If you sell to enterprise buyers, the first call on your calendar this quarter is probably not the first time that buyer evaluated you. A chatbot got there before you did. It pulled together what it could find about your company, set you next to a few others, and gave the buyer a ranked list. Then the buyer called whoever sat near the top.
That is the argument here, and it is aimed at founders and revenue leaders at B2B technology companies who sell to buying committees. For a founder led company, the first sales call is round two. Round zero happens inside an AI answer, and it runs on whatever you can prove in public. Most founders can prove very little there, because their best evidence lives in decks and on calls: how they price, how they handle security, what implementation actually takes. None of that is findable. So none of it counts.
How buyers use AI to shortlist vendors, and how far to trust the research
Three recent studies point the same direction. G2 surveyed 1,076 software buyers in March 2026 and found that 51% now start research with an AI chatbot more often than with Google, up from 29% in 2025. G2 reports that 69% of buyers chose a different vendor than they first planned because a chatbot recommended it, and that one in three bought from a vendor they had never heard of.
6sense's 2025 Buyer Experience Report, built on nearly 4,000 responses, found the winning vendor was on the buyer's Day One shortlist 95% of the time, and that 94% of buyers said their team could rank its shortlist by preference before engaging any seller. Forrester's State of Business Buying 2026, drawing on its 2025 buyer survey, found that generative AI tools were the single most cited meaningful interaction type for researching purchases.
Now the discount. G2 sells review presence and 6sense sells intent data, so both have a reason to like this finding. G2 surveyed software buyers, not every kind of buyer. Everything is self reported. Read these as direction, not as a law of nature. And the same Forrester work shows buyers checking AI output with peers, experts and the providers themselves, and 20% said they felt less confident because the information was unreliable or wrong.
That last point matters more than it looks. It means AI starts the evaluation and people finish it. Which is exactly why the proof has to survive both.
Why founder led companies feel it first
An outbound led company does most of its persuading in private. The pricing logic gets explained on a call. The security answers arrive in a questionnaire after the champion is already invested. The implementation story is whatever the founder says that day. It works, because the founder is good in the room.
Here is the thing though. A buyer's AI cannot sit in your room. It can only summarise what is out in the open. This is inference, not a measured result, and we have not verified how any particular model chooses its sources, so nothing in this piece depends on that. The reasoning is simpler: if the answers are not public, there is nothing accurate to summarise.
Illustration
Picture a security lead asking a chatbot which vendors in your category handle data the way their policy requires. This is an illustration, not a client story. If your answer exists only in a document you send once contract talks begin, the response has a gap where you should be. Nobody rejected you. You were just absent from the list the committee started with.
Round zero and round two are the same process
RivoAxis has argued before that procurement is a second sales process, run by people who never saw your pitch. Forrester reports procurement named as a decision maker by 53% of respondents, so that second process is not a corner case. And we have written about why the buying committee has six different questions, each needing its own artifact.
Put those next to the research and the connection is hard to miss. The questions a committee asks in round two, late and under pressure, are the same questions a buyer's AI is trying to answer in round zero. Pricing logic. Data handling. What implementation costs in time and effort. Whether you fit. If you wait until procurement to answer them, you answer them to a buyer who has already formed a view without you.
So stop treating them as two jobs. The material you build for round two is the material that has to exist in public for round zero. Event technology sellers will recognise the shape of this: association buyers often run a second evaluation on data and security after the RFP is scored. That is an observation about how those deals run, not survey data about how event buyers use AI. We have not found that data, so we won't pretend to it.
The five answers to publish first
Start with the answers a sceptical committee member would ask for before a call, in this order.
How you price. Not necessarily every number. The logic: what drives cost, what the tiers are for, where the edges are. If you build tiers from your own closed and lost deals, as we covered in reading pricing from deal history, you already have the content. It just has never been written down for a stranger.
How you handle data and security. A public version of the packet you would send in procurement. What you have, what you do not have, who to ask. A plain "we don't hold that certification yet, here is what we do instead" usually beats silence.
What implementation takes. Timeline, who does what, what typically goes wrong. Buyers who have been burned are looking for this sentence.
Who you are not for. The fastest way to be believed. It also keeps the wrong buyers out of your pipeline, which your sales team will notice in a quarter.
Proof, with its limits. Customer outcomes with the scope and conditions attached, not a wall of logos. If you cannot back a claim in public, do not make it. A loose claim gets found out by the second call.
The counterargument is half right
The fair objection: this is hype, most buying still starts with Google, peers and analysts, and the people measuring it sell tools that depend on the answer. Some of that is true. The firms behind the numbers are interested parties and the data is self reported. Forrester's own finding, that buyers verify AI output with humans, cuts against any claim that a chatbot decides anything alone.
But run the logic at half the stated effect. If even a modest share of shortlists are shaped before contact, a company with no public proof pays for it in deals it never sees. And nothing on the list above has to be a gamble. Enterprise buyers want pricing logic, security answers and a realistic implementation plan whether or not a chatbot ever reads them, so the work is not wasted. You decide how much to publish, and none of it needs to reveal more than you would tell a serious buyer on a first call.
There are cases where this matters less. If you sell to a handful of named accounts, and every buyer already knows you personally, round zero is a phone call and you can skip most of this. The further you are from that, the more it applies.
A 30 day audit
Week one: write the twenty questions a committee would ask about a vendor like you, across pricing, security, implementation and fit. Ask a few of the major AI assistants those questions, about your category and about you by name. Write down what comes back, and mark every answer that is wrong, missing, or favours someone else.
Week two: pick the single worst gap and publish a plain page that answers it. Not a campaign, a page.
Weeks three and four: tell your sales team that first calls now start at round two. Ask the buyer, early, what they read or asked before they spoke to you. You will learn more from those answers than from the dashboard.
Then repeat the questions next month and see what moved.
Round zero needs an owner
Right now round zero is a sales stage that nobody owns. Marketing does not run it, sales does not see it, and the founder finds out about it when a deal arrives pre shaped by something they never read. Give it an owner this month. The five answers above are enough to start.
If you want a second pair of eyes on what your buyers' AI can and cannot prove about you today, that is a good use of a Revenue Diagnosis conversation with RivoAxis.
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