The Matthew Effect: Why AI Search Loves Big Brands (and What You Can Actually Do About It)
We’re used to it now: You type a question into Google, and instead of the familiar list of blue links, you’re met with an AI-generated answer at the very top. It names two or three companies.
They’re not necessarily the most insightful. They’re usually the biggest.
That’s the Matthew Effect at work — the idea that “the rich get richer.” The term comes from sociology, which studied citations rates and found that famous scientists got cited more often, even when others publish equally strong work. In business, it explains why big brands dominate the shelf space at eye level in the grocery store. And in AI search, it explains why HubSpot, Forbes, or a Fortune 500 company’s white paper shows up in the answer box, while your brand gets ignored.
AI Citation Research and the “Big Brand” Bias
Studies are beginning to put numbers behind this phenomenon. For example, Algaba et al. (2025a) found that LLMs systematically favor content that already looks authoritative: highly cited, recent, cleanly packaged. In a follow-up study (Algaba et. al. 2025b), the team found that LLMs not only replicate human preference for big, popular sources, they exaggerate it.
For marketers, that means one thing: AI isn’t an equalizer. It’s a megaphone for brands that already have volume.
Why It Matters for Marketers
In traditional search, you at least had a fighting chance to appear in the list of 10 blue links on page 1. Even if you weren’t first, you might show up in positions 3, 4, or 5 — and still capture attention.
AI answers collapse that landscape. Instead of ten results, there might be two or three brands mentioned by name. If your company isn’t one of them, you’re not just buried lower on the page. You’re invisible.
This changes the customer journey:
- Discovery is compressed. People may never scroll down to see traditional results.
- Mentions act like endorsements. If your brand name shows up in the AI box, it’s the new “as seen in.”
- Absence is costly. If you’re missing at this stage, you don’t even make it into the consideration set.
Why AI Loves Big Brands
When you look at the big brands that tend to dominate AI search results, the pattern is easy to spot: Their website already carries layers of “authority signals”—armies of backlinks, tightly structured metadata, and polished technical setups that make them easy for machines to parse. Their content also shows up across countless domains, from blogs to reports to syndicated media, so the models bump into the same messages again and again during training or retrieval.
These companies also tend to update constantly—refreshing pages, publishing new guides, releasing white papers—and they get an extra edge from the strong bias toward recent content.
Finally, there’s the simple trust factor. Just as human readers instinctively assume that a well-known name is safer to quote, LLMs tend to do the same.
The combination is powerful: Brands that already have reach and reputation get reinforced by the very systems meant to surface information, which means their visibility snowballs while smaller voices struggle to break through.
What You Can Actually Do About the Matthew Effect
Smaller players can’t out-shout Fortune 500s. But you can increase your odds of being named in AI answers by leaning into the levers you control:
- Fuse Brand + Expertise
- Don’t just state facts. Attach your brand to them: “At company X, we tested…”
- Make your name inseparable from the insights you publish.
- Structure for Recognition
- Use schema (Article, FAQPage, Organization, Person).
- Add author bylines and updated dates. These small cues make content look “authoritative” to an LLM.
- Publish in Clusters
- Don’t just write one-off posts. Build linked hubs around key topics.
- The denser the content cluster, the stronger your authority signal.
- Repurpose Across Surfaces
- Publish to LinkedIn, Medium, Substack, even PDFs and slide decks.
- The more places an LLM sees your brand tied to a concept, the more likely you’ll get surfaced.
- Own Niche Queries
- You won’t beat HubSpot for “best AI tools.” But you can dominate “AI visibility tools for B2B marketers” or “why AI visibility dashboards disagree.”
- Narrower prompts mean fewer competitors — and higher odds your name gets in the box.
Competing with Big Brands Isn’t Impossible…
Here’s the message: You’re not trying to dethrone HubSpot on generic queries. (If you are, bless your soul). What you are trying to do is show up where your buyers are actually searching. AI search might be biased, but it also creates opportunities: A buyer asking a niche, intent-heavy question might see only two or three names. (Words Have Impact ran into this when creating content for a Niche software company, BargeOps…case study forthcoming!) If your brand is one of those sources, you’ve just leapfrogged the giants.
Mindset Shift: AI Mentions Are the New Shelf Space
AI search isn’t fair. It reinforces the Matthew Effect, giving more oxygen to brands that already dominate.
But, ultimately, marketers don’t care about “citations.” What matters is whether your brand name appears where buyers look first. An AI mention is the new shelf space: It’s eye-level placement in the digital grocery aisle, if you will.
You may not be able to change the system, but you can work the levers: Tie your brand tightly to your insights, structure your content for recognition, build topical density, and aim for the niches where your buyers are looking.
Because in the AI era, being absent from the answer box is tantamount to invisibility.
Works Cited
Algaba, A., Holst, V., Tori, F., Mobini, M., Verbeken, B., Wenmackers, S., & Ginis, V. (2025). How deep do large language models internalize scientific literature and citation practices?. arXiv preprint arXiv:2504.02767.
Algaba, A., Mazijn, C., Holst, V., Tori, F., Wenmackers, S., & Ginis, V. (2024). Large language models reflect human citation patterns with a heightened citation bias. arXiv preprint arXiv:2405.15739.
Brandon N. Towl is an SEO strategist and content expert who helps companies stand out in both traditional search and emerging AI-driven discovery. He is the founder of Words Have Impact, a content agency, and Human Driven Understanding, a consultancy focused on buyer insights and strategy.
