Who AI actually recommends: a citation autopsy of 20 GTM questions across three engines
Every "best AI tools" roundup tells you what a writer thinks. None of them tell you what the AI engines your buyers actually use will say, or which pages those engines trust enough to cite. So we measured it. We took 20 buying-intent questions drawn straight from the verticals in our 30-tool GTM index, ran each one through Perplexity, ChatGPT, and Google AI Overviews on June 7, 2026, and recorded two things: the tools each engine named, and the sources it cited. The result is a dated, reproducible look at what wins an AI recommendation in go-to-market software, and what that means if your job is getting a brand cited.
Where the engines agree, and where they don't
The single most useful cut for anyone optimizing across engines: do ChatGPT, Perplexity, and Google AI Overviews recommend the same tool for the same question? We compared the top recommendation per engine across the 14 category and intent queries (the six head-to-head "X vs Y" questions are shown for completeness but are consensus by construction). All three engines named the same top tool on just 5 of 14 questions; on 3 they named three different tools, and every one of those three full-divergence questions sits in the GEO and AI-search-visibility category.
The reading is direct. On settled categories the engines converge: ask any of them for the best sales prospecting tool and you get Apollo; for lead enrichment, Clay; for SEO content optimization, Surfer; for an AI SDR, 11x. Those winners are already lodged in the models' memory, and displacing them is a long game. But ask for the best GEO or AI-visibility tool and the three engines scatter: Perplexity leans on the SEO suites it sees discussed (Semrush, ZipTie), while ChatGPT and Google AI Overviews name the GEO-native players (Profound, Otterly, Peec, Goodie). The category that agencies are being hired to optimize is the one category where AI has not yet picked a winner, which is exactly where visibility is still winnable.
| Buying question | Vertical | Perplexity | ChatGPT | Google AI | Agreement |
|---|
Who gets cited, and what kind of page wins
Perplexity exposes its full source list, so we logged all 162 citations across the 20 answers and asked which domains recur. One answer leaps out: Reddit was cited in 15 of 20 queries, far more than any other source. No other domain cleared 30 percent (Zapier's blog appeared in 6 queries, YouTube in 5). The rest of the citations spread thin across more than a hundred distinct domains, most appearing only once. So citation dominance here is not one publisher owning everything; it is one community, Reddit, being treated as a near-universal second opinion on what GTM software is actually worth buying.
Group the citations by type and a second pattern appears: roughly four in five cited pages were third-party, independent roundups, review blogs, comparison aggregators like G2, and forum threads, rather than the recommended tool's own website. The engines name a tool but reach for someone other than the tool to justify the call. For a vendor, that is the whole game: polishing your own landing page is necessary but not sufficient, because the page the AI cites is usually not yours. It is the roundup you are listed in and the Reddit thread where someone vouched for you.
What the winning pages have in common
We pulled one of the most-cited pages, a Zapier comparison, and coded it directly. It carried Article and BreadcrumbList schema, a side-by-side comparison table, concrete pricing, a 2026 date, and around 2,600 words. That is the archetype: structured, priced, schema-marked, and recently updated. Across the cited set, that shape recurs; what is almost entirely absent is original first-party measurement. The cited pages overwhelmingly re-organize the same publicly available vendor facts into a clean, dated, scannable table.
That absence is the opportunity, and it is why this study exists. When an entire citation pool is consensus-aggregation, the page that runs an original count or test is structurally different from everything around it, which is precisely the kind of information gain the engines are built to reward. We are not claiming a measured citation lift here; we are pointing at a gap in what currently gets cited. A page that is structured and dated like the winners but also carries a number nobody else has is the move this data points to.
What to do with this if you optimize for AI search
Get into the consensus, not just onto your own site. Four in five citations are third-party. Earning a place in the roundups and community threads the engines already trust moves you more than another landing-page rewrite. Reddit, specifically, is doing outsized work in this dataset.
Pick your battles by category maturity. Where the three engines agree on one winner, you are displacing an incumbent the models have memorized; budget for a long campaign. Where they split, the GEO and AI-visibility category being the clearest example, the slot is genuinely open and a focused push can land.
Bring a number no one else has. The cited pages are clean aggregations of the same facts. An original data point, structured and dated like the pages that win, is the differentiator the citation pool is missing.
This study builds on the 30-tool AI GTM pricing and capability index: we indexed the tools, then asked AI which ones it actually recommends. The roundups behind both: best AI marketing tools, best GEO / AI-visibility tools, and best AI sales tools.