We’re all in the same boat. Every revenue leader facing our new, AI-mediated buying reality is wrestling with the same question: how do we market, sell, contract and retain when AI is the buyer’s new trusted adviser, humans still make decisions and traditional search engine optimization (SEO) still matters?
At AI Revenue Institute (AIRI), we call this dilemma the “Three-Audience Problem.” And if you’re not up on it yet, here’s a rundown on what it is and how to get your arms around it.
What is the Three-Audience Problem?
The Three-Audience Problem is the challenge of creating content that simultaneously appeals to three distinct audiences:
AI systems that buyers use for search, research and vetting
The humans those AI systems serve
Traditional search, which still generates enormous traffic and commerce potential
You can’t pick one and expect it to cover the rest. The illustration below offers a visual representation of the scope of the problem.
Selling to AI, humans and search engines can’t wait until tomorrow
If you’ve read AIRI’s study, “The AI-Powered B2B Buyer Has Arrived,” you know that we’ve determined buyers are further along in their adoption of AI than sellers. Here’s why:
Most companies are only just coming to grips with what they need to do to compete for AI search results using answer engine optimization (AEO) and generative engine optimization (GEO).
Websites are starting to carry some boilerplate structured data. JSON-LD is on 54 percent of all sites as of the time of this writing, per W3Techs. But almost none of it would qualify as true Revenue Signal Architecture: the deliberate construction and coordination of revenue-critical content, code and structure for human, search engine and AI conversion.
Our team knows companies that have historically foregone PR, brand and other external validation exercises in favor of long-proven sales motions (direct, referral, partner, etc.) and have yet to connect that decision to slowing revenue (or revenue growth) or deals falling silent. (AIRI Co-Founder Khali Henderson just gave a lecture on how AI is becoming a silent deal killer. While this was an AI event, AI-savvy attendees expressed genuine surprise at new AIRI data showing the scope of buyers shifting to AI. It’s moving fast.)
Speaking of Khali, when she presented on AI disruption of the buyer’s journey to a highly tech-savvy revenue audience at a conference just a couple of months back, participants were caught flat-footed by Forrester data showing that 94 percent of B2B buyers now use AI in their purchase process, and our own live testing data demonstrates surges in negative behaviors toward vendors when AI is specifically asked to vet them.
In broad terms, the current state of sellers’ readiness for AI-powered buyers is probably best described as this: Some sellers are beginning to work toward “showing up in ChatGPT results.” That’s a good step, but it’s way behind the buyers’ adoption curve.
To be fair, there are revenue leaders who see what’s happening to some of their long-tail revenue streams, understand that buyer AI’s influence on lost deals is usually invisible and are trying to drive adaptation.
But in AIRI’s inaugural B2B AI Buying Behavior Survey of 521 enterprise buyers, 82 percent told us they regularly use AI to screen at least one of three core vendor document types (contracts, security documentation and technical documentation). Forty-four percent do all three. That’s not early adoption. That’s near-universal usage of AI for tasks beyond discovery. Buyer use of AI is rapidly expanding into every aspect of finding, vetting and contracting vendors, products and services.
Buyers aren’t waiting for us. They’ve already changed how they buy.
6 factors underpinning the Three-Audience Problem
Under the surface, the Three-Audience Problem is multifaceted because AI is changing the buying experience itself. The big factors you need to address are:
Funnels are fractured. Many buyers no longer travel through journeys and funnels. They may see a single page, if that. Every key revenue page must be a complete sales argument. Some buyers still want the journey, so you have to be ruthlessly efficient in how you structure content that serves both. This means getting your planning house in order to a level you likely haven’t had to reach before.
AI discovery is only step one. As we just covered, AEO and GEO matter, but AI discovery is only your opening move. And AI search yields limited slots since there are no page 2 results as with traditional search, so your other revenue motions will carry most of the load. As our new research data shows, AI will vet you no matter how you’re discovered. A buyer who finds you through a referral, sales partner, ad, event or old-fashioned Google search will still run your claims through an AI assistant. Show well, or you’ll be scrubbed from the shortlist.
Unbacked claims make competitive weaknesses machine-readable. Schema is AI’s love language, but like any language, it’s what you say that matters, not just getting the syntax right. You need to send the right signals, and they need to be verifiable (cue the next point). Structured data with thin, generic or unverifiable claims just makes your competitive weaknesses machine-readable.
AI cross-checks claims against third-party evidence. AI looks for external validation of your signals. Your claims get cross-referenced against reviews, analyst coverage, press, awards, partner sites and anywhere else your story shows up. If the external record contradicts or fails to corroborate what you say about yourself, AI notices. And no, you can’t get by without them. AI will (politely) beat you up for lacking corroborating data and offer to expand the buyer’s search with new vendors.
The easier AI makes buying, the more sellers must do. There’s a genuine asymmetry in how AI is changing revenue motions. The easier AI makes it for the buyer, the more you have to do as the seller. Buyers compress weeks of research into minutes. Sellers have to build the depth, structure and verifiability that makes that compression work in their favor. The good news for you right now is that since most companies are way, way behind the curve, you can gain ground fast in ways that will compound as AI-powered buyers rely increasingly on their AI assistants and agents to guide them.
Organizational silos create misaligned messages. The divisions inside companies, between marketing and sales, product and comms, corporate and field, and all the others, have to be bridged to present cohesive, verifiable stories everywhere. This applies all the way down the org chart. As you build a cohesive content architecture, it needs to be elevated above and over top of everyone who handles your social, web, field, partner, PR, event and other revenue motions. Misalignments that were historically accepted as “could be better” are real deal-breakers in this new world.
Don’t confuse tactics with strategy
As you’ve been reading, you’ve likely drawn a deep breath while thinking through all that needs to happen to adapt to this brave new world. (Welcome to the Singularity, my friend. Bask in the abundance.)
Yes, you need to execute on a boatload of tactics to practically address the Three-Audience Problem. But you won’t achieve your goals without a larger positioning strategy that factors in how people are buying now and the speed at which buyers are leaning into AI, in addition to all the traditional competitive levers you need to close deals (e.g., differentiators, responses to competitor promos and product releases, and all the rest). Tactics executed against a stale positioning strategy just make you consistently wrong across more channels.
What you can do: Take 4 steps to make your content work for all 3 audiences
Unify content and calendaring around one story. Events, product launches and updates, research-based positioning, blogs and podcasts, PR and social campaigns, and all your other messaging need to run on one spine. Use calendaring to look ahead and reinforce your story with every asset you create.
Continuously monitor and improve what AI says about you. Measure, measure, measure what AI says about you. Then respond and measure again. AI’s picture of your company isn’t static. Neither is its view of your competitors. Treat AI perception the way you treat pipeline: a metric you review, act on and re-review continuously.
Ensure third-party evidence supports your claims. Inventory the claims your key revenue pages make and make sure the external record backs them, through analyst coverage, reviews, awards, press and partner proof. Where evidence doesn’t exist yet, either build it or stop making the claim.
Use AI to amplify expertise, not for generic slop. AI assists humans, so it rewards the same things humans and traditional SEO reward: strong graphics, video, genuine insight, real point of view. The three audiences overlap more than they conflict when your content is actually good. You can and should use AI in smart ways to atomize your expertise across formats and channels. Just keep the underlying content real, unique and insightful.
If you’re facing internal pressure to “just have AI” generate content at volume or on the cheap, we have survey data to help you with that conversation, too. Nearly half of buyers already say they or their AI assistants are having trouble differentiating companies because of AI-generated slop. Trendslop gets you nowhere. Worse than nowhere, actually. It makes you indistinguishable at the exact moment distinguishability is the whole game.
The Three-Audience Problem can’t be solved by marketing alone
The Three-Audience Problem touches positioning, content architecture, technical infrastructure, measurement, org design, execution on things big and small, and all the other connections your head just made. (Go ahead, suck in another deep breath. I took one just writing that sentence. Like I said, we’re all in the same boat.)
But the advantage of being in the same boat with others is you aren’t alone. You’ll get lots of data and insights from the AIRI team tackling these areas in the weeks ahead. Onward.
YOUR FEEDBACK IS WELCOME: If there are specific areas you’d like us to cover, ping us.
Download the full AIRI B2B AI Buying Behavior Survey Report, “The AI-Powered B2B Buyer Has Arrived,” to explore all five shifts and the complete findings.