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Events
MARCH 23, 2026

Salon Dinner: Cambridge

Join 3BL for a salon dinner the evening of May 5 during the Reuters Responsible Business USA summit in Cambridge.


3BL is hosting a salon dinner in Cambridge during the Reuters Responsible Business USA summit. 

Join us the evening of May 5 at 6 pm ET for community, cocktails and curated cuisine from Row 34, the high-energy, neighborhood-focused seafood restaurant and oyster bar built on a deep connection to the ocean and the people who harvest from it.

Registration for this event has closed.

Business leaders from Greater Boston and those in town for RBUSA are welcome to join this informal gathering for networking and inspiration from peers in similar corporate roles. No formal agenda, just a fun social event. 

Our salon dinner will take place at Row 34, located just steps from the Boston Marriott Cambridge. Born out of and named after the 34th row of oysters in Duxbury Bay, this acclaimed New England eatery was founded by Chef Jeremy Sewall and features the freshest fish up and down the coast. 

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Product Updates
MARCH 19, 2026

3BL LLM Visibility: AI Content Indexing & Discovery


llm.txt is a lightweight Markdown file that helps AI systems understand, prioritize, and surface your content accurately.

What is llm.txt?

A sitemap built for the AI era.

Traditional sitemaps work fine for search engines. But AI agents like ChatGPT, Perplexity, and Claude prefer clean, structured text — not tag-heavy HTML.

llm.txt tells AI systems:

  • What your organization does
  • Which content is most important
  • Where to find it

How it works for your content:

When a stakeholder asks an AI assistant about your sustainability commitments or community impact, that AI pulls from available sources. llm.txt ensures your published content is legible, authoritative, and prioritized.

Every story published now becomes more legible to AI systems increasingly mediating how stakeholders discover and evaluate brands. That compounds over time.

llm.txt is now live for all client content. Reach out to your Client Success Manager for more information.

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people on a Zoom call discussing AI visibility and AI search results
(Image: Getty Images/Unsplash)
Leadership Perspectives
MARCH 17, 2026

“AI Can’t Quote Coverage You Never Generated.”

Brands have an AI problem, but most of them don't know it yet. The brands winning visibility in AI search are the ones with the deepest independent coverage and the most consistent third-party validation built over time.

Charlie Wilkie
Charlie Wilkie Chief Executive Officer

A comms leader I work with lost a third of her team about two years ago.

The CMO made a compelling case: Advertising had measurable return on ad spend (ROAS). Content marketing had attribution, earned media had neither. It wasn’t an unreasonable argument. The metrics said what they said. Her headcount went to marketing.

We ran an AI visibility audit earlier this month for them. The brand was barely present. Old coverage, a critical piece from 2021, a competitor comparison the marketing team had never seen. Everyone who reviewed the audit was surprised during our Teams call.

She looked into her camera — at nobody and everybody at once — and said, almost matter-of-factly: “AI can’t quote coverage we never generated.”

She’s right, and most boardrooms haven’t properly sat with what that means yet.

Ask an AI assistant about your company right now. What probably comes back is a patchwork: a review site, an old article, a forum thread from 2022. Assembled with complete confidence. Presented as fact. Most people reading it will believe it.

Two peer-reviewed studies from 2025 tested this directly. Citations in AI responses increase user trust, even when those citations are completely wrong. Researchers found that responses with random, irrelevant citations were still rated more trustworthy than responses with no citations at all. Most participants never checked. Among those who did and found the citations were nonsense, trust dropped, but only then.

The default, for most people, is to believe. AI will describe your brand with complete confidence whether you’ve earned that description or not.

Generative AI systems don’t surface whoever publishes the most. They cite whoever is most corroborated — consistently — across credible third-party sources. AirOps analysed over 21,000 brand mentions across ChatGPT, Claude, and Perplexity, and 85% of the citations came from third-party sources. Brands were 6.5 times more likely to be cited through earned media than through anything they published themselves.

The University of Toronto studied citation patterns across industries — consumer electronics, automotive, software. The answer was the same everywhere. Earned media dominated. Owned content barely registered. The brands publishing the most weren’t the ones being cited.
SEO got you here. It won’t get you there.

Traditional search rewarded whoever ranked highest for the right keywords. AI rewards whoever has built the deepest, most consistent trail of independent validation. Those aren’t the same thing. The rules changed while most brands were still perfecting the old playbook.

The standard response is to publish more. Post more. Build the content engine.

The data doesn’t support it. Ahrefs looked at approximately 14 billion web pages and found that 96.55% receive zero organic traffic from Google. Zero. HubSpot, probably the most sophisticated content operation in the world, watched its blog traffic fall 75% in two years as AI Overviews began answering the questions their content was written to rank for.

If the content marketing playbook isn’t working for the people who wrote it, it isn’t working.

AI systems are trained on what already exists. Right now, they’re learning which brands are credible, which sources to trust, which names to cite. Those patterns will be hard to shift once they’re set. Seer Interactive tracked 3,119 search queries across 42 organisations over 15 months. Brands cited in AI Overviews earned 35% more organic clicks than those not cited. Brands not cited saw click-through rates fall 65% year on year.

Gartner predicts PR and earned media budgets will double by 2027 as organisations work out that AI visibility is built through independent credibility, not owned content volume. I run a company that benefits if you believe that. The data is worth looking at anyway. The smarter brands already have.
None of this is an argument for abandoning owned channels. Your blog, your social presence, your press releases — these are raw material. They are not the credibility. They are inputs into a system where what others say about you matters far more than what you say about yourself.

The brands winning in AI search aren’t the ones with the biggest content teams. They’re the ones with the deepest independent coverage, the most consistent third-party validation, and the richest citation trails built over time.

It’s what good comms people have been doing all along.

The comms leader on that call saw it immediately. She’d spent years making the case for coverage that couldn’t be tracked, relationships that didn’t show up in dashboards, credibility that compounded slowly and invisibly. She lost that argument once already.

The metrics have caught up. Whether the boardroom has is another question.

Image: Getty Images/Unsplash

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Product Updates
MARCH 11, 2026

3BL Audience Data: Professional, Demographic, and Geographic Insights


This guide provides a comprehensive overview of the Audience Analytics Dashboard, helping communications teams better understand how audiences engage with their content.

Audience Analytics Perspectives

The Audience Analytics Dashboard is organized across three primary views that mirror the structure of the analytics interface. Each perspective highlights a different dimension of audience engagement, helping teams better understand who is interacting with their content and where that engagement is coming from.

Measurement and Analysis Approach

Audience insights are built on a combination of first-party engagement signals and trusted distribution data across the network. This information is regularly reviewed and maintained to ensure accuracy and consistency, providing a reliable foundation for understanding how audiences engage with your content.

Turning Insights into Strategy

Audience analytics are most valuable when they inform how teams plan, publish, and evaluate their work.

Patterns in engagement can help communications teams refine editorial strategies, identify emerging topics of interest, and better understand the communities interacting with their content. Over time, these signals provide a clearer picture of how messaging resonates across different audiences.

Used consistently, these insights help teams move beyond simple performance metrics toward a deeper understanding of how their content reaches and engages the audiences that matter most.


Interested in shaping what comes next? We’re exploring new ideas around AI-powered insights and would love to hear how your team is thinking about analytics, intelligence, and future of communications strategy.

Let’s chat.

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