The room you're not in

In March 2026, G2 surveyed 1,076 B2B decision-makers. Fifty-one percent said they now begin software research with an AI chatbot more often than with Google, up from 29% a year earlier. Seventy-one percent use one somewhere in the process. AI chatbots are the single biggest influence on which vendors make a shortlist.

Then there is the number that should stop you: 69% chose a different vendor than the one they originally had in mind. A third bought from a company they had never heard of before the conversation started.

That is not a change in traffic source. That is the decision moving to a room you are not in.

What actually changed

The old sequence had a shape everyone in enterprise marketing knows. A buyer has a problem, searches, lands on a few sites, reads, compares, fills in a form, and talks to someone. Every step after the landing is a step you can see, instrument, and influence.

The new sequence collapses the middle. A buyer describes their problem to a model. The model reads, compares, and summarizes. What comes back is not ten blue links, it is a recommendation with reasoning attached. By the time anyone visits your site, the shortlist already exists and your position on it has already been argued.

You were discussed. You were characterized. You were compared against two competitors on criteria you did not choose. And none of it appears in your analytics, because none of it happened on your property.

The visibility problem is the smaller problem

The obvious reaction is to optimize for the model. Get cited. Structure the content. Win the answer instead of the click.

That is real, and it is worth doing. It is also the part everyone will do, which means within eighteen months it will be table stakes and worth roughly what SEO is worth now.

The harder problem underneath is that the pre-contact phase is where the buying decision is now made, and almost no enterprise can see anything that happens in it. You know your traffic. You know your form fills. You know which pages got read. You know nothing about the conversation that decided whether you were on the list, and you would not know how to act on it if you did.

This is the part I keep coming back to, because it is not a marketing problem. It is an instrumentation problem, and it sits in the experience layer, which is product.

Enterprises are not short of intelligence

Here is what I have found consistently at enterprise scale: the signal is already there. It is in the product telemetry, the support tickets, the sales notes, the docs traffic, the community threads, the churn interviews, the partner conversations. Large companies collect enormous amounts of evidence about what buyers are trying to do.

What they do not have is any mechanism that turns that evidence into an action inside a reasonable window. It goes into a warehouse. Someone runs a report. The report goes into a deck. The deck gets presented next quarter. By the time it produces a decision, the situation it described has changed.

So the problem is not that enterprises lack intelligence. It is that they are not actioning the intelligence they already have. Adding another source of signal to a company that cannot act on its existing signal produces nothing except a larger warehouse.

That reframing changes what you build. The question stops being how do we capture more and becomes what is the shortest path from a signal appearing to something changing because of it.

What this means for the experience layer

Three things follow, and none of them is a content strategy.

Your material has to be legible to a reader that does not render pages. Not just crawlable. Structured, current, and unambiguous about what you do and who it is for. If your positioning only makes sense when a human sees the layout, it does not survive summarization. Most enterprise sites fail this badly, because they were built to impress a person who is already on the page.

Intent has to be captured before the form. The buyer who reads three docs pages, the product comparison, and the pricing page has told you a great deal, and most companies do nothing with it until that person identifies themselves. The identification step is precisely the step the new sequence removes.

Somebody has to own the loop. Signal that arrives, gets interpreted, changes something, and produces a new signal. That is a product function, not a reporting function, and it fails the moment it becomes a dashboard that people look at rather than a mechanism that does something.

The honest version

I will say plainly that this is the bet I am building on. At DEMMANND the premise is that enterprises now sell into AI-mediated markets, that buyer intent becomes visible earlier than the funnel assumes, and that every signal returned to the graph compounds. I would rather be transparent that I have a position than pretend I arrived at it neutrally.

But you can test the argument without believing my conclusion. Ask your team what percentage of your pipeline was shortlisted before anyone in your company was aware the buyer existed. If nobody can answer, that is the gap, and it exists whether or not anyone builds a product for it.

This site is a small, cheap version of taking it seriously. Everything on it is generated from one record and served as plain text as well as HTML, so a model reading me gets the same material a person does, in a form it can actually use, rather than a summary of my layout. That took an afternoon. It is not a strategy. It is the minimum.

The buyer arrives already decided. The only real question is whether you were in the conversation that decided it.

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Figures from G2, The Answer Economy: 2026 AI Search Insight Report, fielded March 2026 across North America, EMEA, and APAC, n=1,076, with 39 qualitative interviews. Report · Announcement