Gartner's forecast that 95 percent of sellers' research workflows will begin with AI by 2027, against under 20 percent in 2024, is usually read as a productivity story. There is a second effect worth naming.
Convergence
When most firms in a category research the same prospect using the same class of model over the same public material, the briefings converge. The same framing, the same three pain points, the same opening question, arriving from four suppliers in the same month.
The buyer notices this before the sellers do, because the buyer receives all four. On their ninth purchase in the category, four near-identical approaches inside a fortnight is not evidence that the market understands them. It is evidence that the market is reading the same summary of them.
The part that stays scarce
What does not converge is anything that requires access the model does not have. What this specific buyer said in a prior conversation. What their previous supplier did badly. What their internal disagreement is. A view about their situation that could turn out to be wrong.
That is the same allocation question in a different setting. Assembling the public picture is production work and should cost close to nothing. Forming a position on it is judgment, and it is the only part the buyer cannot get from four other firms.
The other half of the convergence
If sellers research this way, buyers research this way too. That makes what a model can find about your firm the first impression in a growing share of cases, formed before any human reads a word you wrote.
A firm whose public material is generic will be summarised generically and grouped with its competitors, accurately. A firm that has published a specific, checkable position will be summarised with that position attached, because a summariser keeps what distinguishes.
What we take from it
The forecast is a prediction and we treat it as one. The direction is already observable, though, in how uniform inbound approaches have become, and the response does not depend on the exact figure being right.
Our working thesis is that the value of having a written, distinctive position rises as research converges, and rises for both reasons at once: it is what stops your outbound sounding like everyone else's, and it is what a machine carries when it describes you to someone who has not met you.