Key Takeaways
- Consumers have swapped keyword searches for conversational AI prompts, compressing the consideration stage of the funnel and cutting the number of brands buyers ever see.
- Winning AI visibility isn’t a technical checkbox; it demands a consistent digital footprint, structured expertise and a connected marketing org that speaks with one voice.
For two decades, discovery ran on keywords. B2B marketers learned to think in fragments and built entire strategies around ranking for them.
But that era is closing fast as consumers have stopped searching and started asking. They now hand AI assistants their preferences, and let the machine explore on their behalf. The behavioral change is remarkable for how quickly it’s happening, and it rewrites the rules of how buyers find you.
Amy Crowther, CEO of Incubeta Americas, has a clear message for marketing leaders wrestling with this shift: it’s a consumer behavior story, not an SEO challenge. In this Q&A, Crowther unpacks how AI is compressing the consumer decision funnel and what that means for generic discovery, what B2B brands must do to earn citations and recommendations from AI agents, and how marketing organizations need to restructure for an intent-first world.
Demand Gen Report (DGR): For two decades, marketers built their entire discovery strategy around keywords. You argue that era is ending. What’s the single biggest shift you’re seeing in how consumers actually find brands right now, and how fast is it happening?
Amy Crowther: The biggest shift is how quickly consumers have moved from searching to asking. We spent years training ourselves to communicate with search engines in very unnatural fragments: “best CRM software,” “hotel Rome family,” “restaurant near me.” Now we can communicate what we actually want, with context. We provide AI assistants with our preferences, constraints, and ask it to explore on our behalf.
The speed of the behavioral change is what I find most remarkable. AI assistants work with human behavior, not against it. They facilitate how we like to communicate what we want, with rich descriptions that take our messy personal preferences into account.
Adoption will vary by category and demographic, however it changes generic discovery enormously. Consumers can jump much further into the decision-making process with a single prompt. We’re already seeing the consideration stage of the funnel compress as a result. If I ask an AI assistant to recommend five hotels in Italy that meet my specific requirements, I may never see the dozens of brands I would have encountered through a traditional search.
DGR: There’s a real fear among marketers that AI becomes a gatekeeper deciding which brands even get mentioned. Is that fear justified, and what separates the brands that stay visible from the ones that disappear from the conversation entirely?
Crowther: In my prior answer I intentionally referred to “generic search” because branded keywords are still critical. An AI assistant can give me the most personal, tailored response— but if I’m a Marriott member, or know that the Four Seasons will be the luxury experience I want— that will influence my action, every time.
I think the fear that AI will become the gatekeeper of brand visibility is justified, but this is not the fault of AI. It’s because of the lack of consistent, long-term brand building activity many marketers have succumbed to. Swap a Search result for an AI answer and the fundamental truth of marketing still holds— brands that are more familiar, occupy more space in our memories and have recency will be most easily selected.
Yes, market share will become more and more fragmented in many categories as AI adoption increases across all demographics, but this is only a symptom. If you have a recognizable brand, that is thought of in many buying moments, then your loss in this moment should be equitable to the investment you have made over time.
However, an AI model does not mirror a shared human experience. It is the digital footprint that influences whether an AI system can correctly interpret where a brand belongs in the conversation. Therefore brands need to understand what an AI system can actually find and interpret about them. Is the website structured properly? Is the product information clear? Does the language used across the brand’s digital footprint consistently communicate what the company does and why it is distinctive? A well-defined and executed organic content strategy is key here, and starting now is too late.
What Intent Signals Reveal That Keywords Never Could
DGR: When someone asks an AI agent to find exactly what they want, they hand over their intent, not just a search term. Walk us through what that intent signal reveals that a keyword never could, and why that distinction matters so much for B2B marketers.
Crowther: That starts with brand strategy. You have to give the system enough evidence to understand who you are, what you are good at, and when you are relevant. One of the things that genuinely surprises me still is how many organizations don’t have properly documented propositions or history, and that gap matters more in an AI environment than it ever did in a search one.
Then that identity has to be represented consistently across the broader digital ecosystem. Your website cannot tell one story while your product information, PR, social content, and sales materials tell another. Not forgetting, the physical world in which consumers experience advertising and brands day-to-day. The stronger the connectivity across every touchpoint, the clearer the signal you create, the more relevant you are to the intent signal, and the more effectively you can reach the right consumer closer to the decision.
DGR: You’ve said this is a consumer behavior story, not an SEO challenge. Why do so many companies get this wrong, and what happens to the brands that keep treating AI visibility as a technical checkbox?
Crowther: Because search is where marketers have been trained. We understand SEM and SEO. We understand rankings. We understand keywords. And most importantly, we understand how to measure it. AI visibility absolutely has a technical component. Structured data and knowledge graphs matter enormously. So when AI starts influencing discovery, the instinct is to take the framework we already know and apply it. That’s the start, but not the end.
The bigger question CMOs should be asking is: What contexts matter to my customers? That requires looking across the whole customer experience.
DGR: Keywords were something marketers could target and buy against; intent feels harder to game. How does a brand influence discovery when the consumer is talking to an AI agent instead of typing into a search bar?
Crowther: If we’re talking about ‘targeting and buying’ then yes, the richness of how humans interact with AI agents does make it harder to build a plan that meets every need. However, if we go beyond paid media and think about the full digital experience, there is actually very little difference and I believe that it’s easier, not harder for a brand to navigate.
Keywords were always limiting, little snippets of things, places, ideas that were listed out and regularly refreshed. But now, this is the new ‘long-form.’ Brands can match the depth of context, they can share their stories and what makes them distinct in much deeper detail, giving it much more chance of being relevant.
How to Influence Discovery When Buyers Talk to AI, Not Search Bars
DGR: B2B buying cycles are long, layered, and rarely driven by one person. How does AI-driven discovery reshape the way buying committees research, shortlist and choose vendors, and where does that leave the brands still optimizing for last-click attribution?
Crowther: With AI adoption, I would argue that the B2B buying cycle has not changed, yet. Like any multi-stakeholder and very human decision process, a consensus must be formed and we are a long way from complex organizations having a source of truth in AI.
At individual stages of the process, yes, AI can dramatically speed-up the manual steps, such as proposal review, one-for-one comparisons and compliance vetting. AI certainly helps to interrogate those recommendations and narrow a field much faster than a manual process would. But without every stakeholder leveraging AI from the same shared knowledge base, a disconnect persists. Connectivity is the key— across internal and external data which creates the foundations of unified decision making. Without this, last-click attribution is even less representative of how the decision was actually made and frankly has no place in B2B Marketing as a leading indicator or KPI.
DGR: If content used to win by matching keywords, what wins now, and what does B2B content need to look like to get surfaced, cited and trusted by an AI agent?
Crowther: Specificity becomes incredibly valuable. B2B companies tend to have huge amounts of genuinely useful knowledge sitting inside the organization: technical documentation, product expertise, research, customer questions, executive knowledge. Structuring that knowledge so an answer engine can actually parse it, in FAQs, product feeds, and technical documentation, is what earns the citation.
Generative AI makes it incredibly easy to produce enormous amounts of generic content, but flooding the internet with more average material doesn’t give a brand authority. Quality still matters. The brands with something genuinely useful and distinctive to say have an advantage, and AI makes the discipline of articulating that expertise even more important.
DGR: In a keyword world, you could outspend a rival for the top spot. In an intent-driven world, what actually earns you the recommendation, and can a smaller challenger brand now outmaneuver a bigger incumbent?
Crowther: There is an interesting tension here for sure. Large established brands begin with an enormous advantage because they already have awareness and we could assume a substantial digital footprint. There is a version of marketing’s “double jeopardy” effect playing out in AI discovery, where brands that are already known have more signals for these systems to draw from.
But challenger brands have an opportunity because AI is evaluating relevance to a much more specific request. If a smaller company can demonstrate that it is exceptionally relevant to a particular need and provide strong, accessible evidence of that expertise, it can enter conversations where the consumer might historically have defaulted to the biggest name.
That should be exciting for B2B challengers. You don’t necessarily need to become the most famous company in the category before you can become a highly relevant answer to a particular need.
Can Challenger Brands Outmaneuver Incumbents in AI Discovery?
DGR: What’s the first move you’d tell a CMO to make this quarter to prepare for AI-first discovery?
Crowther: Find out what AI currently thinks your brand is.
Before investing heavily in new content, creative, media or technology, establish the baseline. Look at the prompts your customers are likely to use. See whether you appear, who appears instead, and when you do appear, how accurately the answers represent your brand.
I think a lot of marketing leaders are overwhelmed by AI because they feel pressure to immediately develop it as a new discipline or channel. The useful starting point is to think of it as embedded into everything— a horizontal line on the marketing plan. Understand the reality of where your brand is today. From there, identify the gaps that are actually relevant to your business and your customers. Then, adapt your existing plans in media, creative, measurement or technology to account for them.
That also helps cut through some of the AI hype. Not every brand needs the same solution. The right investment depends on your category, your customers and what you are trying to accomplish commercially.
DGR: Looking ahead, if intent replaces keywords as the currency of discovery, how does the marketing org itself need to change, the skills, the metrics, the team structure, to compete in that world?
Crowther: The biggest organizational change is connectivity. Marketing has spent years building specialized teams, and specialization brought tremendous expertise. The problem comes when those teams operate independently. AI-driven discovery draws signals from across the business, so the disconnect between brand, performance, data, technology and the customer experience becomes much more consequential.
That changes the relationships at the executive level as well. I’ve been talking a lot about the growing importance of the CMO, COO and CTO relationship. Marketing infrastructure is becoming a critical part of marketing strategy. If your data systems cannot communicate or your approval processes cannot keep pace with what the technology enables, you cannot operate at the speed consumers now expect.
