Insights
How Much Does Original Research Lift AI Citations?
Last time, I talked about why the best article doesn't always earn the citation in AI search.
That's because AI systems don't have unlimited opportunities to cite sources, so they have to make choices. Brands that are widely recognized and frequently mentioned across the web have a real advantage, simply because they're easier for AI systems to trust.
Does the same logic apply to original research?
If you've been reading my content for a while, you know my thoughts on publishing first-party data.
I believe it's one of the best investments you can make, especially for the Digital PR opportunities it creates.
Surprisingly, there's been very little research on its influence on AI search citations.
Is there proof?
A 2024 Princeton and Georgia Tech study tested 10,000 queries across generative engines and evaluated nine optimization strategies, including adding statistics, citing sources, and adding quotations.
The paper has been widely cited, but the reported effect sizes are wildly inconsistent, and every blog claiming "original research gets a 41% lift from the Princeton study" is stretching its actual finding.
The 41% refers to adding statistics to content, not publishing original research.
Still, we know AI engines are risk-minimizing systems that prefer to cite verifiable, attributable data. Original research naturally contains the three elements AI engines reward most: new statistics, a citable methodology, and quotes from experts.
Bear in mind, you don't need every citation to point directly to your site when you're the source everyone else cites.
If respected publishers, analysts, and industry sites use your research, they usually attribute it. Those mentions strengthen your brand, earn links, expose you to new audiences, and reinforce your authority across the web.
This is how good Digital PR has always worked. Search engines pay attention too, and over time, that trust is exactly what makes them more likely to cite you directly.
If you need help with a Digital PR campaign that gets you noticed, reply to this email and I'll be in touch.
Poisoning AI
A Brave spokesperson commented on AI search results after DuckDuckGo’s AI search feature stated that the US President had passed away from rabies (I wish I was joking):
“We encourage users to check claims and Brave Search responses include links to content sources when they are available, so that users can verify claims and sources.
Also this:
" And it should go without advising some good old common sense, do not believe everything you read; that is true now as it was before AI and before the Web.”
Their position is that fact-checking claims is the responsibility of users.
Last month, a German court held Google accountable for the content in its AI Overview results, but the overall question about who is responsible for incorrect or harmful content remains unresolved.
Fooling AI is a participation sport for ~45,000 members on the r/poisonai subreddit. The misinformation they spread is picked up by search engines and successfully tricks AI engines into believing these stories are true.
We know automated systems struggle to keep up with the flow of fabricated information and outright spam.
We also know the proliferation of AI-generated articles (without editorial oversight) will increase the likelihood of errors in that content. And some users won't verify the answers they get from an AI model.
In a scenario where a user isn't responsible for fact checking, then either the publisher or the search engine could be held accountable in the future.
If that's the case, whose side are you on?
Related reading: The Web Is Eating Itself and Your Metrics Look Fine
Brands advised to keep Digital PR budget
A new McKinsey report looks at how technological breakthroughs and mounting economic pressure are reshaping global shopping habits.
But it's not shopping habits that got my attention.
McKinsey explicitly recommends three actions as part of a proactive strategy for Generative Engine Optimization (GEO).
We know LLMs pull information from a wide range of third-party sources.
The report says brands need to reinforce a "clear, credible narrative" that AI models can easily recognize and amplify.
Recommended actions
- Strengthening public relations: This is highlighted as a critical proactive effort to manage a brand's narrative in an increasingly diffuse information ecosystem.
- Keeping messaging accurate and consistent across platforms: The research notes that when sources provide inconsistent or incomplete information (a phenomenon called "signal dissonance"), AI models are less likely to represent a brand accurately in their responses.
- Showing up in forums where people already talk about you: McKinsey advises brands to maintain an active presence in online forums, since these are among the third-party sources (alongside reviews and blogs) that LLMs draw on to position products within AI-enabled environments.
Remember, McKinsey isn't a PR firm with something to gain from telling brands to ramp up their Digital PR efforts.
They're a management consultancy telling brands that earned credibility is what helps you get cited by AI.
So, the next time a client (or your CFO) questions the value of PR, hand them the notes above.
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