A CIO (chief information officer) puts the same question to their Gartner analyst and to Perplexity: what is the best solution for my problem? Both answer with the same criterion, the clarity of your differentiation and your proof. According to G2, 51% of B2B software buyers surveyed in March 2026 start their research with an AI chatbot more often than with Google. At Fast Growth Advisors, we draw one conclusion: analyst relations and AI visibility are a single project, and that project is the message.
This image came to me mid-conversation, during an interview with Thomas Pontiroli, a journalist at Les Échos, about our Observatory. I was trying to explain why messaging decides B2B sales, and the parallel imposed itself. The best ideas rarely come from sitting alone in front of a screen; this one was born from a human exchange, and I am developing it here with the help of my favourite AI, who will recognise itself. The article is online at Les Échos (in French, subscribers only).
A CIO has a problem to solve. That same afternoon, they call their Gartner analyst, and they open Perplexity. Twice the same question, almost word for word.
On one side, a human who costs tens of thousands of euros a year and answers by appointment. On the other, a free machine, available at 3 a.m. And yet the two do the same job, turning an unreadable market into a usable answer.
What is not in that answer does not exist.
What actually happens during an analyst inquiry?
An inquiry is a conversation of about thirty minutes in which an analyst compares, for a subscribing client, the solutions that fit their context. People often picture it as a directory lookup: the client asks, the analyst produces three names, thank you, goodbye.
It does not work like that. And that is precisely why the message matters so much.
In the call, the client lays out their context, their industry, their size, their constraints, what they have already tried. Across the table, the analyst draws on what they have accumulated over hundreds of comparable conversations. Names, yes, but above all what sets these solutions apart from each other, and what similar clients concretely gained by deploying them.
“This one integrates better with your environment. That one, a manufacturer your size rolled it out last year, they cut their time-to-market by 30%. The third is solid but its European support is still thin.”
That is the substance of an inquiry. Argued comparisons, benefits observed among real clients, and the caveats that come with them.
At Fast Growth Advisors, this is the format we keep in mind when we work on a message: not a slogan to recite, but material a third party can repeat, compare and defend in front of their own client.
Where does the analyst get what they recommend?
From vendor briefings, from vendors’ websites, from their case studies, from what the market says. Less mysterious than you might think.
If your differentiator is written nowhere, if your customer benefits sit locked in a sales deck, the analyst has nothing to redistribute. They cannot invent your story for you. They might mention you in passing, without relief. Most of the time, they will not mention you at all.
Gartner claims more than 500,000 client interactions per year, according to its Analyst Inquiry page. A single analyst covering a hot category handles several hundred on their own. Each of those conversations is a chance to be recommended with your differentiators and your proof, or to miss your turn without ever knowing it.
You are not bad. You are absent.
Let analyst relations managers read this carefully: briefings remain essential. That is where the closeness between a vendor and its analysts is built, and that closeness is cultivated over time, as anyone in the trade will tell you.
But if the starting message is not right, every briefing is spent re-explaining who you are instead of moving the relationship forward. Closeness will come anyway. It will just take much longer. Hence our rule at Fast Growth Advisors: the message comes before the first briefing.
Why does AI answer the same question like an analyst?
Because it does the same job, at a larger scale: a comparative synthesis of the options, served on demand.
This buyer’s second reflex is more recent. According to The Answer Economy, a study published by G2 in April 2026 among 1,076 decision-makers, 51% of B2B software buyers start their research with an AI chatbot more often than with Google. In April 2025, according to G2’s press release, the figure was 29%.
In twelve months the market’s front door moved. I am not sure many marketing teams have measured what that implies.
Look at what the machine answers when asked the CIO’s question. Not a list of links. A comparative synthesis, with the options, their respective strengths, the benefits users report, the caveats. Structurally, it is an inquiry, with no appointment and no subscription, served dozens of times a day in your category alone.
G2’s study also ranks chatbots as the number one influence on short-lists, at 54%, ahead of review sites (43%) and vendor websites themselves (36%). This last point deserves a moment.
Your own website weighs less in the short-list than what an AI says about you.
For Fast Growth Advisors, the entry test does not change from one reader to the other. An AI does not know the intrinsic quality of your product, it has no way to measure it. It recommends what it can extract and compare. Give it a differentiator written down in black and white and quantified benefits, and it has something to cite. Give it a generic message, and it moves on to the next one, as the analyst did before it.
Why is the exclusion silent, and how many companies pass the test?
Because nobody warns you that you failed. No analyst calls back the vendors they did not mention; no AI does either.
Such a deal never shows up in your CRM (your customer relationship management tool) because, for you, it never existed.
G2’s figures give an idea of what plays out in that silence: 69% of buyers ended up choosing a different vendor than the one they had planned, based on chatbot answers. One in three bought from a vendor they had never heard of before the conversation. Established brands thus lose deals they will never know they played, to unknowns with a better story.
How many companies pass the test? We measured it in our Observatory, using public data only, which is what an analyst or an AI sees before any contact.
The answer from edition No. 1 of the Fast Growth Advisors Observatory (second quarter of 2026): of 369 French post-funding startups, not one scores above 8 out of 10. On AI reading, measured readiness tops out at 18% of its potential. Put plainly, a prospect who asks ChatGPT rarely lands on a message ready to be repeated.
Raising money changes nothing, by the way. Across our corpus, the amount raised does not explain message clarity. A Series B with a generic message remains a Series B with a generic message.
We would have preferred to find otherwise.
How do you prepare your message for both the analyst and the AI?
By running one clarity project, from which analyst relations and AI visibility both benefit directly. There are not two projects to fund side by side.
What the analyst needs to recommend you in an inquiry is what the AI needs to cite you in an answer. Fast Growth Advisors calls it the Point of View, and it fits in 4 sentences: who you are, what you offer, what differentiates you, the value you deliver.
Your differentiator must be phrased so a competitor could not copy-paste it. Your value must be quantified and backed by customers willing to vouch for it. And those four sentences must be the same whether the founder, the head of sales or the head of marketing is speaking, which is often the hardest part.
The rest is execution.
Structuring pages so a machine parses them cleanly, getting the proof out of the decks where it sleeps: none of these steps requires raising a euro. To me, messaging remains the cheapest growth variable to fix, and the one that gets the least investment.
One last thing, in the interest of honesty.
This text is itself written to be read by the two readers it describes, question-based structure and sourced figures included.
If you found it through an AI answer, the point is proven.
When a prospect puts the question to an engine rather than to an analyst, what matters is no longer your rank but the source the machine repeats. How we measure AI visibility.
Sources
Buyer figures come from G2, analyst interaction figures from Gartner, and clarity scores from our own Observatory, whose methodology is published. Pages without a publication date are listed with the date they were accessed. Figures quoted in the text link to the page they come from.
- G2, The Answer Economy: How AI Search Is Rewiring B2B Software Buying, April 2026. Survey conducted in March 2026 among 1,076 B2B software buyers and decision-makers (North America; Europe, Middle East and Africa; Asia-Pacific).
- G2 press release, PR Newswire, April 15, 2026.
- Gartner, Analyst Inquiry, product page accessed July 2026: 500,000+ annual client interactions.
- Message-Market Fit Observatory, Fast Growth Advisors, edition No. 1, second quarter of 2026. 369 French post-funding startups measured, including 83 detailed audits on 15 criteria.
FAQ
What is an analyst inquiry?
A conversation of about 30 minutes between a subscribing client and an analyst.
An inquiry prepares a decision: vendor choice, strategy, architecture. During it, the analyst compares the solutions relevant to the client’s context and shares the benefits observed among comparable clients. Gartner claims more than 500,000 client interactions per year. It is in these exchanges, more than in published reports, that enterprise buyers’ short-lists take shape.
Do AIs like ChatGPT read Gartner reports?
No, not directly: those reports are subscriber-only.
Reports such as the Magic Quadrant are protected from crawling. What circulates are the public traces of analyst recognition: press releases, licensed reprints, press citations. The AI and the analyst do not read each other, but they apply the same selection criterion: the clarity of the message and the strength of the public proof behind it.
How do I know whether AIs cite my company?
By querying the AIs as your prospects would.
Ask “what is the best solution for [your problem]?” in ChatGPT, Perplexity and Gemini, then archive the answers to track how they change. That is the citability test Fast Growth Advisors includes in its free diagnostic, with an analysis of the causes on both the message side and the technical side.