What actually decides who AI recommends

A link can sit at the bottom of an AI answer doing nothing at all, or it can be the exact reason one firm gets named as the pick. On a dashboard they look identical. Commercially they are nowhere close. So we read the answers and judged what each citation was doing. Then, before building anything on top of the findings, we did something most publishers of research never do: we re-audited our own study, re-deriving every number on this page from the raw answer database and trying to prove each one wrong. What follows is what survived. What didn't survive has been withdrawn, is being re-run with every judgment recorded, and will return when it can be independently checked.

The research runs across two full market audits with almost nothing in common, one a business-software category sold internationally, the other a local UK professional-services category, plus 1,656 further answers swept across 27 local service markets as a cross-check. Different worlds, one question, and anything that holds across all of it is a finding you can lean on rather than a quirk of one dataset.

Who actually gets cited

Start with the part that is simply countable, because it already breaks most reporting: which sources appear in the citation lists at all. Press dominates the citation count — cited in roughly twice as many answers as Reddit. If your visibility score is built on share of citations, press looks like the boss of the board. Whether a citation changed the answer is a separate question, and it is exactly the question our re-run is designed to answer auditably.

Where the influence ranking went

The first version of this page led with an influence ranking: how often each source visibly decided the pick. When we re-audited the study, the per-answer judgments behind that ranking had not been preserved — the counting was exact, but the verdicts themselves could no longer be independently checked, and numbers we cannot re-derive do not stay on our pages, including our own. The analysis is being re-run now with every verdict recorded and every source-classification list published alongside it. Whatever it says, we will publish it. Until then, treat any tool or agency quoting a precise “this channel decides X% of AI answers” figure with the same question we asked ourselves: can they show the judgments?

The question decides as much as the channel

Sort the data by the type of question being asked and a firm's presence in the answer is not one number, it is a spread. The chart shows how often the firm's own website appears among the cited sources, by question type, in the local professional-services market — the cleanest presence measure the data supports.

A fifty-fold swing driven purely by what the buyer typed. And underneath the thinnest bar sits the starkest verified number in the whole study: across 1,622 problem-led answers — “I have this specific situation, what do I do”, the question closest to a sale — the firm was not mentioned once. Not cited less, not ranked lower: absent, while the engine handed back generic explainers naming no provider at all. Measure your presence per question type, because a healthy average hides near-total absence from the questions worth the most.

Your own website is table stakes, not the decider

This is the one most worth checking, because it is where most budget goes. When a firm gets recommended, is its own website the reason? In the market where we labelled every answer — 817 of them: 106 where the firm was recommended, 694 where it was merely listed as one option — the firm's own site was among the cited sources about as often either way. Being recommended did not make its own site more present; statistically the two rates are the same number.

Your own site being cited does not separate the recommended from the also-ran, because it is there for both. The sharper version survived our re-check even more strongly than we first published: in 1,828 recommendation answers we could re-examine, the firm's own site was the only cited source not once. Zero. The sources that sat alongside it — the third-party layer — are where the difference between listed and recommended gets made. Owned content is the price of entry, not the thing that wins, and spending more on it whilst ignoring the third-party layer is spending on the part that was never in doubt.

The weight hides in a handful of URLs

Being named and being chosen are two different jobs, and a firm can be all over the answer and still rarely be the pick. In a 115-answer sweep of one UK advisory market, the leading firm converted 62% of its mentions into recommendations; a rival with half the mentions converted 20%. Where a single thread or a single publisher carries hundreds of citations, that is where influence concentrates. We can see the pattern in the data, but never who created any of it, so this describes a mechanism rather than accusing anyone.

“There's a difference between showing up and being recommended. AI cannot recommend what it doesn't know.”

What to do with this

• Measure whether citations change answers, not just whether they exist — and ask anyone selling you an influence number whether their judgments are recorded and checkable. Ours weren't, first time round. They are now.
• Don't buy citation share as influence. Press is cited in twice as many answers as Reddit; that tells you about presence, not persuasion.
• Measure presence per question type. A healthy average hid a firm's total absence from all 1,622 of the highest-intent problem-led questions.
• Treat your own website as table stakes. It is cited about as often whether you are recommended or merely listed, and in 1,828 re-checked recommendations it was never once the sole source. The work that changes the outcome sits off your own domain.
• Watch for concentration: single threads and single publishers carrying hundreds of citations is where the weight hides.