Before the First Conversation

By John Rockhold

May 12, 2026

In the age of AI-mediated discovery, vendors earn visibility and credibility before they even know they’re under consideration. At the New York City stop in the Spotlight on the Road tour, a room full of B2B marketing leaders discussed the challenges and opportunities of that uncomfortable reality.

There's a gap most B2B organizations know exists, but haven't fully accepted. They know, intellectually, that their own voice (owned content, campaigns, and crafted messaging) doesn't carry the same weight as what customers, communities, analysts, and experts say about them. They know this. And yet budgets and priorities remain far more focused on the owned voice than on earned authority.

That gap has always created friction but today it creates risk. Because earned voices – experts and customers – are preferred by the “robots” that determine visibility in answer engines such as ChatGPT, Gemini, Copilot, and Claude. Customer reviews. Analyst research. Community discussions. Expert commentary. Owned content has its place, but it’s earned reputation that really powers visibility and credibility.

The stakes are high:

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 are arriving at a vendor's door more informed and more decisive than ever before. Or they're not arriving at all. The “earned” side of the ledger is where preferences form.

The new rules of influence follow from this:

You don't guide the journey, you inherit it.
You win — or lose — before the conversation starts.
The sources AI trusts are the same sources buyers trust. Earn those.

The speakers and agenda at Spotlight on the Road in New York City were assembled to help practitioners understand the challenges and seize the opportunities.

The Great Shift to Answer Engine Optimization

Trevor Pyle, Head of Marketing at Profound, and Neal Behrend, SVP Advisory at Insight Partners, kickstarted the program with a conversation about one of the fastest-moving shifts in B2B marketing: the move from search engine optimization (SEO) to answer engine optimization (AEO).

Profound was built on a simple but unsettling question: As AI becomes the dominant interface for research and discovery, do brands actually know how they're showing up in the answers? Not just whether they appear, but what's being said, if it's accurate, and if the narrative reflects years of deliberate positioning. For most brands, the answer is no.

Trevor made the operational stakes clear. In traditional search, a brand owns the narrative on its own landing page. Answer engines work differently — they editorialize. In Profound's analysis of 50,000 prompts, roughly half of AI-generated responses contain content that goes beyond the question: unsolicited competitor mentions, alternative recommendations, reframed positioning. In one case, a major fitness wearable brand found that 11 percent of AI responses about its products contained inaccurate specifications. For a company doing billions in sales, that's not a data hygiene problem, it's a reputational exposure at scale.

Neal explained how LLMs form their version of the truth. They don't know what's true. They know what's corroborated, as in what appears consistently across multiple independent sources. A brand that has earned consistent, accurate, and multisourced presence isn't just better positioned in search. It's actively shaping what AI systems interpret as reality.

Next, Neal translated this into a practical frame, leveraging what he advises the portfolio companies in his role at Insight Partners. The organizations navigating AEO well start with query strategy: mapping the specific prompts that matter most to their go-to-market motion, whether that's top-of-funnel awareness or simply ensuring an LLM doesn't recommend a competitor in the middle of a seven-figure enterprise deal. They measure first, then act. "You will boil the ocean," Neal said, "and do none of it correctly if you try to do it all."

The Q&A that followed covered Reddit's growing importance as an AI training source (it mirrors human conversation in ways polished brand copy never will), the rising citation power of LinkedIn thought leadership, and how to address inaccurate off-site information. The throughline across all of it: consistency across channels isn't just a brand preference anymore, it's the mechanism through which AI defines what's true about you.

What to Expect From Analysts in the Era of AI

Dan O'Brien, President and COO of The Futurum Group, knows the analyst-vendor relationship from every angle. Dan’s career includes time as a semiconductor analyst, a tech marketing practitioner, the leader of analyst relations at IBM (arguably the world's largest single buyer of analyst research), and now he’s a key leader for one of the most disruptive research firms in the industry.

Futurum is intentionally built to solve the problems Dan experienced on the buying side. It's not just an analyst firm. It's also a media company, an advisory practice, and a benchmarking and lab-testing operation. Futurum is structured to deliver value end-to-end, rather than handing over a PDF and wishing a client luck. When Dan was commissioning research at IBM, he'd spend hundreds of thousands of dollars and months of coordination, only to receive a report with no built-in distribution, no amplification plan, and no clear path to the audiences he was actually trying to reach. The gap between the research and the market impact was enormous.

That model is under mounting pressure, with disruption coming from multiple fronts: seat-based subscriptions are getting squeezed, gated content is invisible to the AI systems shaping buyer discovery, and the pace of market change demands a responsiveness for which traditional research cycles weren't built. A recent example crystallized the moment: a Futurum client asked whether their commissioned research could be delivered not as a PDF, but as an ungated HTML page — openly published, indexed by search engines, and visible to AI. The client understood something many firms haven't yet fully absorbed: Influence lives in the places AI can read.

Dialogue with the audience about if/why/how analysts will remain relevant was frank and fantastic. Dan’s take: In a world flooded with cheap, AI-generated content, the scarce and valuable thing is synthesis — the ability to understand markets and companies deeply, track change in real time, and help buyers cut through noise to find the signal. That function isn't going away. But the format, the business model, and the distribution strategies around it are all in flux. The firms that adapt are the ones that will survive and create new value for their clients.

Amplified Analyst Relations in the Era of AI Influence

Tina Moffett, VP of Corporate Strategy and Development at Analytic Partners, offered one of the most operationally grounded perspectives of the day. It was a practitioner's account of what a sophisticated influence intelligence program looks like in practice.

Analytic Partners is the leader in commercial intelligence, delivering modern marketing mix modeling and ROI measurement for Fortune 500 companies globally. Tina's role spans partnerships, AR, competitive intelligence, and strategic development. She's built win/loss analysis into the center of how Analytic Partners understands its own position in the market.

The program works with deliberate structure. After an RFP process concludes, win or lose, a third party conducts formal interviews with the buyers involved. The interviews uncover:

What shaped the shortlist?
Which sources of information carried the most weight?
What could Analytic Partners have done differently in the process?

The third-party design is intentional: people are more candid when they're not talking directly to the vendor. They get real, fast. And that honesty is exactly the point.

What Analytic Partners has learned is specific and actionable. Their win/loss data has revealed that LLMs and Gartner (in that order) are the top two levers of influence for their buyers. It has uncovered patterns in how competitors approach prospects, which now directly informs business development strategy and competitive positioning. And it has given cross-functional teams — marketing, sales, account management — a shared analytical foundation they didn't have. Before, collaboration existed in the form of disconnected one-off conversations. Now, each team has focused initiatives grounded in what the data actually shows about how buyers decide.

The audience pressed on measurement: How do you quantify the revenue value of influence? Tina was direct — it's something Analytic Partners is working toward, and credibility with the executive leadership team has been built not through a clean ROI formula, but through the clarity and specificity of the insights themselves, and the strategic changes those insights have driven. Tina’s advice for those intrigued by win/loss, but aren’t sure who would “own” it or how to start consideration of it: Talk to the sales team first. Ask them what they know and/or don't know about why deals are won and lost. That question is usually enough to open the door.

The Growth Dilemma: Sales vs. Influence in the AI Era

The Growth Dilemma: A CGO's View on Sales vs. Influence in the AI Era

The conversation with Tommy San George, Global Chief Growth Officer at RAPP and MRM, was insightful, inspiring, lively, and honest. It might’ve redefined raised the bar for what constitutes a “fireside chat.”

Tommy’s central argument: The era of storytelling divorced from evidence is ending. Buyers are shifting their expectations from narrative to certainty. From "this is what we can do" to "this is what we've done, and here's how you can experience it." Slide decks, credentials presentations, and polished proposals are losing ground to hands-on demos, tangible products, and proof. For agencies in particular, that's a forcing function for genuine transformation.

Tommy put a specific goal on the table for his own team: zero slides shown to a client within 12 months. The point isn't aesthetic, it's structural. If you strip away the presentation layer, you have to replace it with something real. And for a CRM and customer experience agency that has just gone through Omnicom's acquisition of IPG to emerge as a newly combined global network, the pressure to become something genuinely differentiated is acute. "Risk aversion," he said, "is just as good as dying as an agency."

Tommy was equally sharp on the RFP process, which he argued is long overdue for reinvention. An RFP is, at its core, a series of prompts soliciting answers from a vendor. Treating it as a static document exchange — heaving a document of questions at a vendor who heaves back AI-generated answers — is a charade everyone recognizes as such. The better model is a more dynamic, conversational, experience-driven interaction that builds credibility in real time rather than asserts it on paper.

What gives him hope is the same thing that makes the moment hard: the pressure is clarifying. Teams that recognize this as a genuine inflection point — one shot to build something real and lasting — tend to find it energizing rather than paralyzing. The goal of growth, at its best, is to make itself less necessary. Deliver enough genuine, differentiated value, and buyers come to you. That's not idealism. It's a strategic objective.

AI Has Changed Everything, Except What Your Customers Want

AI is Changing Everything, Except What your Customers Want

Nate Elliott, Principal Analyst at EMARKETER, closed the program with exactly what it needed at that point: rigorous data and corrections to the assumptions many of us carry.

Nate was direct. AI usage is growing at a pace that is genuinely unprecedented. EMARKETER's forecast shows weekly genAI usage among U.S. internet users climbing from 1 percent in 2022 to 13 percent in 2023, 21 percent in 2024, 30 percent in 2025, and a projected 40 percent by the end of 2026. But B2B marketing pros, for whom AI is central to daily work, can have a distorted picture of where buyers actually are, unintentionally so. Nate’s three questions helped the audience reset.

The first: How many of your customers actually use AI? The aggregate numbers are striking, but the variation by generation and context is significant. Gen Z leads usage. Baby Boomers plateau at around one quarter. And Gen Alpha — average age six or seven — is the least frequent user. Why? Well, naturally, most of them haven't learned to read yet. The point wasn’t that AI doesn't matter. It was that assuming AI is automatically the most important channel for your specific buyer is a hypothesis worth testing before you organize your strategy around it.

The second: Why do your customers use AI? The answer, consistently, is information search. People use AI for the same primary reason they use the internet — to find answers, faster. And critically, human motivations don't change at the pace of platforms and features. What changes is the tool. What stays constant is the underlying need for authoritative, synthesized, specific responses to real questions. Understanding that distinction matters because it shapes strategy: You're not competing for AI attention in the abstract, you're competing to be the right answer to a specific question your buyer is already asking.

The third: How does AI fit into your existing strategies, rather than replace them? This is where the data is most grounding. Google AI Overviews are consumed by more than two and a half times the number of people who actively use ChatGPT. Even the heaviest AI users aren't searching less — they're adding AI to their existing research behaviors. And when buyers receive an AI-generated recommendation, the most common next step is to go do their own research anyway. AI isn't replacing analyst research, peer reviews, search, or sales conversations. It's adding a powerful new layer to all of them. The brands that navigate this well treat it as an additional earned channel to optimize, not a wholesale reinvention of everything that came before.

Closing Thoughts

Our half-day in New York City had it all: energy, insight, skepticism, optimism, urgency, tension, and hope. There was a sense that the window for strategic debate is narrowing and the window for building the actual systems is opening.

What unified the sessions was a single pattern: The teams navigating this moment well aren't running campaigns and hoping. They're running systems and learning.

Trevor and Neal named the measurement imperative: query strategy before tactics, visibility before anything else.
Dan named the synthesis imperative, and the delivery model that needs to evolve around it.
Tina showed what an influence intelligence system actually looks like in practice: structured, cross-functional, and grounded in what buyers tell a neutral third party when no one's selling to them.
Tommy named the experience imperative: the shift from storytelling to proof that is forcing agencies and vendors alike to become something real.
Nate gave everyone permission to slow down and verify their assumptions before sprinting.

My challenge to the room at the start of the day was simple: Be more than a result. Be the answer. The brands that win in the AI era won't just appear in AI-generated responses. They'll be the ones the response is 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. And earning it requires a system.