After two decades of optimizing funnels, measuring attribution, and perfecting lead scoring, the rules of B2B marketing have fundamentally changed. Large language models aren't just affecting how buyers research—they're causing buyers to disappear from traditional marketing channels altogether.
Seemingly overnight, SEO click-through rates have dropped by over 30% as buyers turn to LLMs like ChatGPT, Claude, Perplexity, and Gemini for product discovery and evaluation. Even more problematic, buyers are beginning to conduct entire evaluation processes within AI environments, skipping vendor websites, avoiding generic content, and never appearing in marketing impact reports.
As this trend gains momentum, AI becomes the decision-maker on which products should be considered or valued without buyers ever knowing of their existence. This is a particularly harsh reality for burgeoning companies and marketers.
This isn’t the death of marketing, as much as it may feel like it. It’s a call to evolve.
The Invisible Buyer Crisis
Consider how a modern B2B purchase decision actually unfolds today. A CTO at a 300-person global company needs a new secure access solution. Instead of starting with Google searches that lead to vendor websites, they open ChatGPT with a detailed prompt: "I'm evaluating secure access solutions for a 300-person company across 10 countries. We currently use [current stack], operate in [specific cloud environments], and need [detailed requirements]. What should I be considering, and which vendors best fit these criteria?"
The LLM responds with a comprehensive analysis—key evaluation criteria, potential pitfalls to avoid, and a ranked list of vendors with detailed comparisons across every criterion. The buyer then refines their requirements, asks follow-up questions, and even requests the AI to generate an RFP template tailored to their specific situation.
Through this entire process, which might historically have generated dozens of website visits, content downloads, and trackable touchpoints, the buyer never once visits a vendor website. They arrive at vendor conversations already educated, with pre-formed opinions shaped entirely by how well each company's information was represented in the LLM's training data.
This is highly efficient for the buyer. It’s no wonder they love the approach.
But the new process highlights that a massive break is underway, rupturing an economic model that has powered B2B marketing for decades. Suddenly, the exchange of valuable content for contact information and behavioral data—the foundation of lead generation—holds no currency.
It can feel a bit fatalistic for marketers who wonder if their role may disappear altogether. The answer, from my perspective, is a clear no. But it is changing quite rapidly, which has to be acknowledged. Marketers must recognize that personalization at scale is do now or die; they must be ready for LLMs to emerge as a dominant marketing channel. Otherwise, people will stop creating and publishing content.
Three Waves of Marketing Evolution
This transformation is unfolding in three distinct waves, each requiring fundamentally different strategic responses.
Wave 1: Operational Efficiency.
The first wave mirrors the rise of generative tools for personal productivity. Tools like ChatGPT and Canva Magic Write let marketers draft faster—but they remain manual, siloed, and inconsistent. Now we’re evolving toward more sophisticated, structured platform-native creation. Tools can generate complete marketing programs from a set of inputs: campaign messaging, audience parameters, and brand guidelines that produce everything from microsites to email sequences to social content– localized and aligned to buyer goals and market segments. This isn’t just about efficiency—it’s a 10x acceleration in campaign launch speed and a lifeline for budget-strapped teams.
Wave 2: Strategic Orchestration.
The second wave is now starting to shift focus from creation to performance. Modern marketing requires orchestration: dynamic, 1:1 journeys that adapt by stage, industry, role, or behavior—at scale. In this phase, AI isn’t just creating assets, it’s coordinating them. Think about AI-powered systems that develop smarter, more relevant experiences that adapt in real-time to buyer behavior and context. For the first time, truly personalized engagement will become economically viable at enterprise scale. This could result in an order of magnitude higher responses and business outcomes.
Wave 3: Transformational Engagement.
The third wave breaks the funnel altogether. Large language models (LLMs) will become the default research interface for B2B buyers– and this is happening soon. The next generation of AI-native buyers may never visit a vendor’s website. They’ll ask a chatbot, voice assistant, or wearable device to compare options, generate RFPs, and surface vendors—all without a click.
No more navigating complex corporate websites. Buyers will land on a simple page—like Google's homepage—with a single prompt: "Ask me anything about our solutions." Forward-thinking companies are already experimenting with this type of blank-page experience where sophisticated AI agents handle the entire initial buyer interaction, providing deep product expertise and personalized guidance without human intervention.
Preparing for the Inevitable
The buying behavior changes we're already seeing point toward a clear conclusion: LLMs will become a primary channel for B2B discovery and evaluation. This does not mean that people will avoid marketing touches outside of LLMs, but they are far more likely to only respond if that touchpoint was highly specific and relevant to them in a particular moment. Otherwise, the buyer could remain completely under the radar. To succeed in this landscape, B2B marketers must adapt their strategies–and build and implement the right systems to compete.
This means B2B marketers must stop chasing impressions, clicks, or even leads and start engineering relevance through next-generation personalized experience platforms–ones that enable rapid deployment capabilities, hyper-personalization at scale, and interactive buyer experiences that generate deep behavioral signals. New technology should be implemented seamlessly with existing systems of record to create bidirectional data flow that feeds both immediate engagement and long-term pipeline intelligence.
Though we don’t quite know what future channels will look like, consider that LLMs will serve as marketing channels, accessible to marketers through some paid media option. Personalization could actually operate as its own system, one that could operate inside LLMs themselves. Think beyond SEO for AI interfaces. Think paid visibility inside buyer conversations—not just on Google, but on ChatGPT, Claude, Perplexity, or your next-gen phone’s voice-only assistant.
As systems and processes change ROI measurement will need to evolve as well. New success metrics will move into leading indicators, not only brand mentions, but rather measuring true engagement with the actual messaging and content in those scarce moments.
The marketing funnel, as we've known it for decades, is dying, and so are the traditional systems that support it. That’s ok. We simply need to prepare. This is an opportunity to think differently, embrace a new challenge, and leverage new tools built for this moment. Let us not run away or bury our heads in the sand, but seize it and go boldly into the future.
So what now?
Start by embracing what AI is already changing—and prepare your team for what’s next.
- Upskill fast. Make AI literacy a team sport. Get marketers hands-on with real tools. Run monthly challenges. Remove fear. Reward experimentation.
- Audit your stack and practices. Legacy tools weren’t built for this. Ask every vendor—and yourself: Can this scale personalized engagement and capture deep buyer signals in real time?
- Pause the replatforming. A full website rebuild or new system of record may sound strategic. Right now, it could be a career-killer.
This isn’t about waiting for the future to arrive. It’s about recognizing it’s already here—and choosing to lead.
