Buyers across every generation are using AI engines to evaluate your brand and its competitors—and they’d rather lurk in your marketing and sales funnels undetected than talk to your team. By the time they reveal themselves, their decision has already been made.

So: How do you engage with someone who doesn’t want to engage with you?

Picture this. A 39-year-old marketing director (we’ll call her Zoey) on the verge of a promotion to CMO at a multibillion dollar financial institution is evaluating CRMs to power targeted personalization campaigns. The CRM must span every major line of business—consumer banking, small business, commercial lending and wealth management—integrate with the bank’s core, ingest payment and transactional data, meet compliance and BSA/AML requirements, satisfy the fraud and financial crimes team, connect to lending operations and commercial real estate, and give the wealth management group what they need to service high-net-worth relationships. Oh, and it has to perform flawlessly at the teller line so that branch staff have at their fingertips every piece of information they need on a customer to spend time building that relationship instead of navigating between three tools just to get an account balance, a credit score and a next-best offer recommendation.

Zoey’s promotion hinges on her ability to navigate the complexity of this purchasing decision and get it right. She starts her search.

She begins by reading a few reviews of a couple of brands she’s already familiar with on G2. She consumes a handful of LinkedIn posts from one brand and its executives, casually reads about another in her favorite newsletter from The Financial Brand (of course it’s her favorite, The Financial Brand specializes in bank marketing, after all) over her morning coffee. She catches a 20-minute clip from a prominent trade podcast she likes that features another provider’s payments SME and dives into Gartner’s Magic Quadrant on banking payment hub platforms. 

Her list broadens—she needs to tighten it. And she knows exactly where to go to do it. 

She compiles what she knows into a prompt she submits to her two favorite generative AI engines, Claude and Gemini. She asks about the brands she knows, which providers fit her specific use case and if there are alternatives she hasn’t learned enough about yet—or doesn’t know about at all.

Within an hour or two, she has a shortlist. 

She finds that Claude is giving her the right information she needs—Gemini was citing too much from a brand’s website in its responses and she wants independently validated information to inform her search. 

She and Claude spend the next couple of months conducting due diligence and evaluating. She adds more context about what she’s looking for; Claude refines his search. He crawls every vendor’s website and uses his training data to get a baseline on who they are, what they do and how well their solutions match what Zoey needs in her CRM. He provides summaries of a few relevant articles from American Banker and the ABA Banking Journal—of which her bank is a prominent member—that mention the companies on her shortlist, their CEOs and quotes from customers the reporter interviewed. He consolidates hundreds of customer reviews to identify the most relevant ones and provides a pros and cons list for every company they’re evaluating, even finding a new option they decide to add to the shortlist because of its outstanding customer reviews. He surfaces a Reddit thread where a number of users comment on one vendor’s terrible customer service and the difficulty of their integration. She’s seen enough. They drop that one from the shortlist. 

Within a few months, Zoey has a favorite and a back-up option. Time to commit. 

Now she has to walk into a room and convince her 63-year-old CEO—a guy who built his career on handshake deals and steak-dinner relationships with sales reps and peers—that her pick is the right one. The 48-year-old CTO wants references he can call to ensure the integration goes smoothly. They both want a deck they can show the board to get their buy-in. Her chief risk officer, her various VPs and department heads for consumer and small business banking, lending and compliance all expect to have their say. 

Zoey’s already past that. After months of searching, with Claude in her corner, she’s ready to finally contact her top choice to initiate the purchase, to reveal herself to her chosen vendor who, until now, had no clue who she was, that she was in the market for a purchase and that she was lurking through their marketing and sales funnels undetected at a pace she was comfortable with.

That’s just how she wanted it. 

The rest of her team, meanwhile, is just getting started. Each of them will conduct their own version of the same evaluation she just finished—through their own channels, their own sources and their own criteria for what counts as credible. Half of them will use a generative AI engine of their choice, and each of those AI engines rely on different signals and sources in how they evaluate vendors.

Versions of this scenario are happening in every B2B buying committee right now, across every vertical, and most marketing teams have no idea the degree to which it’s reshaping how demand generation actually works. These buyers are well aware of you—your brand, your executives, your reputation, your products, your competitors—long before you ever know they exist, let alone that they’re in the market for a purchase. 

But here’s the part that matters most: Awareness isn’t the same thing as authority. A buyer can know you exist and still not trust you. They can recognize your name and still rank you last on their shortlist, if you’re on it all. Brand awareness means you show up, whether in an AI engine’s response to a prompt or in a traditional marketing channel like your brand’s LinkedIn page and website. 

Brand authority means they’d choose you—and so would the AI engines they’re using to build their shortlist. That gap between awareness and authority is the thing your marketing has to close, without you ever knowing (or being able to track) who your prospects are because they prefer to move through your marketing and sales pipeline in secret, turning the former into spaghetti and the latter into a dry trough. 

More and more of them, across every generation in the workforce, are using AI in their evaluations and decision-making. They’re just using it at vastly different rates, in vastly different ways and with vastly different levels of trust in what it tells them.

Some, as you can see, are using it far more than others.

Four generations forming one buying committee with…we’ll call it “mismatched”  alignment

Here’s where it gets genuinely complicated—and where most marketing strategies fall apart like a spacecraft without a heat shield.

Gartner estimates the average B2B buying committee includes six to 10 stakeholders, which can grow to 20 or more on the most complex of purchases. Every one of those people brings a different generational default for what counts as “enough research.” The millennial trusts peer reviews on G2—where public review sites have become the number-one consulted source at 31% and climbing. The Gen X CTO trusts analyst reports. The boomer CEO trusts the relationship with the account executive.

One message alone doesn’t work for that room. And if your brand story is inconsistent across the channels each of those people trusts—if your G2 reviews say one thing, your website says another and your executive’s LinkedIn tells a third version—the committee hits an impasse. Forrester found that 91% of B2B purchases stall at some point, and younger buyers frequently cite inability to build internal consensus on vendor selection as the reason.

The messaging prism

Think about your brand’s authority like light through a prism. Your brand positioning—who you are, what you do, who you do it for, why you do it better—is a single, coherent beam of white light. But it can’t stay white. It has to refract.

Every member of that buying committee needs to see the same truth in their favorite color. And everyone has a favorite color. 

 

Brand authority is being defined right now—whether you’re building it or not

Generative search is the crucible where brand authority is being defined and measured in real time—not by your marketing team, but by how AI engines interpret everything your ecosystem says about you.

When Zoey asks Claude to compare CRM platforms, the engine isn’t just reading your website—that’s just where it starts. It’s synthesizing your reviews, your executives’ LinkedIn profiles, your media coverage, your competitor comparisons and your consistency across every channel. The recommendation it produces is shaped by signals most marketing teams aren’t measuring—and each engine weighs those signals differently, which is why she noticed Claude and Gemini giving her different answers.

One signal stands out above the rest. Millennials—the largest share of B2B buyers and the heaviest users of generative search—have significantly higher brand affinity for companies with visible, authentic executive leadership. That connection between executive presence and buyer preference is not a coincidence. Read Kathleen Lucente’s companion piece on executive visibility and the generational preferences that drive it →

Brand authority and the positioning strategy underneath it have to compensate for that awareness gap. Generative search isn’t just another channel to optimize. It’s the lens through which your brand’s coherence, credibility and consistency are being evaluated by the buyers who matter most, before they ever raise their hand.

Red Fan’s Brand Authority Index workshop at 1 p.m. CT on June 17 breaks down the seven signals that drive how AI engines recommend B2B brands—including the ones your buyers are using to build shortlists right now. Register here.