Public Relations Has Become Machine Relations — Most Founders Have No Idea What This Means

I have spent nearly a decade placing brands in the kinds of publications most founders dream about. I say that not to brag but to be clear about how deep in the PR world my adult career has been. When you are inside a line of work long enough, it becomes your identity, and when that identity is threatened, most people break down rather than embrace the inevitable changes coming their way.

To anyone who relies on PR to build their brand, that change is not coming. It is already here. Before you take this as another doom-and-gloom article, let me say this right now: PR still works. Earned media is more valuable right now than it has been in a decade, and maybe more valuable than it has ever been. Today’s PR playbook, though? It is dying. Rapidly.

A placement in a major outlet builds credibility, reaches the right people and earns trust. This has been true since PR existed. Where that thinking falls apart is the belief that the job ends once the article goes live. That is where traditional PR is breaking down. Not casually. Structurally.

Bain & Company found that 80% of consumers now rely on AI-generated results for at least 40% of their searches, and 60% of those searches end without a click to an external site. An MIT-led study of 24,000 search queries found that 67% of U.S. queries now return AI-generated answers, up from 42% a year prior. Your coverage still gets read by humans. But before most humans see it, a machine has already decided whether your brand is worth citing.

So, to answer why traditional PR is breaking down: humans are no longer the first reader. Machines are.

PR was designed to get the story picked up and published. Google crawls it, the founder posts it on social and the sales team drops it into outreach. All good and all valuable, sure. But there is a second and more important job now: making that coverage legible to the machines that now control where buyers get their answers.

I started calling this Machine Relations in 2024 after watching this shift happen from the inside. Through years of figuring out how to secure earned media on a results-based model at AuthorityTech, I realized rather abruptly that securing the press hit was only part of the solution. The other part was ensuring AI engines could retrieve, understand and cite the article.

Nothing else in the market named the full problem or the full workflow required to solve it. My co-founder Christian Lehman was seeing the same pattern from the growth side as clients started asking for AI results, metrics and the answer to the question now showing up in every founder’s head: “How do we show up in ChatGPT and AI Overviews?” What slapped us both in the face was this: the placement still matters, but what the machine can extract from it matters more in the AI search era.

When this truly clicks, the opportunity is staggering: your brand can show up not just as one page in a sea of millions, but as the direct answer inside ChatGPT, Perplexity and Google AI Overviews when buyers ask the questions that matter most in your market.

Here is what I tell founders when they ask me what to do about this.

Stop treating placements as endpoints

The placement is not the product anymore. The placement is raw material. When your brand gets featured in a credible publication, that article becomes a source that AI engines can either find and use or ignore entirely.

The difference has nothing to do with how impressive the outlet’s name is. It has everything to do with whether the coverage contains specific, extractable claims that a machine can confidently attribute to your brand. Research across 80 million AI citations shows that brand mentions correlate with AI visibility at three times the rate of backlinks. In other words, press mentions are becoming exponentially more valuable, but only if they actually say something worth citing.

Ask your PR team the question they cannot answer yet

Here is the question: Can the coverage you are securing right now be cited by an AI engine as the answer to a specific question a buyer in your market would ask?

If your team cannot answer that with a yes and a concrete example, then you are paying for coverage that compounds in a world that no longer exists. The success condition changed underneath them. Many PR firms were already struggling to secure coverage. That struggle has been extended one step further, so expect a polished non-answer.

Before you approve a pitch, ask what question the resulting article should help answer. If you or your firm cannot name the question, the coverage is probably being built for optics or to fulfill a contract. The hard truth is that a quote about your “innovative culture” will never be cited. A stat about your growth rate or a named differentiator in your category will.

Audit your brand through the machine’s eyes

Go to ChatGPT, Perplexity and Google’s AI Mode right now. Do not search your brand name. Search the category: “What is the best X for Y?” “Who should I hire for Z?” “What are the top companies doing W?”

If you are not in the answer, the machine does not know you exist in that context. That is your gap. Everything you invest in visibility should be reverse-engineered from what the machine says when your name is absent.

This is uncomfortable because it removes the vanity layer. You may have press, rankings and a polished website with thousands of blog posts. None of that matters if the machine does not connect your brand to the questions buyers are actually asking.

Build earned media around machine-answerable questions

Most founders pitch stories based on what sounds impressive to humans. That still matters. But the coverage also needs statements AI engines extract and reuse: specific data points, named comparisons and concrete claims with context.

“We grew 300% year over year” is extractable. “We are disrupting the industry” is not. “We help mid-market finance teams close books 40% faster” is extractable. “We are transforming finance operations” is not.

Independent studies consistently show that 82-89% of AI citations come from third-party editorial sources, not brand-owned pages. Earned media remains one of the most trusted source types for AI engines when the content gives the machine something real to work with.

So stop asking only, “Will this article make us look credible?” Ask: “What exact sentence in this article would a machine cite when explaining why we matter?” If there is no answer, the article is probably weaker than it looks.

Measure what the machine says, not just what Google ranks

Share of voice was built for the old world. The metric that matters now is what I call share of citation: how often your brand shows up as a cited source in AI-generated answers relative to your competitors.

Run your most important category queries across ChatGPT, Perplexity and Google AI Overviews. Track whether you are cited, what the engine says about you and how it compares you to alternatives.

Do not just track whether your name appears. Track the language. If the machine describes your competitor as the category leader and describes you as an option, that gap has commercial consequences. If the machine cites a competitor’s earned media and ignores yours, your PR problem is no longer visibility. It is machine legibility.

The founders who will win the next five years understand that the first reader and filter of what the human audience sees changed.

PR built the foundation. It still does. But if the foundation just sits there without being made legible to the machines that now control discovery, it is an asset that depreciates the moment it publishes. Machine Relations is the discipline that prevents that depreciation and sets up the golden opportunity on the other side of this shift.

The shift is not coming. It’s already here. The only question left is whether your brand is in the answer or watching from outside the conversation while your competitors get cited.