Milena Traikovich is a powerhouse in the demand generation space, specializing in how data-driven strategies connect with evolving buyer behaviors. In an era where the sales landscape is being reshaped by machine intelligence, she offers a ground-level perspective on how businesses can maintain a competitive edge. As our Demand Gen expert, Milena brings extensive experience in analytics, performance optimization, and lead generation initiatives to help businesses navigate the complexities of modern procurement. Today, we are exploring the profound shift toward buyer-controlled AI and what it means for the future of human-led sales.
G2’s 2026 Buyer Behavior Report, “The Evaluation Maze,” highlights that over 60% of B2B buyers are now utilizing AI agents to navigate the software purchasing process. How is this fundamental shift in research and shortlisting changing the way you approach lead generation and vendor discovery?
This shift is revolutionary because it fundamentally moves the “gatekeeper” role from a human assistant to a sophisticated digital agent. When 60% of your audience is delegating research, shortlisting, and side-by-side comparisons to an algorithm, your traditional top-of-funnel tactics have to evolve or they simply become invisible. We are no longer just marketing to humans who might be swayed by a flashy banner or a catchy subject line; we are marketing to agents that prioritize structured data and objective performance metrics. This means our discovery strategy must focus on being “agent-readable” while ensuring that the final human decision-makers receive the distilled, high-value insights their agents produce. It’s a sensory shift for sales teams who are used to the “vibe” of early-stage discovery calls, as those initial interactions are increasingly being replaced by the silent, efficient processing of a buyer’s own AI.
In the current landscape, the traditional sales relationship is often built on trust, yet Forrester’s data shows that generative AI and conversational search have overtaken vendor websites and sales reps as primary information sources. What does this tell us about the three pillars of trust—competence, reliability, and alignment—and which one is currently the most vulnerable to AI disruption?
The most vulnerable pillar is undoubtedly competence, as AI can already out-research almost any human rep when it comes to product specifications, pricing models, and competitive benchmarks. We are seeing a massive “competence gap” close rapidly because a machine doesn’t forget a technical spec or miscalculate a tiered pricing discount. However, reliability remains a significant hurdle, as evidenced by the “one-in-five” problem where 20% of buyers feel less confident due to AI hallucinations or outdated information. While competence is being automated, reliability is still an engineering challenge that, once solved, will leave “alignment” as the final human stronghold. Alignment—the sense that a partner is truly on your side and understands your unique business pressures—is something a buyer’s agent can simulate, but it cannot yet replace the gut feeling of a shared mission between two people.
While many organizations are investing in AI to make their sales reps more efficient, you’ve noted that the real threat isn’t the vendor’s AI, but the buyer’s own agent. Why should sales leaders be more concerned about the machine working for the buyer than the one they are building for their own team?
The dynamic changes completely when the buyer stops trusting your AI because they know it’s a “salesperson that never sleeps” designed to maximize vendor profit. A buyer’s own agent is a different beast entirely; it is a loyal advocate that researches vendors, flags hidden risks, and negotiates terms with the buyer’s best interest as its only north star. Trust doesn’t simply disappear from the sales cycle; it transfers from the human seller to the buyer’s machine, which can feel like a cold, impenetrable wall to a traditional sales team. When a buyer trusts their agent more than your rep, your rep loses their seat at the table during the most critical evaluation phases. This forces us to reconsider the value proposition of a human seller, moving them away from being information providers and toward being strategic navigators who can handle the nuance an agent might miss.
Recent surveys from Gartner indicate that 45% of buyers used generative AI during a recent purchase, yet complex, high-stakes deals still seem to require a human touch. In what specific scenarios do you see accountability and personal risk keeping humans at the center of the deal?
High-stakes deals, particularly those seven-figure platforms that can define a career, carry a level of personal risk that an AI simply cannot shoulder. When a buying group commits to a massive implementation, they aren’t just buying software; they are buying the assurance that someone will be there when the implementation goes sideways at 2:00 AM. Buyers want a human who will walk into the CFO’s office with them to defend the ROI, and they want someone who can be held personally accountable if the promised results don’t materialize. An AI agent cannot feel the weight of a reputation on the line, and it cannot navigate the silent tension of a boardroom where the IT director and the VP of operations are at odds. This “accountability premium” is what buyers are actually paying for in complex cycles, and it remains the strongest barrier against total automation.
You’ve mentioned the “invisible work” of sales—the hallway conversations and the ability to sense political capital within a buying group—as a current human advantage. As call recordings, Slack, and meeting transcripts begin to capture more of this data, how quickly do you see this “data gap” shrinking for human sellers?
The data gap is shrinking much faster than most people realize, as every Slack message and Zoom transcript becomes fuel for more sophisticated behavioral models. We are moving toward a reality where the “vibe” of a meeting is no longer a mystery but a series of data points that an AI can analyze to detect if a champion is losing political capital or if a “no budget” objection is actually a timing issue. The sensory details of a sales call—the hesitation in a voice, the delay in a response—are being digitized and decoded with increasing accuracy. However, there is still a layer of “hallway knowledge” and off-the-record side calls that remains uncaptured, providing a temporary sanctuary for the human rep. The challenge for sales organizations is to realize that this sanctuary is getting smaller every year, and they must double down on judgment and the ability to translate risk into confidence.
What is your forecast for the evolution of the B2B sales representative role over the next few years as AI agents become the primary interface for procurement?
The sales rep of the future will either become a “strategic architect” or they will find themselves obsolete. We will see a sharp divide where transactional, low-risk deals—like cloud capacity renewals or commodity software licenses—become entirely autonomous “zero-touch” environments. For everything else, the role will shift toward navigating the internal friction of the buying group, exercising high-level judgment that data alone cannot provide, and owning the ultimate outcome of the partnership. The question isn’t whether AI will get good enough to replace your reps; it’s whether your reps can provide a human reason for the buyer to keep them in the room. By 2028, I expect the most successful sellers will be those who use AI to handle 90% of the administrative and research heavy lifting, allowing them to focus entirely on the emotional and political nuances of the final 10% of the deal.
