Why editorial coverage shapes AI recommendations…

Forever and a day, earned media was viewed as a non-paid and powerful, credible layer in the brand marketer toolbox. It served as a highly intrusive form of communication that already nailed the attention of its audience. Journalism offers a respected third-party voice that intrinsically administers trust and belief in an environment where consumers increasingly tune out self-serving selling messages.

Now the brand communication game plan is evolving as the rapidly escalating use of agentic AI operates as a source of direct guidance and recommendations on purchase decisions. LLMs learn and then report after crawling sources used to inform their analysis.

Editorial media is performing a dual role as a third-party validation of claims made by brands, while also serving as a supplier of important information that teach LLMs. The next time a consumer asks an AI chatbot for a recommendation on pet food, nutritional beverages, or electric vehicles, the advice they receive will be subtly shaped by the journalism the brand PR team has secured.

Editorial coverage is no longer just about influencing brand perceptions. It now plays a foundational role in training and informing the AI models that millions are relying on for trusted guidance.

The rise of Agentic AI and its insatiable need for trustworthy data

AI systems —like ChatGPT, Perplexity, Claude, or Pi—are operating as autonomous agents and advisors that provide people with personalized recommendations, context, and insights. These systems rank and recommend based on patterns of trustworthiness they consume through crawlers. These unseen digital knowledge vacuums do this by prioritizing sources considered authoritative including consumer, business and trade media.

Key to managing the agentic AI voice is knowing that LLMs perform their ranking and recommending through data they encounter in ‘patterns of trustworthiness’. LLMs train on vast datasets that include publicly available text across journalism, Wikipedia, Reddit, and the open web. The models are continuously updated through tech called ‘Reinforcement Learning from Human Feedback’. News stories, product reviews, and media analysis all contribute to that learning loop.

Are you managing the loop?

Here are some examples of trusted teachers in LLM training sets:

• Editorial media publishers and broadcasters like CNN, Bloomberg, NYT, Reuters, The Guardian
• Trade publications (via open-access syndication or licensed content)
• Company press releases published by high-authority domains (PR Newswire, BusinessWire, etc.)  — now elevated in their importance

The influence of PR multiplies from people to platforms

Coverage by respected editorial outlets delivers not only consumer-facing credibility but input data that engages AI-generated opinions and summaries. Unlike social content or ads, published editorial stories live in perpetuity across syndicated news wires, re-aggregated media platforms, and crawled databases.

A well-placed story in Food Dive or Forbes can ripple across multiple LLMs as they use that content to better understand product categories and brand claims.

“If you’re not appearing in credible editorial sources, there’s a good chance the next AI assistant won’t know much about you—or worse, it may learn something inaccurate.” — Noah Giansiracusa, author of “How Algorithms Create and Prevent Fake News”

Practical implications for brands

In addition to analysis of the levels of influence on brand reputation and belief, and the legacy data collection around non-paid impressions, Public Relations now stands at the front gate of managing GEO (Generative Engine Optimization) outcomes.

Trade coverage isn’t just about reaching trade partners.

Business media isn’t just about informing investors.

Consumer media isn’t only about building awareness of product benefits.

All of these are also working in tandem to bring your brand background to AI crawlers. This can be organized, optimized and delivered with intention and best practices towards assuring agentic AI recommendations are correctly, accurately, fully telling your brand and product story.

New goals for PR

Not just about reach or impressions – it now includes visibility in trusted training data ecosystems. GEO best practices will put greater emphasis on the value and importance of —

• Trade media coverage as a resource for more, in-depth analysis thorough reports on new product innovations, key messaging, positioning and other important information that vertical media typically report on.
• Thought leadership articles and by-lined op-eds often published in the same trade channels. These stories convey added texture and leadership for your brand and its role in culture, innovation, research and social issues.
• Data-backed press releases. Releases start out as invitations to a story. Now their importance advances as a device for informing AI advisers. This means press releases should go on the wires regardless of whether the story topic warrants broad distribution, because again, crawlers are consuming the output of credible news platforms like BusinessWire and PR Newswire. Note: LLMs like facts, reports, charts and other data that gives your story context and proof.

Audit and optimize for “AI crawl-ability”

An entire new area of best practices is surfacing to better assure earned media is optimal in this environment of influencing agentic learning:

• Accurate brand/product naming
• Structured context (quotes, data, headlines)
• Syndication and backlinks to brand content

Enabling alongside an ecosystem of owned and aligned content

Same rules apply to owned and social channels with the same considerations in how stories are told and what information is presented in a supporting, confirming role. Strengthen the signal by pairing PR wins with:

• Company blogs optimized for GEO (Generative Engine Optimization)
• Expert-authored LinkedIn content
• Wikipedia/Google Knowledge Panel upkeep

Here’s an example of how this might play out

1. A pet food brand lands an article in Pet Age about ingredient sourcing.
2. The article is crawled by Perplexity and Anthropic’s Claude.
3. Six months later, those same AI systems cite the article when users ask about “sustainable dog food.”
4. Result: organic traffic has moved from Google to conversational AI, driving new customer recommendations from a trusted voice.

The significance of this shift brings new meaning and value to the importance of earned media outreach campaigns, alongside efforts to assess, manage and monitor what LLMs think they know about your brand and business (more on this vital topic in our next issue of ETR). A third party is now showing up between your brand and the consumer to provide trusted guidance, without consumers ever visiting your web site.

You can immediately visualize the importance of managing how your brand shows up in agentic AI recommendations — and the ability of your earned media strategies to help influence those assessments.

If this story raises questions about how best to optimize and adjust your strategies to stay relevant in the agentic AI game of influence, use the link below to ask questions.

Looking for more food for thought? Subscribe to the Emerging Trends Report.

Bob Wheatley is the CEO of Chicago-based Emergent. Traditional brand marketing often sidesteps more human qualities that can help consumers form an emotional bond. Yet brands yearn for authentic engagement, trust and a lasting relationship with their customers. For more information, contact Bob@Emergent-Comm.com and follow on Twitter @BobWheatley.

What does AI believe, say, recommend about your brand and business?

What happens when agentic AI steps in as the authoritative source of information and credible recommendations about brands, products, claims, technology, formulations, ingredient sourcing and emerging health/wellness issues – bypassing any need to visit your website at the start of an exploratory journey? Think for a moment about the implications of a super well-informed digital advisor making trusted recommendations to consumers based on its own assessment of your brand and product strengths vs. competitive choices. We’re standing at the edge of nothing less than a transformative shift in how people and trade partners get information, find solutions and make decisions.

To succeed in the era of LLMs, brands must now optimize for AI agents—not just customers.

• More than 50% of Internet traffic is now populated by non-humans — AI crawlers operating out of sight on a subterranean highway of digital data collection, scouring every available channel to train and inform LLMs so they can be instantly summoned to dispense informed recommendations.
• Unlike any previous technology generation such as Google search, AI speaks to its users in an authoritative, empathetic voice while supplying answers and a point of view. Yes, this is a machine, but we say it again — with solutions and recommendations — from a source that isn’t your brand saying it. A smart source that over time will get more and more familiar with customer needs, aspirations and desires. It never forgets, never sleeps and remembers every detail about preferences, concerns and prior conversations.

Will consumers and trade partners make decisions, form impressions based on what they read or hear from an AI guide? Likely. Could this become reflexive and embedded behavior? Yes.

Managing agentic AI in the battle for trust and influence

What does AI know and believe about your brand and product line?

Your company?

Your technology expertise?

What will it say about your formulations and claims?

What will it recommend?

Is the narrative accurate?

Is your brand story presented in the best light possible?

What portion of your key messaging came through?

What’s missing?

Will your customers trust this on-tap source and rely on it?

This is not a phase, a passing fad or a novelty. It is business infrastructure, and it’s about to change everything including your strategy, marketing and comms game plan.

Over the past 30 years, the phrase “Google it” emerged with the revolutionary idea that any answer was just a web inquiry away. Over the past few years we’re also hearing, “Ask your AI.” Google search links still require effort and time to investigate, collect, digest and assess.

This week I requested AI help to find a hotel near the University campus where my daughter will attend this fall as we prepared to join her freshman orientation. In seconds I got a list of options, then a filter of those choices based on AI’s assessment of the best deal, location and quality plus an offer to assist with booking. Follow-up questions for clarity were answered in seconds with refinements. The process was easy, painless, quick, convenient and presented in an authoritative and helpful voice.

• I went with it. Done and done. For a travel and hospitality brand, or any other business really, you have to be concerned about the presence of a machine that doesn’t behave like a machine gaining a recurring trusted role as arbiter and sage of risk-free choice.

All of this potentially happens without anyone first visiting your web site or social channels. This begs the question of how to control and enable your brand narrative — when an unseen army of AI bots are hoovering everything available, good or bad, right or wrong to formulate its own assessment of your brand and business from what it collects.

An AI mandated moment of truth

The AI agent era flips the script—you don’t search for information – that information comes to you through an intelligent liaison that knows what stakeholders want.

We’ve reported previously on the pervasive levels of uncertainty and anxiety consumers are facing right now. What do they want above all? The return of certainty and a sense of control. Can agentic AI offer a resurgence of perceived control? It’s quite possible that this pipeline from mountains of aggregated data digested and served up in conversational recommendation form could become a trusted partner — when everything else often appears to be self-serving, biased and often requires burning mental calories to unearth and evaluate.

New platforms designed to monitor, gain intel and help inform LLM crawlers

If you want to know the details of what LLMs believe about your brand, new tools have emerged to help bring detailed understanding of what AI agents think they know about your business. From there you’re in a better position to design content that is AI crawler friendly. This will help assure your brand, claims and formulation story is coming across correctly, supplemented with monitoring to see how that plays out in real time.

Out of fear of losing control over brand IP, some businesses may be tempted to erect digital barriers to bot crawling access. However, that also risks ceding future control and diluting the ability to manage a conversation that’s gaining increasing traction among consumers who are going to get more and more comfortable with seeking out AI sponsored advice.

Better to manage this than leave it alone and hope your brand is properly presented, recommended and the story being told is accurate and complete.

With that in mind, LLM engines prioritize the following brand content characteristics:

• Language. LLMs like to navigate rich, conversational text such as blog posts and newsletters, more so than webinars or embedded images.
• Agentic-optimized structure. Prioritized lists, definitions, and guides make it easier for LLMs to synthesize and summarize information.
• Clean, scrapable web sites. Accurate, fully indexed web sites are better than keyword optimization or navigating older legacy pages designed to elevate site authority.
• Third-party earned authority. Outside publications, external media and expert commentary can help confirm, verify and validate your brand story and value proposition.
• Deep customer conversations away from your site. The presence of external reviews and forums generates authoritative mentions, backlinks, and credibility.

Elevating importance of earned (editorial) media to credibility and trust

Whatever your brand states and claims remains an assertion – of what you want people to believe about your brand, business standards, unique strengths and added value. Running alongside the advice of agentic AI, and also a part of its assessment structure, is the increasing importance of third-party credible endorsement.

Journalism and reporting are third party evaluation of what you claim from a respected source. Earned media will play an increasingly important role in the agentic eco-system, operating in two directions as an added authority in what LLMs process, and as an independent voice that validates and verifies what you want stakeholders to believe. PR has always been important resource for credible third-party evaluation. Now it has added gravitas in the system of informing LLMs and also providing a trusted resource consumers also look to for affirmation.

The one-two punch of LLM crawler optimization and earned media outreach forms a formidable strategic foundation for brand storytelling in the era of AI advisory.

Next gen strategies to manage an LLM informed future

LLMs can circumvent brands, cutting them out of directing the consideration process before they even know a consumer is investigating. Thus, why adapting current strategies to engage LLM crawlers can build a virtuous, holistic solution. Optimized web content, earned, and social media leads to better AI references, greater trust and engagement, and prioritization in LLM assessments.

Considerations on the AI crawler journey

It’s time to systematically evaluate how LLMs will impact customer consideration, and how that will change go-to-market strategies. Engaging with new AI crawler intel, analysis and impact tools can help build a fluid map of the customer buying journey alongside an AI-engaged buyer journey, and how brands will show up in AI-powered search engines. While LLMs and AI-powered search are constructed on similar inputs, they can produce radically different results and outcomes. An LLM scorecard can help your brand identify the areas of greatest need and inform the tools designed to secure the optimal brand story and recommendation.

Adapting your strategy to engage LLMs will create a virtuous eco-system: Strong internal, earned, and social content will lead to more AI references, greater trust and engagement, and further prioritization in LLM queries.

If you’re wondering how these developments will impact your business and what’s the best path to navigate an agentic AI informed future, use the link below to ask questions and start an informal conversation.

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