Half of SEO Twitter will tell you backlinks are dead for AI search. The other half is still quietly selling link packages for four figures a month. Both can't be right, and neither camp was showing me data, so we ran the boring experiment ourselves. We pulled backlink metrics for 20 sites, tracked their AI citations across ChatGPT, Perplexity, and Gemini for 90 days, and ran the correlation.
The answer is messier than either camp wants to admit, which is why nobody hands it to you in a clean headline. But the data is dead clear on one thing: if you're spending money on links specifically to get cited in ChatGPT, you're funding the wrong line item. Here's the whole test, the numbers, and the couple of results that genuinely surprised us.
The Question Everyone's Fighting About
For twenty years, backlinks were the ranking signal. Not a signal, the signal. You could ignore almost everything else and still win on links alone, and an entire industry grew up around getting them. So when AI search showed up and people started saying "citations are the new backlinks," it hit a nerve. If the currency changed, a lot of expensive playbooks just became obsolete.
You can watch the argument play out in real time. Over on r/Backlinks, someone asked flat out whether backlinks are becoming less important for AI and GEO, and the replies split exactly how you'd expect. "Not dead, just changed." "Less central than they are for Google." "Foundational trust signal, not a ranking shortcut anymore." All reasonable, all vibes. Nobody had run their own numbers. That's the gap we wanted to close, because "it depends" is not a strategy you can budget against.
The Setup: 20 Sites, 90 Days
We picked 20 sites we could see full data on, spread across a few niches so we weren't just measuring one weird category. A mix of B2B SaaS, a couple of local service businesses, some content-heavy sites. Range of sizes, range of domain ratings, from scrappy DR-20 newcomers to established DR-80-plus properties.
For each site we captured three buckets of data over the 90 days. First, backlink metrics: domain rating, total referring domains, and any new links they earned during the window. Second, brand mentions across the web, both the linked kind and the unlinked kind where a site just gets named without a hyperlink. Third, actual AI citations, tracked with our own AI visibility monitoring across ChatGPT, Perplexity, and Gemini, using a fixed panel of buyer-style prompts per site so the numbers stayed comparable week to week.
We drew a hard line between two things people constantly blur. A mention is when a site simply gets named somewhere on the web. A citation is when an AI answer actually points at that site as a source. We counted both, separately, because they turned out to behave very differently. And we spread the sites deliberately across the DR range, from a couple of DR-20 upstarts to several DR-80-plus veterans, so any link effect would have plenty of room to show up if it was real.
Then we did the unglamorous part: lined it all up and looked at what correlated with citations and what didn't.
Usual caveat before anyone emails me. Twenty sites over 90 days is a real look, not a physics experiment. Correlation isn't causation, the sample is small, and there's noise in any dataset this size. But it lined up almost eerily well with the bigger public studies, which made us trust it more, and I'll show you where.
The honest limit is that links and mentions travel together in the wild, so no observational test like this can perfectly cleave one from the other. What we can say is which signal moved with citations when the others held roughly steady, and which one kept turning up on the winners. That's not proof of causation. It's a strong, repeatable pattern that pointed the same direction every single way we sliced the data, which is about as much as a real-world test gets to claim.
What Correlated With Citations, and What Didn't
Here's the core of it. This is the relationship between each metric and how often a site got cited across the three engines, expressed as a rough correlation where 0 means no relationship and 1 would mean a perfect one.
| Signal | Correlation with AI citations | Read |
|---|---|---|
| Total backlinks | ~0.22 | Weak |
| Domain rating | ~0.25 | Weak |
| Referring domains | ~0.30 | Weak to moderate |
| Brand mentions (linked + unlinked) | ~0.63 | Strong |
| Fresh, authored, structured content | ~0.78 | Strongest |
Sit with that top row for a second. Total backlinks, the metric an entire industry is built on, barely moved with citations. In plain terms, the size of a site's link profile explained only a tiny slice of whether it got cited. Referring domains did a little better than raw link count, which makes sense, but still landed in "weak" territory.
Brand mentions were the story. Whether or not those mentions linked back, sites that got talked about across the web got cited far more. And the strongest signal of all was the messy human stuff: fresh content with a real author's name on it, structured so a model could lift a clean quote.
The part that made us trust our own data was how closely it tracked the big studies. Ahrefs ran the numbers on 75,000 brands and found brand web mentions correlated with AI visibility at about 0.66, versus roughly 0.22 for backlinks, mentions coming out almost exactly three times stronger. Other 2026 analyses put domain authority's share of the variance around 3% and expert-and-freshness signals up near 65%. Our 20-site test, tiny by comparison, landed in the same neighborhood. When a scrappy internal experiment and a 75,000-brand study agree, that's usually the truth talking.
I'll be fair, though: not every study lands here. One analysis of 129,000 domains came out swinging the other way, calling referring domains the single strongest predictor of AI citations, with the top link quartile pulling several times more citations than the bottom. We don't think that contradicts us as much as it looks. Sites with lots of referring domains also tend to be the sites that get mentioned everywhere, get covered in the press, and publish constantly. Links and mentions travel together, so a study that only measures links will hand links the credit for work the mentions did. When you hold mentions and links apart, which is exactly what our test and the Ahrefs work did, the link signal shrinks and the mention signal grows. That's the version we'd bet on.
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Talk to us→The DR-85 Site That Got Ignored
Averages hide the good stories, so let me tell you about two specific sites, because they're the whole article in miniature.
Site A was a DR-85 property with a backlink profile most SEOs would kill for. Thousands of referring domains, years of authority, the works. It got cited less than we expected. When we dug in, the reason was obvious in hindsight: the content was old, most of it had no author byline, and the pages were dense and hard to quote. All that link equity, sitting on top of pages that gave the models nothing fresh or extractable to grab.
Site B was a barely-two-year-old DR-30 site in a similar space. On paper it should have lost every matchup. Instead it got cited constantly. Why? It was mentioned all over its niche, in Reddit threads, a couple of roundups, a review site or two. It published original data with real numbers. Every post had a named author and a visible "last updated" date. It had almost none of Site A's authority and beat it soundly on the thing we were actually measuring.
This isn't a fluke of our sample. One 2026 analysis put it bluntly: a five-year-old DR-85 site without named authors, original data, or current refreshes will get out-cited by a six-month-old DR-30 site that has all three. We watched it happen in our own numbers. If you've been quietly assuming your big domain rating would carry you into AI answers, this is your warning.
Backlinks Didn't Die. They Changed Jobs.
Now let me argue against my own headline for a second, because the "backlinks are dead" crowd overshoots too. Links absolutely still do something. They just do a different job than they used to.
Here's the mechanism. Backlinks still help you get crawled, build authority, and rank in traditional search. And ranking still feeds AI citations, especially on Google. Roughly half of ChatGPT's cited pages come from results ranking number one on Google, and about three-quarters of the URLs cited in Google's AI Overviews already sit in the organic top ten. So links help you rank, and ranking gets you into the pool of pages a model might pull from. That's real, and it's why links aren't going anywhere.
What links don't do anymore is select the citation. They get you into the room. Something else decides who gets called on. A developer on Reddit framed it well: for AI search, backlinks act as foundational trust signals rather than the ranking shortcut they once were. Or as someone on X put it, backlinks are the shovels, but in the age of AI search, mentions matter just as much. You still want a few good shovels. You just can't dig the whole hole with them.
Not Every Engine Weighs Links the Same
One thing our aggregate numbers hid: the three engines don't agree with each other about how much links matter. Splitting the citations out by platform changed the picture in ways worth planning around.
Google AI Overviews were the most link-friendly of the three. That's because Overviews lean heavily on the existing organic results, and organic ranking still runs partly on links. In the data, around three-quarters of the URLs cited in AI Overviews were already ranking in Google's top ten, and the number-one spot had roughly a one-in-three shot at getting cited versus about one-in-eight down at position ten. So on Google specifically, the links that earn you a top ranking do genuinely buy you citation odds.
ChatGPT cared about freshness far more than links. The overwhelming majority of the pages it cited were published or updated in the last ten months or so, and pages carrying a visible update date got pulled in close to twice as often. A giant link profile on a stale page did almost nothing here. A recently refreshed page from a modest site did plenty.
Perplexity was the structure obsessive. It kept reaching for pages with explicit sources, hard statistics, and clean comparison tables, almost regardless of the domain's authority. If your page handed it a quotable, well-sourced claim, it got cited. Link count barely registered.
The practical read: if your buyers do their research inside Google's AI Overviews, keep some investment in the links-and-ranking path. If they live in ChatGPT and Perplexity, shift that money hard toward freshness, structure, and mentions, because links are close to dead weight there.
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What Actually Moved the Needle
So if link count is weak and mentions are strong, what did the top-cited sites in our test actually do? The pattern was consistent, and none of it is exotic.
They got mentioned on trusted third-party sites. This was the big one. The winners showed up in news pieces, niche roundups, Reddit threads, and review platforms. That tracks with the broader finding that the large majority of AI citations trace back to earned media rather than your own site. In one experiment, taking identical content and republishing it through a credible third-party outlet lifted its AI citations by well over 200% compared to leaving it on the brand's own domain. Same words, different address, multiples more citations. The models were weighting the domain doing the mentioning. The brand stayed identical; the address it lived at made the difference. If you do one thing after reading this, make it earning mentions, not links. Our guide on why Reddit became a top AI citation source is a good place to start, and getting into the directories and lists AI pulls from matters just as much.
They put a name on their work. Sites with visible author bylines got cited noticeably more, on the order of a 40% lift in some studies. Anonymous content reads as lower-trust to the models, same as it does to humans.
They stayed fresh. Pages with a visible "last updated" date got cited close to twice as often, and the vast majority of ChatGPT citations come from content published in the last ten months. Stale pages quietly fall out of the answer.
They packed in original data. Pages with a few unique data points were multiples more likely to get cited, because a model reaching for a specific stat wants a page that actually has one. Structure it cleanly, with short quotable claims and clear tables, and you make yourself the easy source to grab. This is exactly why we lean on content built for AI extraction over hoping authority alone carries a thin page.
Here's the honest bit about how we even know all this. We only spotted the mentions-beat-links pattern because we were tracking citations and backlink metrics side by side. Wire that up by hand across three engines and 20 sites and you're looking at a serious chunk of hours every month just to keep the spreadsheet current. You can run it yourself, and plenty of teams do. Or RankControl tracks the citations and correlates them against your backlink and mention data automatically, so you find out which lever is actually moving before you've spent a quarter's budget on the wrong one. We ran the same kind of side-by-side measurement in our llms.txt case study, and it saved us from crediting the wrong thing there too.
So, Should You Still Build Links?
Yes. Just stop calling it your AI strategy.
Here's the budget version of everything above. Keep a foundation of genuinely good links, the kind that earn you rankings and baseline trust, because ranking still feeds citations and that path is real. But once you've got that foundation, every extra dollar does more work pointed somewhere else: earning mentions on the sites your buyers and the models already trust, putting real authors on your content, keeping it fresh, and stuffing it with original data worth quoting.
The teams winning AI citations right now aren't the ones with the biggest link profiles. They're the ones being talked about in the most places, by the most credible sources, with the freshest and most quotable pages. Their link profiles are usually fine, often unremarkable. It's everything stacked on top that does the winning. Backlinks got them into the room. Everything else is what got them cited. Spend accordingly, measure what actually moves, and let the link-package salespeople keep arguing with the data.
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