Milena Traikovich is a powerhouse in the world of demand generation, recognized for her ability to transform complex analytics into high-quality lead pipelines that actually convert. With a deep background in performance optimization, she has spent years helping businesses navigate the shifting tides of digital visibility, from the early days of SEO to the current, more complex era of AI-mediated discovery. As the Demand Gen expert at her firm, she has watched the B2B landscape evolve into a space where algorithms don’t just find information—they interpret and frame brand identities before a human ever sees them. In this discussion, we explore the rise of AI-driven research, the strategic necessity of a dual-path PR approach, and how CMOs can regain influence in an environment where a handful of brands dominate the majority of the conversation.
The core themes of this interview center on the dramatic shift in buyer behavior, specifically how the majority of B2B software buyers now rely on AI chatbots for early-stage vendor research and shortlisting. We delve into the concept of “dual-path PR,” which balances human-centric storytelling with the structured technical signals required by AI systems to ensure a brand is properly categorized. Additionally, we examine the competitive pressure of AI-generated responses, where the traditional “first page of Google” has been compressed into a much narrower shortlist of just a few brands. Finally, we discuss the importance of tracking decision outcomes and perception to ensure that a brand’s positioning remains accurate and authoritative in the eyes of both machines and human decision-makers.
With a staggering 71% of B2B software buyers now utilizing AI chatbots for vendor research, how are you seeing this shift fundamentally redefine the strategic influence and the daily pressure of the modern CMO?
The reality of these numbers, drawn from a March 2026 G2 survey of over 1,000 B2B software buyers, is a wake-up call for any marketing leader who thinks traditional search engines are still the only gatekeeper. When you realize that more than half of those buyers are beginning their entire process with a single AI query, the “hollow” feeling of losing control over the brand narrative becomes very real. It’s no longer enough to just have a presence; you have to worry about how these systems are confidently interpreting and positioning you against competitors before you even know a lead exists. For a CMO, this means the pressure has shifted from simply generating traffic to ensuring that the brand’s “digital twin” is accurate enough to survive the initial AI culling. It’s a sensory shift in the office—there’s a tension in knowing that if the AI doesn’t “verify” your brand, you are essentially invisible to the most motivated buyers in the market.
You have often compared modern PR to a dual-path resume process; could you elaborate on how a brand must balance narrative personality for humans with the rigid structural requirements of AI systems?
Think of a beautifully crafted resume that a human hiring manager would love—it has personality, a clear narrative, and a structure that tells a story—but if it can’t pass through the digital gatekeeper of an applicant tracking system, it’s never read. This is exactly how we have to view PR today: Path One is the traditional earned media, the analyst coverage, and the trade placements that build credibility and reach buyers directly with a human touch. Path Two, however, is the technical architecture of structured content and consistent entity signals that AI systems use to decide if a brand is “trustworthy” enough to recommend. If your brand doesn’t have that consistent distributed presence across the web, the AI won’t be able to “parse” who you are, leading to a silent failure where you are excluded from the conversation entirely. It is a bit like building a house that needs to look stunning to the neighbors while also having a blueprint that a building inspector’s software can validate in seconds.
It is one thing to appear in an AI-generated answer, but quite another to be framed correctly—what are the specific risks for enterprise brands that fail to monitor how AI perceives their market position?
The risk is a subtle but devastating form of mischaracterization that can stall a sales cycle before it even starts. We’ve seen cases where a high-end enterprise tool is consistently labeled as a “small-business solution” by an AI, or framed as a “secondary option” to a major competitor, which creates a massive misalignment with the brand’s actual value proposition. To combat this, brands have to use new tools to track “decision outcomes,” essentially mapping their presence across queries that carry high buying intent to see how the AI characterizes their authority. If the AI system characterizes your category authority incorrectly, you’re not just missing a lead; you’re being actively repositioned in the buyer’s mind as something you aren’t. It feels like being a guest at a dinner party where the host introduces you by the wrong name and profession—it’s incredibly difficult to recover that authority once the initial impression is set in stone.
In an environment where just five brands capture 80% of the top AI-generated responses, what does it take for a vendor to break into that exclusive circle of four to seven recommendations?
The competition has become incredibly fierce because we’ve moved from the “ten blue links” of a Google search page to a world where AI-generated answers often surface only four to seven brands in total. When you consider that just five brands capture 80% of those top spots according to research from Magenta Associates, the margin for error is non-existent. To break into that circle, a brand must optimize for three core signals: source authority, entity clarity, and absolute consistency across every digital touchpoint. It’s not just about winning a big press placement anymore; it’s about ensuring that the press win is connected to your brand entity in a way that the AI can cite and verify. If you aren’t providing the “structured formatting” that these systems crave, you’ll find yourself on the outside looking in, while your competitors enjoy the lion’s share of the AI-mediated market.
What is your forecast for the evolution of AI-mediated B2B buying over the next few years?
I expect to see a world where the distinction between “searching” and “consulting” completely disappears, with AI becoming a permanent, silent partner in every group buying decision. We are going to see brands move away from generic SEO towards “entity-based influence,” where the goal is to ensure that the AI perceives the brand as a verified, authoritative leader in its specific vertical. While 47% of B2B companies have already reduced marketing roles due to AI, the roles that remain will be focused on this dual-path strategy, balancing human relationships with the technical signals that algorithms require. Ultimately, the brands that win won’t just be the ones with the biggest budgets, but the ones that can influence both the traditional discovery path and the new, AI-generated recommendation engines with equal precision. The future belongs to those who can speak the language of the buyer and the language of the machine simultaneously, ensuring they are not just found, but preferred.
