Studies say AI favours publishers. Not in enterprise B2B.

The published research on AI search says AI favours independent, impartial sources. Trade media is about as independent as it gets. So why are the publishers I talk to still watching their traffic fall?

The usual explanation is that nobody clicks inside AI answers. But if AI were building its answers from trade media, some of that would still show up. Something didn't add up, and having run publishers myself at Dennis and Autovia, I wanted to know why. So I measured it.

If AI really prefers independent sources, trade media should be all over the answers. So I measured what AI cites when buyers ask buying questions: six enterprise technology and services categories, in the UK, across ChatGPT, Gemini and Google's AI Overviews, in September and October 2026.

Trade media got between 3% and 9% of the sources AI cited. Fewer than one in ten, in every category.

Most of the rest belonged to the vendors. Their own pages, and those of the consultancies and partners around them, took between 52% and 80%. Next came review and analyst sites, which AI cited more often than trade media in all six categories.

That last point matters more than it looks. Review platforms read like the independent voice in an answer, but many are paid by the vendors they list. Trade media is the independent voice, and it's the one that's largely missing.

A word on terms. A citation is a source the answer shows as its evidence, usually as a link or a source card beside the text. A mention is a name in the answer itself. You could argue the mention matters more: buyers rarely click the links, but they do read the names. So I checked that too, this time counting answers rather than sources. Across 783 answers to buying questions, a trade or business title was named in the text once. Gartner was named in 27.

It also cuts against the published research I could find. A University of Toronto study, published in September 2025, found AI search leaning heavily on third-party sources over brands' own content. A long-running study from a PR software company finds journalism behind roughly a quarter of AI citations. Both used consumer questions, the "rank the best smartphones" kind. And even there, the Toronto team found brands' own content gaining ground the closer a question got to a purchase. Enterprise buying questions are about as close to a purchase as questions get, and that's where I looked.

The full data, both tables and the method are on the site: Missing from the answer.

ChatGPT shows some of its working, which helps explain why we’re seeing this. In 36 of 59 answers, its very first search already named vendors.

So where do the names come from? From what the model already knows: everything it absorbed in training, long before anyone asked the question. Nobody outside the AI companies can see inside that. What we can see is what it does next, which is check its candidates, mostly on the vendors' own pages.

That gives a publisher two places to be: in the model's memory, and in what it checks. Trade media may well help shape what the model knows, but if it does, it isn't getting the credit: when an answer names a reference, it's an analyst like Gartner, not a trade title. The check is where the answer gets its evidence, and that's where trade media is missing.

In three categories, ChatGPT cited no trade media at all, not once in 998 citations, even when it had pulled trade pages into its sources. In endpoint management, one trade title's vendor ranking was cited eight times by Google's AI Overviews. ChatGPT pulled the same page into its sources and cited it zero times.

Then I checked Google, twice, a week apart. Same questions, Google’s first page: trade media was between 0% and 10% of results both times, and vendor and company sites between 57% and 80%. Google’s own AI tools, AI Overviews and Gemini, treat trade media about the same as its search results, and in identity and endpoint management AI Overviews gave it more room than Google’s first page. ChatGPT, which isn’t built on Google, is harsher still, as those 998 citations show.

Vendors have spent the best part of 30 years building their marketing around content, while publishers built theirs around traffic. The job of comparing suppliers went to vendors and review sites long ago. AI just makes it final.

So the gap was already there before AI arrived. What is new is that there's no second page and no click left for trade media to close it.

For B2B media businesses, this goes straight to revenue. Advertising, sponsorship, lead and demand generation and newsletters are all priced on the evaluative audience: the readers comparing suppliers and deciding. A reader comparing suppliers is worth more to the vendors paying for your audience than one browsing the news.

When that comparing happens inside an AI answer that doesn't name or cite you, you lose the reader and the proof you were ever part of the decision. And when investors and buyers come to value these businesses, they'll price that exposure.

If you run a B2B media business, the lazy reading of this data is to write more rankings. Don't. Thin lists win because nothing independent is there - vendors' own best-of, comparison and alternatives pages take between 12% and 39% of the citations that go to vendor and company sites. It's a numbers game publishers can't win: every category has far more vendors than trade titles, each with a content team. And a thin list written to chase citations spends the one thing a publisher has that a vendor page doesn't: independence. A ranking is only worth citing if readers trust it wasn't bought.

The opening for independent B2B media is evidence and judgement a vendor can't credibly offer - benchmarks with a published method, original data, tested comparisons, buyer's guides the model can actually read. I won't pretend the engines already reward depth. They don't yet. But the slot is open.

This is the opportunity, and it's a big one. AI goes looking for third-party judgement: in every category I measured, it cited review and analyst sites ahead of trade media, and when it names a reference, it names an analyst. When a trade title did publish a ranking, Google's AI Overviews cited it again and again. In consumer categories, where independent testing runs deep, the research shows AI leaning heavily on it. The demand for independent, authoritative evaluation is already there. In enterprise B2B the supply isn't, and no one is better placed to provide it than independent trade media.

Being cited doesn't pay in clicks. Being named as the reference does.

If you market a vendor, read the same data the other way round: when AI checks a shortlist, it checks you mostly on your own pages, including the best-of and comparison pages you wrote yourself. Those pages are now doing the job a trade review used to do. Make sure they're accurate, current and specific enough to quote, and that every claim on them would survive a buyer checking it.

One caveat, whichever side you're on. I measured six enterprise technology and services categories, and I can't assume the pattern holds in yours. In sectors with a deep bench of independent reviews and testing, it may run the other way. In others it may be worse. What you can't afford is not knowing which way it works in your market. If you're missing, the opening is the one I've just described. If you're already the reference, the job is different: making sure you're credited, and paid, for work the answer now does in place of your pages.

When a buyer in our sector asks AI for a shortlist, how often does it name or cite us?

Most boards can't answer it, because nobody has measured it. So here's an offer. Reply with one of your titles and the category it covers, and I'll report back how often AI names or cites it on shortlist questions. First five replies. I want to know how far this holds beyond the six categories we measured, and you'll see what it means for your business.

Next issue: what this does to intent data?

John
Decoding Growth (formerly Get2Growth)