A buyer arrives at a vendor conversation this year having already read the reviews, compared several alternatives, watched a demo video, asked a peer on a private Slack channel, skimmed an analyst report, and asked an AI tool to summarize how the category works. By any reasonable measure, this person is informed. What is less certain is whether they are decided.

That gap — between having information and having a defensible conclusion — is where most current thinking about B2B buying behavior stops short. The prevailing narrative describes a buyer who no longer needs anyone’s help: self-directed, digitally fluent, allergic to sales outreach, increasingly served by AI tools that can summarize a market in seconds. Gartner’s research, based on a survey of 645 to 646 B2B buyers fielded between August and September 2025, found that 67% of buyers prefer a rep-free purchasing experience, and 45% report using AI tools during a recent purchase. That finding is real. But the same research program and fielding window produced a second finding that complicates the “buyers don’t need us anymore” story rather than simply softening it: 69% of B2B buyers said they prefer to validate AI-generated insights with a sales representative.

This is not a contradiction to explain away. It is the actual shape of the problem, and it is more precise than “buyers are self-directed but still want humans.” The precise version is this: access to information and confidence in a conclusion are not the same achievement, and the gap between them does not close just because research got easier.

Information Access Was the Old Problem

There was a period, not long ago, when a buyer’s biggest obstacle really was finding out enough about a category to make a decision. Vendors controlled much of what was knowable about their own products; competitive comparisons were hard to assemble independently; pricing was often opaque until a sales conversation began. Under those conditions, “give the buyer more information” was a coherent, sufficient strategy, because information was the scarce resource.

That condition has changed. Forrester’s 2026 State of Business Buying report, drawing on its 2025 Buyers’ Journey Survey, found that generative AI tools were the single most cited meaningful interaction type buyers used for researching a purchase — ahead of vendor websites, peer conversations, and every other channel Forrester tracked. Gartner’s data adds a related detail: buyers now consult an average of seven distinct information sources during a purchase.

None of this means total transparency has arrived, or that every buyer can now assemble a perfect picture of a market unassisted. It means the specific barrier that used to define the early stage of buying — not being able to find enough information — has substantially fallen for a large share of B2B purchases. That is a real shift, and it changes what a company’s communication is actually being asked to do. It is no longer primarily being asked to inform someone who lacks facts. It is being asked to do something else, and the nature of that something else is where most current commentary loses precision.

What More Research Actually Produces

Here is the complication that access alone doesn’t resolve: more research does not just produce more answers. It produces more material that has to be weighed, reconciled, and judged.

A buyer using generative AI to research a category is not receiving a single, verified answer. They are receiving a fluent, confidently-worded synthesis assembled from whatever sources the tool was trained on or retrieved — sources of uneven quality, sometimes outdated, sometimes contradictory, compressed into a single authoritative-sounding response. Gartner’s research captures a direct consequence of this: 51% of buyers say they are more likely to encounter misleading information from generative AI, compared with 49% who say the same about sales representatives — a near-even split that suggests buyers do not currently regard AI-derived information as more reliable than the human channel it is often assumed to be replacing.

This is a different problem than “AI is sometimes wrong.” It is that the buyer, not the vendor and not the AI tool, is now the one responsible for figuring out which parts of a synthesized answer to trust, which reviews reflect their actual situation, and which competing claims to believe. A tool can compress disagreement into a single fluent paragraph without resolving it. The buyer is left holding more material and more responsibility for judging it than they had when information was scarcer and the questions were simpler.

Validation Is Not a Retreat From Self-Direction

This is where the Gartner finding above earns a second look. Sixty-seven percent of buyers prefer to avoid a sales rep. Sixty-nine percent say they prefer to validate AI-generated insights with one. Gartner reports both findings from the same research program and fielding window — and the firm’s own interpretation treats them as compatible rather than contradictory: buyers are comfortable navigating most of the purchase process independently, but that comfort does not eliminate a distinct need for validation at specific moments.

Validation does not mean asking someone else what to buy. It means testing whether a conclusion the buyer has already reached is one a credible source would also reach — a check against error, not a surrender of judgment. Gartner’s VP Analyst and Chief of Research in its Sales practice put it directly: buyers are “more comfortable using digital channels and GenAI to navigate the purchase process on their own, but that does not eliminate the role of the seller.” A separate part of the same research quantifies what that role actually contributes: buyers were 32 percentage points more likely to say a sales rep made them feel confident in their purchase decision than to say the same about generative AI, and 39 points more likely to say a rep understood their needs. Whatever independence a buyer exercises earlier in the process, the research suggests confidence and understanding are still disproportionately associated with human interaction rather than AI-assisted research alone.

Forrester’s research points to a related but distinct pattern. In 2025, 30% of buyers cited generative AI as a meaningful interaction type during the final commit stage of a purchase — a substantial figure, and higher than the 17% who cited direct interaction with product experts at that same stage. AI-assisted research, in other words, remains genuinely significant even late in the buying process; it is not simply displaced by human validation as a deal nears close. What Forrester’s broader findings add is that buyers are, at the same time, increasingly turning to peers, experts, and providers specifically to confirm what those AI tools produced — a validation behavior that coexists with continued AI use rather than replacing it.

Self-direction and validation-seeking are not opposing impulses fighting for control of the same buyer. They are two different jobs. One is discovery: finding out what exists, what’s possible, what others have experienced. The other is confirmation: determining whether a specific conclusion, already reached, is safe enough to act on. The evidence suggests many buyers want both, without inconsistency.

The Committee Raises the Bar Again

Even a buyer who has fully validated their own conclusion is often not the only person who has to be convinced. Gartner’s research on B2B buying groups has found that these groups frequently span multiple functions and can number well into the double digits for complex purchases, and that a large share of buying teams experience what Gartner characterizes as unhealthy conflict during the decision process. Forrester’s most recent Buyers’ Journey research puts the typical buying decision at 13 internal stakeholders and nine external influencers, a figure the firm notes grows further for more complex or strategic purchases. The two firms use different methodologies and arrive at different specific counts — a reminder that “how many people are in a B2B buying group” does not have one settled answer — but both point in the same direction: the group deciding is larger and more structurally prone to disagreement than the individual buyer researching alone.

This changes what “confidence” has to mean for the individual who started the process. Believing a solution is right is necessary but no longer sufficient. That belief now has to survive contact with finance, procurement, IT, legal, and whichever executive sponsor has the authority to say no — each of whom may have done their own independent research and arrived at a different, equally confident, equally unverified conclusion. Gartner’s data captures the cost of failing to reconcile this: buying groups that reach genuine consensus are meaningfully more likely to report a high-quality deal outcome than those that don’t, and buying groups with low internal dysfunction were substantially more likely to report high-quality outcomes than those with high dysfunction. The individual buyer’s question has quietly changed from “do I believe this?” to “can I defend this to people who did their own research and may have found something that contradicts mine?” That is a materially harder question, and it is not one that more product information answers on its own.

Content Can Answer Questions Without Resolving the Decision

This is where the problem becomes a communication problem rather than a research-behavior problem, and where it becomes relevant to the people building a company’s content, marketing, and sales-enablement functions rather than only to those studying buyer psychology.

A company can maintain an extensive library of SEO content, comparison pages, case studies, product documentation, webinars, calculators, and an AI chatbot trained on its own materials — and still leave a buyer unable to answer the specific questions their decision actually depends on. Why is this claim true. What evidence supports it, specifically, rather than in general. What situation does this not apply to. What would a skeptical procurement lead find if they looked harder. Who is this genuinely not a good fit for, and does the content admit that anywhere. None of these are questions about whether enough content exists. They are questions about whether the content that exists helps a buyer determine what it legitimately establishes, as opposed to what it merely asserts.

This is a distinct failure mode from having too little content, and it often coexists with having a great deal of it. A comparison page can present ten data points without indicating which three actually matter to a compliance-sensitive buyer facing a specific edge case. A case study can be true and still not tell an evaluator whether their situation resembles the one described closely enough to trust the outcome. An AI-generated FAQ can answer the literal question asked while leaving the buyer no better equipped to judge whether the answer holds up under the kind of scrutiny a CFO or a security team is about to apply. Volume, in other words, is not the variable that determines whether a buyer’s underlying uncertainty gets resolved.

The Better Question for Leadership

The evidence assembled here does not support a claim that AI has made buyers less capable or more easily misled, and it should not be read that way. The evidence reviewed here points to buyers becoming more self-directed and increasingly comfortable using digital and AI-assisted research, including, per Forrester’s data, at the final commit stage of a deal. What the evidence does support is a narrower and more useful distinction: self-direction has changed what kind of help a buyer actually needs, not whether they need any.

The question worth displacing is “how much content do buyers need before they’ll talk to us.” It has an easy, and largely wrong, answer: more. The more useful question is harder to answer but far more relevant to what actually determines whether a deal closes: what uncertainty remains for this buyer after they have already done the research, and what, specifically, would make their existing conclusion sturdy enough to act on and defend.

That question points somewhere different than a content calendar. It points toward what a buyer would still need in order to feel that their interpretation is right, that it applies to their specific situation, that the parts of the evidence which disagree with each other have been accounted for rather than ignored, and that someone credible — a peer, an analyst, an expert, a reference customer — would look at the same material and reach the same place they did. A company’s communication can be extensive, accurate, and well-produced, and still be silent on exactly that question. Whether it is silent on that question, more than how much of it there is, may be the more consequential thing for leadership to know.