Note from editor: Today’s post covers an increasingly important topic in the B2B marketing mix: the role of PR in driving AI search visibility. I am happy to welcome this guest post from Dakota Shane Nunley, Director of Content Strategy at Product.ai who is on the front line of turning earned media into AI search visibility and shares some important lessons for all B2B marketers under pressure to deliver AI search performance. I am also happy to say that it lines up well with our Best Answer Marketing framework.
For B2B marketing teams, digital PR spent the past decade perpetually on the chopping block, and as with everything in tech, we’re now hearing the same words uttered every time we open LinkedIn: AI changed it. This time it’s true. Answer engines are grounded on exactly the assets digital PR has always produced, the authority publications, the expert quotes, the third-party mentions, the original data.
I run the Authority Program (AEO/SEO and digital PR) inside Product.ai (formerly Demand.io). Here are the new physics of digital PR, how to get cited in the age of AI, and the most common myths I see circulating your feeds today.
What Are the New Physics of Digital PR in the Age of AI?
What actually changed is the physics of the machines we’re optimizing for. For years, digital PR was about driving authority via traditional search engines, namely Google, which is an army of crawlers that ranks pages. Today, AEO is optimizing for LLMs, pattern-recognition machines that cite passages.
So why would that matter? Well, SEO has the luxury of pages and links to distinguish entities, LLMs don’t. An answer engine runs on an accumulated sense of which claims keep showing up next to your name, and if it can’t resolve you into a real, distinct entity, you’re out of the answer, and no ranking report will ever tell you it happened.
How Does My B2B Brand Get Cited in AI?
Chase the Canonical Stat
As a B2B marketer, you should be chasing what I’ve started referring to as the “canonical stat,” a piece of original research, usually in the form of a fact or figure, adopted as canon in your category. LLMs cite it, journalists quote it, and industry roundups are built on it. It’s the holy grail of these new physics, because the companies that own the canon own the LLM answers.
So, how do you get there? Start by productizing your data. Somewhere in your company is the survey nobody has fielded, the experiment nobody has run, the dataset nobody outside your walls has seen. Then design the research backwards from the answer gap.
Before we fielded ours at Product.ai, I audited which studies the models already treated as canonical, found the questions they had no source for, and built our survey to address those gaps while fulfilling our curiosity and questions we wanted answers to. Since then, that AI shopping study has become a marquee citation inside the answer engines faster than any other activation we’ve run, with over a hundred media pickups, a national TV segment, ingestions into listicles, and citations in high-trust publications like eMarketer. Create a canonical stat in your category, and you’ll be earning AI visibility across this new world of digital PR.
Build Your Entity Signals
The stronger your entity signals, the more confident an LLM can be including you in its answers. Without this foundation, all the sexy media mentions won’t add up to much. One surefire way to strengthen your entity signals is by combing through your ‘authority files’ — the third-party hubs that LLMs treat as ground truth. Every industry has its own. For most B2B companies that means Wikidata, Crunchbase, G2, LinkedIn Company Pages, and other niche databases your category runs on. Learn every one of yours, because the models trust those hubs more than your website. Then comes the janitorial part of the job, ensuring the wider footprint tells one consistent story: the About page, the FAQ, the social profiles, the reviews.
Nobody claps when you fix your Crunchbase entry, but it lays the foundation necessary to take advantage of your media hits across digital PR campaigns.
Publish Proprietary Insights
This has become common knowledge in recent years, but for good reason: the best way to combat the era of AI slop is to compile and publish proprietary insights an LLM can’t replicate. That’s what productizing your data actually means. Take the raw material your company already generates, the transaction data, the survey results, the patterns your team notices before the rest of the industry, and package it into something citable, whether that’s a named report, a recurring benchmark, or something similar.
When you begin ramping up your first-party data engine, it will serve you twice. A proprietary insight can take almost any shape, an original statistic, a benchmark nobody else tracks, a pattern pulled from your own customer base, a contrarian read your team earned in the field, and every one of them does the same double duty. Reporters want it because they can’t get it anywhere else, and the answer engines keep lifting it long after the coverage runs.
What Are the Most Common Myths of B2B Digital PR?
Myth 1: Only the Big-Name Outlets Matter
A decade of SEO trained us to write off the high-DR (domain rating) outlet nobody visits. But we’re finding that LLM ingestion doesn’t necessarily care about pageviews. A model weighing a claim counts how many independent sources agree on it, which turns that DR-90 outlet into a premium placement.
When SimplyCodes, coupon platform and child company of Product.ai, published a study on how often promo codes fail at checkout, local and syndicated news carried it into over a hundred TV markets, including a Scripps News segment syndicated to a host of broadcast stations. To a model, that’s dozens of independent, trusted news entities agreeing about one brand.
Myth 2: One Brand Mention at the Top Is Enough
Kevin Indig, the growth consultant who coined the term ghost citations, put a number on this one with Semrush in June. Across 3,981 domain appearances in AI answers, 61.7% were ‘ghost citations,’ the page used as a source, the brand never named. Ouch.
Ghost citations are half the problem. Numbers also get repeated with the figure wrong, the source missing, or both. And there’s a stranger case I’ve started calling credit drift: a statistic keeps circulating while the credit slides to a bigger or more plausible name than the one that actually published it. We’ve watched LLMs hand our own study’s findings to Gartner.
So what’s the fix? Entity density, your brand name welded to every stat, in the same sentence, every time. Write “Acme’s 2026 study found that X% of buyers did Y…”. It’s okay if it feels repetitive because a sentence that carries your number without your name just becomes a donation.
Myth 3: The Press Release Is Dead
The obituary numbers are real. Meltwater tracked more than 8 million LLM citations in May 2026 and found press releases were 0.2% of them, and Muck Rack put earned media at 84% across 25 million AI citations. Both companies sell PR software, so grade accordingly, but the direction matches what I see every week.
The press release itself might not get cited for as long as you’d like, but that’s not the point. Press releases should be seen as the match, not the candle. A release exists to ignite the third-party coverage, and the coverage is what the machines actually consume. Measuring whether releases get cited is measuring the ignition instead of the fire.
In our own campaigns, we’ve observed press releases doing their jobs wonderfully. As with everything in a burgeoning field though, treat every benchmark as a prompt to measure your own, because nobody’s numbers generalize yet. The canon in most B2B categories is still forming, and it’s a lot easier to get written in while it is.
What Happens Now?
Every AI-search playbook is written for the buyer typing a question. But a second kind of user is typing now: the writers. Reporters on deadline ask an LLM for three recent stats on B2B buying behavior, with sources. The thought leaders your prospects follow pull their evidence the same way. And whatever the machine hands them ends up published, which feeds the next round of answers.
That loop is why it’s so critical to strive for canonical stats while avoiding ghost citations. A stat circulating without your name costs you the article the reporter never writes and the deck the analyst never builds. It’s also why your next PR hire matters more than your next tool. Find the specialist who knows your field’s authority files the way a beat reporter knows sources.
Best of luck.
