Earned Authority Over Owned Narrative

By John Rockhold

May 27, 2026

What vendors say, via owned surfaces and content, has its merit. But in the new era of AI-mediated discovery, what experts and customers say – earned authority – is far more powerful in shaping whether buyers find and choose vendors. At the Seattle stop on the Spotlight on the Road tour, a room full of B2B marketing and AR leaders explored what it takes to earn authority.

Ask ChatGPT, Gemini, Claude, etc., a question about your market, and pay close attention to what happens. The “robots” that engineer the answers don’t guess. They don’t generate opinions from nothing. They turn to the sources that humans trust: what analysts articulate, what customers say, and what communities banter about and conclude. The robots, in other words, turn to humans to produce the best answers for humans.

For B2B marketers, this signal is clarifying and its implication is substantial. At a time when AI is the primary mediator between a buyer's question and your brand's answer, it’s crucial to understand that the sources AI “trusts” are the sources that determine your visibility. And those sources — analyst research, peer reviews, community discussions, expert commentary — are earned, not owned. Most organizations haven't fully reorganized around that reality. Budgets and systems still lean heavily on owned content: branded campaigns, crafted messaging, and assets a vendor controls start to finish. None of that is wrong. But it's increasingly insufficient on its own, in a world where …

94 percent of B2B buyers now leverage generative AI somewhere in their buying journey (Forrester, Buyers' Journey Survey, 2025).
80 percent of buyers ultimately choose the vendor they contact first (6sense, 2025 B2B Buyer Experience Report).

Buyers arrive at your door more informed and more decisive than ever before. Or they don't arrive at all.

The new rules of influence follow from this:

You've lost control of the buyer journey. You don't guide it — you inherit it.
You're winning or losing before the competition starts or your voice can be heard..
The sources AI trusts are the same sources buyers trust. Earn those.

The speakers assembled for Spotlight on the Road in Seattle brought inspiration, wit, and experience to help B2B practitioners navigate these uncertain and exciting times.

From Activity Theater to Outcomes

Influence Isn't Theater. It's Revenue Impact.

Lucas Welch has a term for what most B2B influence programs actually are: activity theater. The briefings completed, the events attended, the customer stories produced — all of it well-intentioned, and almost none of it connected to a shared outcome the business actually reviews. Lucas oversees communications, brand, and demand generation at Highspot. That’s a combination of disciplines that requires a certain amount of creativity to hold together coherently, and creativity is something Lucas has in droves. (He's a former actor and rapper. The evidence is out there.)

His central argument was that most marketing and AR programs are still running in silos: separate teams, separate strategies, separate measures of success. And when AI comes along and condenses all of that work into two sentences, whatever signal each program was trying to send gets lost. The buyer sees a fragmented or inconsistent picture, and trust erodes before the conversation begins.

The programs Lucas named — analyst relations, customer advocacy, events, content — aren't the problem individually. The problem is that they're rarely designed to work together toward a single, cohesive story. His challenge to the room was direct: if those teams aren't connected, stop everything else and fix that first. Nothing can compound the way it should until they are.

On the question of proving impact, Lucas was concrete. At Highspot, he embedded two questions into win/loss surveys: did you speak with an analyst, and if so, did it influence your decision? The result is roughly a 70 percent win rate on deals where an analyst was involved. He also tracks marketing's contribution to closed-won revenue: at Highspot, $1 into marketing returns $3. Those are the metrics that earn a seat at the table and protect the budget when pressure hits.

Lucas closed with a point about making work findable. The era of the form-gated asset is over. If content can't be indexed, it doesn't exist for the buyers who need to find it — or for the AI mediating their search. "Our job is not just to put on a great show," he said. "It's to change the trajectory of our businesses."

Building Trust Everywhere

Trust at Every Layer: Evolved AR in the AGE of AI Visibility

Abbey Fischer, Head of Analyst Relations at Qualtrics, started her career at Spotlight as a client partner before going in-house — first at Amazon, then at Qualtrics. In a fireside conversation, she reflected on how the AR function has changed, and where it's heading.

The efficiency gains from AI are real. Briefing transcripts that once required hours of careful note-taking — typing notes, Abbey noted, used to be about 80 percent of the job — can now be recorded, uploaded to a model, and debriefed in a fraction of the time. But she was quick to draw the line between what AI has changed and what it hasn't. The relationships are still irreplaceable. The ability to pick up the phone and have the kind of candid, off-the-record conversation that only comes from trust built over time — that's what AR professionals are actually good at, and it's not going anywhere. Relations, after all, is word number two in the title.

What has genuinely changed is the aperture of the function. AR used to be organized almost entirely around the big three analyst firms and their evaluative research. Abbey described a moment early in her time at Qualtrics when the SEO team approached her, not about evaluation reports, but about G2 and Gartner Peer Insights. The SEO experts wanted to understand those platforms because they had become top sources of off-site generative engine optimization. She'd never been approached that way before.

She's since taken G2 under her remit. When she pulled up the profile in a cross-functional meeting, colleagues were stunned to see outdated branding and three-year-old assets. Buyers were finding that. So was AI. Her broader point: the era of the big three as the only answer is over. G2, Futurum, Constellation, and other emerging voices are becoming more important. AR teams that aren't paying attention to the full landscape are leaving influence on the table.

For the next generation of AR professionals, Abbey said she's looking for people who see the broader vision — who understand that the function's impact on pipeline can and should be measured, that LLMs are a new form of measurement for the program, and that the job is no longer the same old same old.

The Precision Advocacy Imperative

Liz Richardson and Deena Zenyk, Co-Founders of Captivate Collective (now part of Spotlight), have spent more than twenty years in customer advocacy. Their session in Seattle was both a history of the function and an argument for why this particular moment demands something different from it.

The arc of customer advocacy in B2B has run through three phases. In the first, it was about one-to-one sales acceleration: getting the right customer on the phone at the right moment in a deal. With the rise of SaaS came the second phase, in which retention and expansion required continuous proof of value — and scaled advocacy programs emerged to meet that need. Now we're in the third phase, where the question isn't just whether your customers are talking about you. It's whether what they're saying is shaping what the machines say about you.

The result of everyone investing in customer content at scale is a cacophony. There's so much of it that it's harder than ever to break through — and easier than ever for AI to flatten it into noise. The good news, Liz and Deena argued, is that the organizations that have been playing the long game — genuinely investing in customer relationships, building real advocacy programs, earning authentic voices — now have something that can't be quickly replicated. Coding isn't a moat anymore. A great marketing campaign isn't a moat. But a pool of genuine advocates who believe in you and can speak credibly in the channels AI is listening to? That's a moat.

Their concept of precision advocacy is a response to the volume-first approach that defined the last era. Rather than maximizing review counts, it starts with understanding what narrative is forming in the AI tools your buyers actually use, which sources those tools are pulling from, and where the gaps are. From there, the work is surgical: identifying which advocates have the right voice, expertise, and channel presence to address specific gaps in that narrative — and deploying them with intent.

Their warnings were equally direct. Cycling through your customer base for reviews is a transaction that runs out. Reddit is notoriously hostile to corporate agendas. If you send advocates there on a mission without a strategy, it will go badly. And content volume without authenticity won't break through. Buyers are learning to discount manufactured trust signals, and that speed of discernment is only increasing.

AI Is Shrinking the Window to Shape B2B Buying Decisions

Kelsey Voss is a Principal Analyst at EMARKETER, and she covers the hottest of hot topics in B2B: answer engine optimization, AI visibility, and content marketing. Kelsey closed the program with data that sharpened the urgency of everything that had come before.

The central argument: AI is shrinking the window to shape B2B buying decisions, and most brands aren't ready. According to Google and National Research Group survey data, 35 percent of B2B buyers use AI during the discovery phase — identifying which vendors exist — and 43 percent use it during the consideration phase. Kelsey noted that the stat showing 77 percent of B2B buying journeys complete within 12 weeks is a little misleading. The point isn't that the journey is short, it's that buyers are doing enormous amounts of research before they ever contact a vendor. By the time they reach out, they've largely already decided. And 58 percent of buyers switched vendors in the prior six months, often because what they experienced after engaging a vendor didn't match the expectations formed during their AI-assisted research.

To close that gap, Kelsey explained EEAT: Google's principles of Experience, Expertise, Authoritativeness, and Trustworthiness, and their growing influence on what AI-driven systems choose to surface and cite. The human layer underneath all of it has never been more important. Increasingly, SEO professionals understand this too: nearly 60 percent say they plan to invest more in human-authored content with AI support over the next 12 months. The signal isn't that SEO is dead. It's that generative engine optimization builds on the same foundation — and the human expertise and authentic voices that underpin it are what the machines are ultimately trying to surface.

She pointed to data that puts the business case in sharp relief. A Bain & Company survey from March 2026 found that B2B companies with a strong, consistently understood value proposition grew revenue 19 percent compared to 12 percent for those without one. Only 4 percent of B2B executives said their organization actually had a strong, consistently understood value proposition. That gap is significant, and AI is making it visible in ways it wasn't before.

Kelsey’s core takeaway was about consistency: every piece of public-facing content, every claim a sales rep makes, every customer success interaction — it all needs to reflect the same story. When it doesn't, buyers who arrive with AI-formed expectations hit friction. And when they hit friction, they switch. The deal cycle, she noted, is 31 percent faster when the buying experience is excellent rather than just good (Denso, Superpowers Index, November 2025). The difference between excellent and good is consistency.

Closing Thoughts

What made Seattle work was the mix in the room. As Liz noted early in her session, it's rare to have AR professionals, customer advocacy practitioners, and demand gen and brand leaders all gathered together — typically these disciplines don't share a room. But they're all working on the same underlying problem from different directions. That convergence is exactly what the Spotlight on the Road tour is designed to facilitate.

My challenge at the start of the day was simple: don't think about how to be a (search) result. Think about how to be an (LLM’s) answer. The brands that win in the AI era won't just surface in generated responses — they'll be the ones those responses are built around, because analysts cover them, customers trust them, communities reference them, and the market has decided they're worth knowing. That kind of influence isn't manufactured. It's earned.

Each speaker built on that from a different direction:

Lucas made the case that AR, customer advocacy, and content need to operate as one integrated system. And that the integration only matters if it's tied to outcomes the business actually measures.
Abbey showed what an expanding AR remit looks like in practice: one that stretches from evaluative research into peer review strategy, AI visibility, and the full landscape of emerging analyst voices.
Liz and Deena argued that the long game of building genuine customer advocacy is now paying its most significant dividend — and that precision, not volume, is what the moment requires.
Kelsey grounded it all in data: the window to shape buyer perception is narrowing, the stakes of inconsistency have never been higher, and the human layer underneath all of it has never mattered more.