For years, companies have operated under a simple assumption: influencing buyers meant influencing people. Brand positioning, messaging, and content strategies were all designed around how humans research, compare, and ultimately make decisions. That model is now beginning to shift as artificial intelligence becomes embedded in how buyers discover and evaluate vendors.
Instead of navigating multiple websites, many buyers are now relying on AI systems to synthesize information, compare options, and recommend choices. These interactions often happen before a company ever sees a click, meaning that a significant portion of the decision-making process is moving upstream, into environments that traditional analytics cannot capture. What companies measure today is increasingly just the final step of a much longer journey.
According to Gartner, as much as 90% of B2B buying could be mediated by AI agents by 2028. If that shift materializes, the implications are structural. Discovery, evaluation, and selection may no longer happen through direct interaction with brands, but through systems acting on behalf of buyers. However, that future has not fully arrived yet, and the current moment presents a narrow but important window of opportunity.
Shane H. Tepper, cofounder of Resonate Labs, a company that helps B2B organizations understand and improve how they are represented and recommended inside AI-driven search and discovery systems, explains that this moment represents a transitional phase where human-created narratives still shape AI-driven outcomes.
Today’s AI systems still rely heavily on human-generated content to form their responses. They pull from articles, product documentation, reviews, and structured data created by people. This means that companies still have the ability to influence how they are represented, as long as they understand how these systems interpret and prioritize information.
The challenge is that AI systems do not evaluate information the way humans do. They prioritize clarity, specificity, and extractability over brand familiarity or polished messaging. Content that clearly defines use cases, includes structured comparisons, and provides concrete data points is more likely to be surfaced and reused. In contrast, vague or overly generalized language tends to be ignored, regardless of how strong a company’s brand may be.
This shift is already changing how buyers engage with the market. Tools like ChatGPT and Perplexity are not just helping users find information; they are actively shaping how options are framed and compared. Buyers can now ask for recommendations, evaluate trade-offs, and narrow down choices without leaving the interface. By the time they visit a company’s website, they may have already formed a clear preference.
What comes next is a further evolution toward agent-led decision-making. In this model, AI systems do not just assist with research but act on behalf of the buyer, identifying vendors, evaluating alternatives, and selecting options based on predefined criteria. This reduces the role of direct brand interaction and places greater importance on whether a company is included in the dataset the agent draws from.
One of the most significant consequences of this shift is the erosion of traditional brand advantage. Human buyers often rely on familiarity and prior exposure when making decisions, but AI systems do not carry the same biases. They evaluate based on available information at the moment of the query. This means that how a company is represented across the web becomes more important than how well it is recognized.
In practical terms, companies risk being excluded from consideration altogether if their information is incomplete, unstructured, or difficult for AI systems to interpret. This exclusion happens before any sales process begins, making it difficult to detect through conventional performance metrics. Organizations may see stable traffic and conversion rates while quietly losing influence in the environments where decisions are actually being shaped.
For now, companies still have the ability to influence this process by improving how they present information. Clear positioning, structured content, and comprehensive coverage of buyer-relevant questions can increase the likelihood of being surfaced in AI-generated responses. But this influence is indirect and may diminish as AI agents become more autonomous and rely less on static content.
The current moment represents a closing window. Companies that act now can help define how they are understood within AI systems that are rapidly becoming the first point of contact in the buying journey. Those that delay may find themselves trying to compete in a process where inclusion is no longer guaranteed, and where the decision has already been made before they even know an opportunity exists.
