There are two very different ways to make information machine-readable. One helps a machine identify what’s on a page. The other helps it understand what’s actually being said.

Those are not the same thing. And new research suggests the distinction matters for AI citations.

What is Thing One?

Thing One is schema markup, often implemented using JSON-LD: structured information added to a webpage that machines can read.

Think of the tag sewn inside a shirt collar. A shopper never sees it, but it tells a scanner at checkout what the shirt is. Schema is that tag, for a webpage.

It has a real job: telling a search engine like Google what’s on a page, a product, a price, an event, a person, an organization, so Google can build a result.

That’s legitimate. It’s just not the job this piece is testing.

What is Thing Two?

Thing Two is the words on the page, organized clearly: clear headers, one idea per paragraph, the source of a fact sitting next to the fact, a real question answered directly.

No hidden notes, no code to interpret. Just information a person could read and understand right away.

Thing One identifies. Thing Two explains.

We’ve been talking about “machine-readable” as a technical problem. AI adds another question: can the machine actually understand what you’re saying well enough to use it?

What does “getting cited” actually mean?

Ask ChatGPT a question, and sometimes it names a company, person, or article as where it got the answer. That’s a citation, the AI version of a reporter naming a source instead of using the quote without credit.

More citations mean more people hearing your name, or company name, from a tool they already trust.

So does Thing One also earn citations?

The data doesn't show that schema earns more AI citations.

Ahrefs, an SEO research company, added Thing One, schema, to 1,885 real webpages and tracked citations for a month afterward. Citations barely moved. On Google’s AI Overviews, they actually dropped.

SearchVIU tested it from the other side. They built several versions of the same product page, some showing the price in plain visible text, others hiding it only in code, JSON-LD, with nothing visible anywhere. AI tools found the price wherever it was visible. In their tests, they didn’t find it where it existed only in hidden code.

Now look at Thing Two. Notified analyzed more than 8,000 GlobeNewswire press releases and found that 99.3% were cited by ChatGPT or Claude. The average time to first citation was just eight hours, and well-structured releases generated 2.6 times more citations on average.

Thing One helps AI identify the page. Thing Two gives it something it can actually use.

So should you drop schema?

No. Keep it. It’s still doing its own job, and Google still reads it.

What actually earns the citation, then?

The question isn’t “is my site machine-readable?” It’s “is my expertise understandable enough for a machine to use?”

Write like you’re explaining something to a person, because you are. Say the source and number in the same sentence. Answer the real question your reader, or an AI, is asking, including in your headers. Make the claim, context, evidence and attribution easy to connect.

AI doesn’t just need to find your information. It needs to understand it well enough to reuse it.

What it means for the RECORD:

Documentation has two jobs: one helps a search engine identify what’s on a page; the other helps a person, and increasingly AI, understand what’s actually being said.

The web taught us to document for indexing. AI is forcing us to document for understanding.

I’m going through my own site against this split right now, as part of the audit I’ve been running on myself in public all summer. I’m not sharing what I found yet. That’s coming.

This newsletter, for what it’s worth, is built like Thing Two on purpose: real headers, the source next to the number, one idea per paragraph, no hidden information you have to decode. That’s what Thing Two buys you: understanding.

Thing One isn’t the villain.

Thing Two isn’t the replacement.

They just have different jobs.

Build the Record. Become the Source.

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Sources

• We Tracked 1,885 Pages Adding Schema. AI Citations Barely Moved. — Ahrefs, May 11, 2026

• Schema Markup and AI in 2025: What ChatGPT, Claude, Perplexity & Gemini Really See — SearchVIU, Dec 2, 2025

• PR News | The Press Release’s Role in the Age of AI Answers — Erik Carlson, CEO of Notified, via O’Dwyer PR, Aug 26, 2026

• Schema Markup Adoption: 5,000-Site Audit and Findings — Digital Applied, Apr 26, 2026

Snow White’s stepmother asked a mirror for a ranking and got exactly what she asked for. A number. No method, no explanation, no way to check its work. She built a whole plan around it anyway.

That’s most AI visibility scores right now. And I’m surprised our industry hasn’t dug deeper into this yet, because on May 20, 2026, AMEC, the group that sets the global standard for PR measurement, published new principles for measuring AI visibility. This is the first real answer, from the people whose job is measurement standards, on what a number has to prove before anyone should trust it. The rule: a number isn’t evidence unless someone can explain how they got it.

Can we talk about what’s actually happening here for a second?

Our industry is changing. PR and comms are finally getting pulled into THE room where decisions get made, and it’s well deserved. Brands started noticing they don’t show up when someone asks ChatGPT who to trust, and the answer to that lives in reputation, credibility, and authoritative coverage. Our domain. Nobody handed us a rulebook for it though. We’re writing it as we go.

That part is fun. Not the pressure of it. The actual figuring it out.

Every client and founder I talk to wants the same thing: get my score up (become part of the answer). I get why. It’s the natural question. But it’s the wrong first question, because a score is a mirror, not a roadmap.

So I rebuilt how I measure Recognition, the RECORD layer I’m covering this week.

Every audit starts with Spyglasses.io, a white labeled AI visibility platform built specifically for PR and marketing teams. I use it because it gives me a consistent way to see how ChatGPT, Gemini, Claude, Perplexity, and Google AI Overviews actually describe a brand, and just as important, the coverage and conversations shaping those results. I can see not just what AI is saying, but what’s influencing the answer. No guessing.

I then run those findings through the RECORD framework, layer by layer: Record, Expertise, Corroboration, Owned, Recognition, Documentation. Each layer produces a specific finding and a specific next step. Not just a score.

That’s the moment. The story stops being a number and starts becoming evidence.

Here’s what that looked like on a real audit. One client is an arts educator whose students land stage and screen roles. Nothing under his own name has been published in many many years. His site was never built for a machine to read. So I built him a new one.

The one piece of trade coverage built for exactly his category, a roundup of the elite experts to know and trust, profiled the studio he works out of. Not him.

That’s not a ranking problem. That’s a record that doesn’t exist, in the one place it needed to.

The method has to meet that same bar AMEC is setting. Every audit I run now documents which queries ran, on which platforms, on what dates, and states its own margin of error instead of presenting a number as exact. That’s the disclosure AMEC is asking for. In writing, not assumed.

A better AI score was never the goal. Getting the credits, the named programs, and a corrected, disambiguated identity actually documented somewhere AI and search can find, cite, and get right, is.

The mirror can keep ranking us. I’d rather build the thing it’s reflecting.

Build the Record. Become the Source.
____________________________________________________________________________
Sources:

• AMEC GEO Principles

• AMEC launches GEO Principles to bring rigour to AI-led communications measurement

Citation research is starting to feel like information overload, and maybe that’s the point. Ask six different researchers how often AI cites a brand’s own website, and you’ll get answers from 2.9% to 86%. Not because anyone’s wrong, they’re just measuring different things and calling it the same number (full breakdown here).

Turns out it comes down to the question being asked. Ask a fact, like “what does this cost,” and AI usually goes straight to the source: nearly 60% of the time, per Yext. Ask an opinion, like “which one’s better,” and AI turns to reviews instead. Foundation found brand sites get cited just 2.2% of the time on those comparison searches.

So if your plan is “fix my website and I’ll start showing up in AI answers,” slow down. That’s not quite how it works. But don’t stop building the site either.

Here’s why. In RECORD, Owned was never meant to get you cited first. Earned media does that. Owned is what’s still standing when AI checks the citation. You can’t vouch for yourself, but someone else can, and then AI checks your site to see if it holds up.

Billy Beane didn’t win by getting his players more at-bats. He won by changing who made the team. Owned works the same way. It’s not the stat that gets you picked. It’s the check that keeps you in the lineup.

A home run doesn’t count until you touch the plate. Owned is the plate. Earned media is the swing.

So before you chase your next mention, check your own plate first. Does your About page actually match what people are already saying about you? If not, the run doesn’t count.
_________________________________________________________________________
Sources:

• Stacker: How Earned Media Distribution Expands AI Visibility

• OptimizeCamp: Do You Need A Website For AI Visibility? What 680 Million Citations Say

• Yext: 86% of AI Citations Come from Brand-Managed Sources

• Otterly AI: The AI Citation Economy (2026 Report)

• Foundation: The 14x Gap Between Branded and Unbranded Prompts

Huh, right? I thought people would just pick a team. They don’t.

This is from Skyword’s AI Buyer Research. They asked 1,000 U.S. adults in April what they do when a company’s own website says one thing and an AI assistant says another. And most people basically go “nah, I don’t trust either of you, I’m doing my own digging.”

Which, honestly? Valid. I search for stuff to buy this way too.

Think about it like this. Say you ask ChatGPT to compare a company’s product to their competitor’s, and it doesn’t match what’s actually on the company’s site. Now you’ve got two different stories and zero reason to believe either one. So what do you do? You open a new tab. You go looking for someone who isn’t the brand and isn’t the AI.

That’s it. It’s just a reference check.

AI doesn’t just take the brand’s word for it, and there’s a simple reason why. A company describing itself is like a guy describing himself on a first date. Of course he says he’s great! Everybody does. AI knows that, so it goes and calls your references instead. Same thing a hiring manager does. Nobody hires someone off their own word alone. You call their old coworkers. And if those coworkers tell a different story? The manager doesn’t split the difference. They go find a fourth person.

That fourth person is your 54%.

In a real reference check, you hand over the names. You pick your three biggest fans, obviously. AI doesn’t ask permission for that. It just finds whoever’s already out there talking about you: a reporter, a customer, blogger or random analyst. You don’t get veto power. Whoever’s on record is the record.

So what actually counts as corroboration?

Corroboration just means someone with nothing to gain backs up your story. A journalist, a customer, an analyst, a peer. Unpaid, unprompted. It’s the reference check that kicks in the second your story and AI’s stop matching.

Without it? A buyer asks who founded your company and gets a competitor’s name. A prospect hears a product you stopped selling last year is still available. A journalist quotes pricing from two years ago. AI fills the gap with whatever’s out there. The buyer can’t tell who’s right, they just know two things disagree, so they go find a third. And if all they find is more stuff you wrote about yourself? You lose. By default.

One good article doesn’t fix this, either. One article is a data point. It’s not a pattern. Similarly, one glowing reference is just one former coworker who happened to like you. More and more data confirms AI authority comes from the same claim getting repeated, by different independent people, over and over. Old-school PR counted placements. This counts consistency.

Four things move the needle now, and they all do the same job:
1) Someone with zero incentive except honesty backing you up: earned media a reporter actually verified, not a press release with new formatting. 2) Analyst coverage, from people whose whole job is being skeptical. 3) Podcasts and guest bylines where someone else’s audience vouches for you. 4) Customer stories, told in the customer’s own words.

Skyword’s research backs this up from a totally different angle too: brand influence now flows through places you can guide but can’t fully control including publishers, analysts, review sites. This is exactly why one great placement isn’t the win. Consistency is.

Where this fits in RECORD

RECORD is my thesis and working framework for building earned trust. It’s how brands and people become discoverable through AI authority. PR, evidence, content, and trust meet here.

Most AI visibility tools tell you whether you appear. RECORD tells you whether you’re understood, and whether you’re worth citing.

It measures how likely AI systems are to see you as a trustworthy source, based on evidence vs. your own claims about yourself. Six layers: Record, Expertise, Corroboration, Owned, Recognition, Documentation.

Corroboration is the layer that answers exactly what this Skyword data is pointing at. When neither your word nor the AI’s answer is enough for a buyer, what actually is?

Bottom line

AI is running a reference check on your brand right now, and nobody sent it a list of who to call. Go ask ChatGPT or Claude who you are and what you do. Then check what comes back. Does it match what you’d actually say about yourself?

Wherever it doesn’t? That’s a reference you don’t control yet.

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Build the record. Become the source.Sources: Skyword AI Buyer Research; When AI Gets Brand Information Wrong, Consumers Look Beyond the Brand (Skyword, June 2026); How to Adapt Enterprise Content Strategy for the AI Search Era (Skyword).

Then I read what network scientists at Northeastern did with this summer’s World Cup, and I haven’t watched a match the same way since.

They’re not counting goals. They’re mapping identity. The goal is the announcement. The win happened long before it.

Most brands only show up for the announcement. There’s a moment in every match the highlight reel skips. Not the goal, but the eleven touches before it.

Argentina’s signature is built to find one man. Norway’s signature runs long and right, aimed at players tall enough to win it in the air. Spain’s signature splits in two directions at once, a short combination on the left and a long ball hunting an eighteen-year-old on the right. Northeastern’s NetSI Sport group mapped all 48 World Cup teams this way, tracking the five passing patterns each team ran more than expected, above the baseline every team shares.

That baseline is the part that struck me. Brennan Klein, who leads the research, said most passes in a match are the ones any team would make, formulaic, interchangeable, forgettable. What separates a team isn’t that it passes the ball. It’s the handful of patterns it runs again and again that no other team runs the same way.

That’s the part the RECORD Framework calls Expertise. Not the pass, not the game, but the thinking that shows up as a repeated deviation from what everyone else is doing, until it’s recognizable on sight. Spain’s split identity didn’t start this tournament. Argentina’s whole shape existing to find Messi didn’t start this tournament either. Both were built match after match, long before anyone outside the data was counting.

A forty-eight team World Cup means more teams arriving without an established shape yet. New entrants without a record. Everyone starts there. Norway didn’t invent its long-ball dependence on Haaland and Sørloth for this tournament. It built that signature, above the baseline, one match at a time.

The score is what happened in ninety minutes. The record is what was true the whole time underneath it. AI citation works the same way: it rewards the pattern, not the post.

Four things to take with you:

1. One isn’t a pattern. Authority shows up in what repeats above the baseline, not in what’s loud once.

2. The deviation gets recognized, not the moment. That’s why a record compounds and a campaign doesn’t.

3. Every new entrant starts without a record. The question is whether you’re patient enough to keep producing the work that lets one form.

4. AI reads the same signal. It's not indexing your best post, it's tracking whether the same idea keeps showing up.

This piece grew out of Northeastern Global News’ coverage of the 2026 World Cup, drawing on research from Northeastern's NetSI Sport group.

If you want to see where your own record stands, which layers are humming and which are quiet, the RECORD Framework is the place I’d start.

So I asked. Formally. I ran the full RECORD Audit on my own firm, the one I just launched. The same one I run for clients. Five discovery queries. Five platforms: Google AI Overview, ChatGPT, Gemini, Perplexity, Claude.

I expected bad results. What surprised me wasn’t that they were bad. It was how they were bad. If RECORD only works after the numbers improve, it’s marketing. If it works when the numbers are zero, it’s measurement.

Here is my scoreboard, dated July 6th, the day before this newsletter launched:

• The audit recorded 62 discovery searches trying to answer questions about my category. I ranked for 0 of them.

• AI cited 295 sources when answering those questions. Zero were mine.

• Brand mentions: 0. Share of voice: 0%.

• Brand consistency, meaning how accurately AI describes me when asked directly: 67 out of 100.

• My site’s structured data score: 40%. Fast site. Clean site. Still not enough context for AI to confidently understand who I am.

The audit worked exactly as it should. It measured reality, not potential. Then the audit showed me something I didn't expect. It also logs AI’s discovery searches.

When asked what the RECORD Framework was, I watched it fill in the blanks. Among the searches it ran were:

"RECORD framework Result Evidence Context Reason Options Decision"

"RECORD acronym Reach Engagement Conversion Outcomes Results."

Neither exists. AI started filling in the blanks because there wasn't enough published evidence to confidently associate RECORD with my framework.

And my favorite finding: AI isn’t sure I’m me. It blends my firm with a Silver Communications in California and another one in Australia. I built a framework about AI visibility, and AI thinks I’m three other companies.

I’ve spent years helping companies build authority. What didn’t exist until this month was a public record under this firm’s name.

Plenty of people publish frameworks for measuring AI visibility. Almost nobody publishes their own numbers while those numbers are bad. That’s why I am making myself Client Zero. Not a new metric. A public track record.

The first layer of the framework is Record: publishing. Not one great article. Not a launch week. A body of work that accumulates until AI has something to learn from.

So here’s what I’m doing about it

Over the next six weeks, this newsletter walks through the framework one layer at a time, what each layer is and how to build it. Then I re-run the audit and publish what changed.

I’m calling it Client Zero. This post is the starting line, published before I know how it ends.

I’m not promising the numbers will move by early September. I’m promising the work gets done.

Nobody controls when models re-crawl my site or who they decide to cite. And anyone who promises you a citation by a date is selling something. What I control is what gets published: the FAQ page, the schema, the pitches, the cadence. Every fix the audit recommends gets implemented. In September, I re-run the audit, same tool, same queries, same platforms, and publish the before and after, whatever it says.

If the numbers jump, you’ll see it. If they crawl, you’ll see that too.

That’s the difference between building authority and claiming it. The scoreboard stays honest either way.

Your turn this week

One action, fifteen minutes: write down every piece you’ve published in the last twelve months. Articles, posts, pages, podcast appearances. Count them.

That number is the size of your publishing record. Most people have never counted. The number is usually smaller than it feels, and it explains more about your AI visibility than any tool ever will.

Mine was 8. That’s why my share of voice was zero. Next week: Expertise, and why a named framework nobody can find is just a name someone else’s guess can fill.

Build the Record. Become the Source.

I run this same audit for brands that want to know where their record stands. If you want yours, start at lasilvercommunications.com.

First, the numbers, because they’ve gotten sharper.

Start with the ownership gap.

• Muck Rack surveyed 1,115 PR pros for its State of PR 2026 report.

• 73% call AI search visibility important to their strategy.

• 29% say no one owns it.

• 39% aren’t measuring it at all.

Everyone sees the shift. Almost nobody has a playbook.

Now the search data. People ask, AI answers, nobody visits your site.

• 68% of U.S. Google searches ended without a click in early 2026, up from 60% in 2024 (SparkToro’sSimilarweb analysis 2026).

Here’s the part that should reorganize your budget.

When Muck Rack’s research team analyzed 25 million links cited by ChatGPT, Claude, and Gemini this spring, 84% were earned media.

Paid and advertorial content? 0.3%. You cannot buy your way into the answer.

The answer is earned.

Earned. That’s our word. This moment belongs to PR, if we show up for it.

One more thing before the system. Most PR teams are meeting this moment with efficiency questions. Draft faster, cut hours, do yesterday’s work more cheaply. Fine, but small. Efficiency improves what already exists. The bigger question is what’s possible now that wasn’t possible before.

For PR, the answer should thrill you. Becoming the source AI cites was impossible two years ago. It’s buildable today, with skills we already have. We’ve spent decades proving our value with metrics nobody trusted. Finally, the game favors our work.

Here’s how.

The core idea

AI doesn’t rank you. It remembers you.

Everything published by you and about you is the record it learns from. Thin record, thin answers. Wrong record, wrong answers. Strong record, and you get recommended by name.

I’ve lived this. Two months ago I asked five AI platforms to describe Vinebox. Most got the basics right. Not one mentioned corporate gifting, the entire B2B strategy we were building. The record was thin exactly where it mattered most, and that gap became the foundation of our go-to-market plan. RECORD is what I built from that lesson.

Authority isn’t built through campaigns. It compounds. The RECORD Framework is a six-layer system for building authority AI can find and cite: Record, Expertise, Corroboration, Owned, Recognition, Documentation. Each layer strengthens the next. For each, here’s the idea and one free thing to do this week.

• R is for Record. Publish. The steady stream of ideas everything else is built on. No output, no record. One great article changes nothing. Fifty decent ones over two years change what AI says about you. This week: ask ChatGPT, Claude, and Perplexity what they know about you. Then pick a publishing schedule you can keep.

• E is for Expertise. Think. AI rewards knowledge, not slogans. A named idea, an original framework, a perspective only you could have. And specificity wins: researchers at Princeton, the Allen Institute for AI, and IIT Delhi found in controlled tests that adding statistics, citations, and quotations improves AI visibility by up to 40%. Vague claims get skipped. This week: write down the one thing you know better than anyone. Put a number in it. Publish it.

• C is for Corroboration. Validate. You can’t declare authority. Third parties do the vouching: journalists, analysts, customers. Machines weight independent proof the way people do, which is why that 84% matters. This is PR’s home turf. This week: ask AI which outlets it cites for your topics. Your media list just changed.

• O is for Owned. Own. Your website is the source of truth AI triangulates back to. And it’s usually the boring content that surfaces. FAQs beat manifestos. This week: write down the ten questions customers actually ask. Answer them plainly on your own site.

• R is for Recognition. Earn. The evidence the record is working: AI citations, media quotes, invitations. This is the layer you watch. It also catches what AI gets wrong, and wrong claims compound. This week: ask AI what your customers would ask. Fix what’s wrong at the source. Recheck monthly, same questions, same tools.

• D is for Documentation. Structure. Authority must be machine-readable. If AI can’t parse it, AI can’t cite it. Sloppy structure means someone else gets credit for your thinking. This week: make your bio identical everywhere you publish. Cheapest fix in the framework.

What RECORD is not

It’s not a rival to the measurement standards this industry already has. RECORD lives upstream: I build what AI learns from, measurement proves whether it moved anything. You need both.

It’s not a certification or a tool. Every action above is free, on purpose. I’m an independent practitioner. Systems scale down. If you’re a solo consultant or a three-person shop, this was built at your size.

And it’s not a crisis tool. AI visibility is what you build before the crisis. When a reporter opens ChatGPT mid-story, the answer comes from your record or from your critics’. Decide which one you’re building now.

Start here

The full framework lives at lasilvercommunications.com/record-framework.html.

If you do one thing after reading this, ask an AI what it knows about you. Five minutes, and it’s the most honest performance review your program has had in years.

The record is the asset. Citations are just the box score. Start building.

If you’re building your record and want the next piece when it lands, subscribe below.

Sources:

• Muck Rack, The State of PR 2026 (survey of 1,115 PR professionals)

• Muck Rack, What Is AI Reading? (May 2026 edition, 25M+ links cited by ChatGPT, Claude, and Gemini)

• SparkToro, analysis of Similarweb clickstream data (2026)

• Adobe Digital Insights, AI-sourced traffic report (Q2 2026)

• Aggarwal et al., GEO: Generative Engine Optimization (Princeton, Allen Institute for AI, IIT Delhi)

PR just crossed the same line.

• On July 2, Visa and more than 30 European banks let AI agents complete real purchases at real merchants: lastminute.com, Frasers, Cleverbridge. Not a demo. AI isn’t just shaping opinions anymore. It’s starting to close sales.

The chain is real. So is the risk of overstating it. Comms builds the front end of it. What we can’t prove yet is the whole thing, one placement traced all the way to one sale. Here’s what we do know: the loop is closing. When it closes, the credit goes to the brands that built a record before it did. That’s the window, right now.

A handful of people have been evangelizing this shift long before this week’s news made it easy to see. Sarah Evans is one of the sharpest voices making the case that PR finally has receipts. She’s right that something is closing. Where I land is on what to do about it before it closes: build the record now, not after.

We’ve all felt this shift coming for a while. A placement that used to matter on its own now only matters if it connects to something bigger. Nobody had a name for that yet. So I built one.

For most of my career, the hardest part of being a publicist wasn’t landing the coverage. It was proving the coverage meant anything. I sat in year-end reviews holding impressions, reach, and coverage volume. Our batting average. Visible. Countable. Comfortable, right up until a CFO’s eyes glazed over, because we both knew those numbers measured what looks good, not what wins.

Buyers don’t start with Google anymore. They ask ChatGPT, Claude, Gemini, Perplexity, whatever ecosystem they’re comfortable using, to find them a brand and tell them it’s safe to trust. The answer isn’t a ranking of who spent the most on visibility. It’s a synthesis of who has the strongest record.

The new scoreboard

Impressions are out. Authority is in. Reach is out. Citations are in. Coverage volume is out. Source credibility is in. Claims are out. Evidence is in.

Everything on the left measures how loud you were. Everything on the right measures whether anyone, human or machine, has a reason to believe you.

Why campaigns stopped compounding

The old model treated authority like something you rent. Run a campaign, get a spike, watch it fade, run another. AI broke that model. It doesn’t remember your campaign. It remembers your record, the body of work attached to your name that’s out there, findable, and verified.

• Here’s the thing. Earned media accounts for 84% of all AI citations across ChatGPT, Claude, and Gemini. Paid content accounts for 0.3%. That number has held steady, within a few points, for a year straight. And when the same article gets picked up by third-party outlets instead of sitting only on a brand’s own site, AI citation rates jump 325%. Not because the writing got better. Because someone else vouched for it.

One great placement with nothing built around it fades. A placement that other sources keep pointing back to compounds.

The system for the new game

I’ve spent 25 years helping companies build credibility, trust, and loyalty via earned media. When the scoreboard changed, most of the industry responded by making more content. That’s not wrong, exactly. It’s just not enough on its own. What was missing was a roadmap: what to build first, what has to corroborate it, what makes it citable instead of just visible. RECORD is that name.

It’s called RECORD. Six layers: Record. Expertise. Corroboration. Owned. Recognition. Documentation. Yes, the first R stands for Record. That’s the whole point.

Skip a layer and the record leaks. Publish constantly with no structure and machines can’t see you. Nail the schema with nothing original to say and all you’ve documented is your own claims.

Next Wednesday I’ll break down all six layers: what each one is, why it earns citations, and the one question to ask about your own brand. Subscribe and it lands in your inbox.

The window

Brands building their record now are setting the patterns that will harden into defaults, the same way the first teams to use on-base percentage got years of advantage before everyone else caught up.

Moneyball was never about baseball. It was about what happens when the measure of value changes. The teams watching the wrong thing lost to the ones who adapted to the new game.

The scoreboard changed. RECORD is how you play the new game.

The full framework lives at lasilvercommunications.com. Start there if you want to know what AI says about you when a buyer asks who to trust in your category.

Build the Record. Become the Source.

____________________________________________________________________________

LeeAnn Silver is the founder of L@Silver Communications, a strategic communications firm helping brands become the source AI cites and buyers trust. The RECORD Framework is the foundation for building that authority.

Answer: The internet’s power structure changed almost overnight. And PR professionals are finally positioned to win in it.

For 15 years, visibility meant SEO, paid ads, social reach, owned content. That was the strategy.

Now AI systems decide what information gets surfaced, summarized, and recommended. And those systems rely on exactly what PR has always operated in: news articles, expert quotes, third-party validation, interviews, reviews, publisher authority, reputation signals across the web.

That shift is accelerating. Here’s why it matters.

Why This Is Happening Right Now

1. AI rewards credibility, not optimization

Traditional SEO optimized for keywords. AI models reward trusted sources and repeated mentions across authoritative publications. If a brand is consistently covered in The New York Times, Forbes, podcasts, analyst reports, Reddit discussions, industry newsletters, AI systems know that brand exists and describe it confidently.

PR creates those signals. That’s always been the job. Now it’s the only job that moves the needle.

2. Earned media became machine-readable authority

PR used to be “soft” compared to performance marketing because attribution was fuzzy. Now it’s not.

Press mentions become training data. Executive quotes become source material. Media narratives shape AI summaries. Reputation compounds across models.

That makes PR suddenly measurable in a new way: AI visibility. 84-85.5% of what AI systems cite comes from earned media. Not from brand websites. Not from paid content.

3. Brand websites matter less than companies realized

AI assistants summarize information without sending traffic to homepages. Brands can’t rely only on blogs, optimized landing pages, or buying clicks anymore.

They need third parties talking about them. That’s classic PR territory. And it’s non-negotiable now.

4. PR people are uniquely cross-functional for this moment

Good PR professionals already know how to:

• Shape narratives

• Simplify complex ideas

• Manage stakeholders

• Work with journalists

• Respond in real time

• Protect reputation

• Position executives as experts

Those skills map directly to the AI communications era. Nobody else has this toolkit built in.

5. The definition of “search” changed

It used to be: “How do I rank #1 on Google?”

Now it’s: “Will AI mention my company at all?”

That’s a communications problem, not a marketing problem. It moved PR from support function to core strategy.

What People Are Getting Wrong About This

Most organizations still think PR is support. They measure it like it’s 2020: coverage counts, reach matters, sentiment scores validate the work.

But that misses what’s really happening.

The shift isn’t that PR got more important. The shift is that the communications expertise PR already has is now directly tied to how companies get discovered.

For the first time in years, storytelling expertise maps to technological distribution power.

That’s why PR professionals are suddenly getting invited into conversations about:

• AI strategy

• Brand discoverability

• Executive positioning

• Search evolution

• Trust and credibility systems

They’re not being invited because someone finally realized PR matters. They’re being invited because PR is the only function that knows how to work in the spaces AI systems are reading from.

Here’s Your Competitive Advantage

If you’re a PR professional reading this, you already know something organizations haven’t figured out yet: visibility isn’t about clicks anymore. It’s about whether AI mentions you when someone asks about your space.

The difference between claimed authority and documented authority is everything.

Right now, most PR teams are still pitching for coverage. Most companies are still measuring reach. Most strategies are built on hope. Hoping visibility compounds. Hoping the right people notice. Hoping earned media eventually reaches AI systems.

That’s backwards. You have to design visibility to compound. You have to create content that works for readers and trains AI models. You have to turn claimed authority into documented authority through strategic, measurable placements.

The teams moving first all do the same four things, in the same order.

They start by understanding how AI actually interprets their brand today, then create content built for both readers and AI systems.

They distribute that authority across the channels that shape modern visibility, so one placement becomes ten discovery moments.
They earn third-party validation through outlets that reach both readers and AI training data, because that is how claimed authority becomes documented authority.

And they track exactly how their brand appears across ChatGPT, Claude, Gemini, and Perplexity. Citation counts, mention frequency, weekly. Not quarterly guessing.

That’s the shift. Not different work. Different structure.

The Real Moment

You’re not having a moment because communications suddenly got fashionable. You’re having a moment because the power structure of the internet shifted and your skillset is the only one built for what comes next.

But here’s the tension: most organizations will approach this like it’s still 2020. They’ll hope visibility compounds. They’ll chase placements instead of building a system. They’ll measure mentions instead of how often they show up in AI answers. They’ll move too slow.

The PR professionals winning right now aren’t just seeing the shift. They’re building systems that turn visibility from hope into design. They’re measuring how often they show up across AI models every week. They’re treating earned media as training data, not just traffic. They’re proving authority instead of just claiming it.

Position yourself as that person. Not for credit. To move your organization 12 months ahead of everyone still hoping visibility happens.

The shift is real. The window is open. The question is whether PR professionals will step into this systematically or whether someone else will try to manage it without that expertise.

Based on what I’m seeing, the best ones already know what’s happening. The next question is whether they’re designing for it or just observing it. I am building for it.

Sources: Muck Rack May 2026 Generative Pulse | 5W Research |

I did something uncomfortable a few weeks ago.

I ran an audit. Asked five major AI platforms (ChatGPT, Claude, Gemini, Google AI Overview and Perplexity) to describe Vinebox.

Most got the basics right. Sommelier-curated. Wine by the glass. 100ml pours. A few had outdated details. One described our hero product that sells out every year.

But here’s what actually stopped me.

Zero platforms mentioned corporate gifting. Not one. Not even a passing reference. And corporate gifting isn’t a side offering. It’s the entire B2B strategy we’re building. In fact, Vinebox corporate gifting grew 151% YOY (More on that in a future post).

That gap, that whitespace, became the foundation of our entire go-to-market plan.

This is the new search. And most brands don’t know they’re invisible in it.

When someone types “best branded corporate wine gifts” into an AI assistant, they’re not getting ten blue links. They’re getting a confident, synthesized answer. A short list. A recommendation. If your brand isn’t in it, you don’t exist in that moment.

AI-assisted research is increasingly where B2B vendor discovery begins. Roughly 50% of buyers are starting their search in AI. Up to 73% are using AI tools somewhere in the research process. The exact stat shifts, but the signal doesn’t. The consideration set is forming before a buyer ever reaches a website.

That’s when it clicked for me. The brands that win from here will be the ones built for zero-click discovery. Found, understood, and recommended by AI before a buyer ever visits their webiste.

I’m calling it Answer-First.
And it changes everything about how I think about brand building, content and communications.

What made this shift real wasn’t just the gut feeling. It was seeing it in black and white. That’s So True. (Gracie Abrams reference). Some things you can’t unsee.

A colleague connected me to Spyglasses.io, a white-labeled AI visibility platform built specifically for PR and marketing teams. They are not the only ones doing this but the reports are clean, shareable, and built for teams that need to make the case internally. It audits how major AI platforms describe your brand. It scores where your content falls out of the AI citation pipeline. It tells you which press placements are actually reaching AI and which ones aren’t doing the work you think they are.

It also tells you if a target site is blocking AI entirely. Wouldn’t you want to know this in advance of any content or pitch you spend time on?

Once I understood that AI doesn’t “know” things in some abstract way, it’s searching, pulling, and ranking content like any other system, everything clicked. Spyglasses is built around that reality.

That’s not just a better dashboard. It’s a fundamentally different way of seeing the problem.

Owned. Earned. Community. All 3. That the formula right now.

I’ve always believed PR should connect to measurable outcomes. This tool gets us so much closer to make that case as the industry shifts.

Here is what I learned:

A 28% share of voice in AI for sommelier-led wine content means nothing if the buyer asking about corporate gifting never hears your name.

The whitespace wasn’t a positioning problem. It was a visibility problem.

Share

And once we saw the gap clearly, the Answer-First GTM almost wrote itself.

Every piece of content mapped back to one question: does this teach an AI platform what Vinebox actually does for corporate buyers?

That’s not traditional PR. That’s Answer-First strategy.

The takeaway?

There’s a new layer now, and the gap between teams who can see it and teams who can’t is growing fast.

If AI doesn’t know what your brand does, specifically for the buyer who’s actively searching, you’re not in the consideration set. And you won’t know you’re missing until you look.

So look.

Ask ChatGPT to describe your company. Ask Perplexity what you’re known for. Ask Gemini where you show up in a category search.

What you find will be clarifying. Maybe uncomfortable.

Either way, building Answer-First isn’t optional. It’s the most important audit your comms team isn’t running yet.

vinebox.com/corporate

Batman said it right back. No hesitation.

Like nothing else in the world mattered more than that moment.

Nothing did.

—

On World Wish Day, April 29th, Sugarwish was invited to Wishes Assemble at Disneyland. The kickoff to Make-A-Wish’s Wish Week.

Not as spectators. As partners.

I didn’t fully understand what that meant until I was standing in it.

Nearly 40 families. Inside a place built for magic. Experiencing something most of us take for granted.

You feel the difference.

This isn’t branding. It’s responsibility.

—

Bob Iger was honored that night with Make-A-Wish’s first-ever Wishmaker Lifetime Achievement Award.

During his time at Disney, they’ve helped grant over 110,000 wishes.

Here’s the number that stuck with me:

A Disney wish is granted every single hour.

Every hour, someone’s life changes.

That’s not a stat. That’s a system. A commitment that never turns off.

—

I met the other partners too.

Founders. Operators. Teams who have built businesses around giving back.

No one was loud about it.

Just a room full of people who understood the assignment.

The best things we build are rarely about us.

—

When Sugarwish was founded, the idea wasn’t just to send gifts.

It was to build something that could give back as part of how it operates. Not later. Not once a year. Every day.

Now, nearly every Make-A-Wish chapter in the country - 49 of them - can send Sugarwish gifts whenever the moment calls for it.

Big or small.

To lift spirits. To celebrate. To acknowledge. To remind someone they’re not alone.

Wish kids. Families. Volunteers. Donors. Medical teams.

Over 110,000 gifts donated.

Over $5 million donated and we’re just getting started.

That’s not a campaign.

That’s what happens when a mission compounds.

—

Happiness isn’t a byproduct of the work. It is the work.

—

Watching a child say “I love you” to Spiderman and hear it said back.

Watching families light up in a place designed for wonder.

Watching what it looks like when a company actually builds around delivering joy.

It all pointed to the same thing:

If you’re building anything, this is the bar.

People don’t remember the product.

They remember how you made them feel.

—

A wish gets granted every hour.

Somewhere, right now, that moment is happening again.

That’s the whole thing.

Sugarwish is proud to be a partner of Make-A-Wish: https://sugarwish.com/us/make-a-wish

Thirteen years of trying to provide timely, relevant and media-sensitive pitches to skeptical, (and lovely!) editors from Fortune to Forbes, and GMA - at outlets I would have been too nervous to cold-call at the start of my career - that a gifting company was worth their readers’ time.

In a media environment that rewards disruption and urgency and a hard news hook, the Sugarwish story is essentially: we help people feel joy. Once learned, the doors keep opening.

Last month, we soft-launched the Gift Genie; an AI-powered proposal wizard built into our WishDesk platform.

It removes every piece of friction between a gift consultant and a sent gift. Personalized messaging. Custom created eCard designs. Proposals built in seconds so the human on the other side of the relationship can focus on the relationship, not the interface.

Zero Input isn’t the innovation. Knowing what to do and how it makes people feel is.

The results: 2x corporate signups versus traditional landing pages. 20+ new accounts per day within a week of launch. 25,860 completed Genie sessions and counting.

My take after thirteen years: the AI stories that will matter over the next decade are not the ones about efficiency. They are the ones about what gets unlocked when you remove friction from a human gesture.

We built an AI that clears the path. The joy is still the point.

If you are thinking about corporate gifting, employee recognition, or how your team is showing up for clients in a world where every outreach feels automated; I am happy to share what we’ve seen work.

#CorporateGifting #AIforGood #EnterpriseRelationships #WomenOwnedBusiness #Sugarwish #GiftGenie #ClientSuccess