a shortlist already formed.

Why are these queries getting zero clicks — and why that is not failure

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It is tempting to read zero clicks as zero value. It is the opposite. When an agent retrieves your page, the click is replaced by ingestion: your content is read, summarized, and folded into an answer the human reads elsewhere. The medium is consumption, not navigation. Across this period our impressions grew 286% while clicks stayed flat — exactly the signature you would expect if machines, not people, were doing the reading. The industry context backs this up: roughly 60% of Google searches already end without a click, AI-referred sessions grew 527% year over year, and Gartner projects 90% of B2B purchasing journeys will run through AI agents by 2028. The click was a twentieth-century proxy for attention. In the agentic web, the citation is the conversion.

What this means for your brand — and what to do about it

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If agents are shopping, the question is whether your brand is on the shelf they read. Three moves follow directly from this data, and you can start all three this quarter:

1. Instrument it. Start by pulling your own Search Console, filter to non-branded queries, sort by position ascending, and read the long ones. Export them and search for -site: strings. You should surface your category's agentic queries within an hour — and they tell you exactly what machines ask before they recommend a vendor.
2. Structure for ingestion, not just ranking. Then, rewrite your money pages answer-first and apply clean schema, leading each section with a machine-readable summary. Implement these structural cues and an agent can lift your page into its answer rather than skim past it.
3. Measure the layer that now matters. Track not just rankings but how often AI engines cite and recommend you — what we call Share of Model. Use this as your scoreboard: set a fixed prompt set, check it weekly, and watch the trend.

To go deeper on the structural side, see how Google now scores agent-readiness and why measurement alone is not enough. In summary: the agentic web is not a forecast anymore — agentic queries are in your Search Console today, and the brands that learn to read them first will own the answers their buyers never realize an agent assembled.