The Third Participant on the Call: When AI Vets Your Fractional Sales Leadership Partner
Our discovery calls with fractional sales leaders have acquired a third participant. It never speaks, it does not appear on screen, and it has already formed an opinion before anyone says hello.
A majority of the fractional executives who find Vendux today do not find us through a referral, a LinkedIn post, or a conference. They find us through their preferred AI model. And by the time we meet, that same model has handed them a script.
How the Search Begins
Executives have been generous enough to share the prompts that led them to us. A few representative examples:
"I'm a fractional CRO with 20 +years in B2B SaaS. Which firms match fractional sales leaders with SMB clients, and which are worth my time?"
"Compare firms that place fractional sales executives. Include fee structures, vetting process, and reputation."
The Script
Within the first ten minutes of many calls, we now hear some version of the following, frequently in this order and occasionally word for word:
How do you source clients, and how many active engagements do you have?
What does your vetting process look like, and what percentage of applicants are placed?
What is your fee structure, and who pays you: the client or me?
Do you require exclusivity?
Who owns the client relationship once the engagement begins?
What happens if an engagement is not working?
What can I do to increase my chances of being placed?
These are good questions. That is precisely the point: they are good, generic questions, and when five different executives ask them in the same sequence in the same week, the similarity is striking.
The process rarely ends with the call. It is reasonable to assume that many executives then paste their notes, or a transcript, back into the model and ask for an assessment. Somewhere, a scorecard on Vendux is being generated from my answers.
Is all of this a good thing? IMO, mostly, yes. But the trade-off deserves an honest look.
What the Executive Gains
A higher floor. No one forgets to ask about fees, exclusivity, or relationship ownership anymore. For an executive new to fractional work, that alone can prevent an expensive mistake.
Breadth and speed. AI surfaces options an executive would not have found through their own network, and compresses days of research into minutes.
A counterweight to charm. Sales leaders are, ironically, susceptible to a good pitch. A structured list keeps the conversation anchored to substance rather than rapport.
A second opinion. Even an imperfect post-call assessment prompts reflection that might otherwise not happen.
What the Executive Loses
Signal. A discovery call runs in both directions. We are assessing the executive as carefully as they are assessing us, and the questions someone asks reveal how they think, which is exactly how they will run discovery with a client. A borrowed list tells us the model is thorough. It tells us very little about the executive and their fractional maturity.
Relevance. The most important questions are specific: your ideal client profile, your capacity, the kind of engagements you want more of and those you want fewer of. A general-purpose model cannot know these unless you tell it, and most prompts do not.
The follow-up. Scripted conversations tend to move to the next question rather than the next layer. The most revealing moment in any vetting conversation is the second "why," and a list does not ask it.
Judgment in the assessment. A general model scoring a transcript evaluates what was said, not how it was said. It cannot detect conviction, hesitation, or chemistry, and it rewards answers that resemble the answers it expected. A firm with an unconventional but better model may score lower than one that recites the expected talking points. Models can also be confidently wrong about specific firms, blending outdated or conflated information into an authoritative-sounding verdict.
The muscle itself. Outsourcing evaluation repeatedly has a cost to the evaluator, a theme I explored in Is AI Making Us Dumber?
Where I Land
On balance, this is a positive development. Informed executives make better partners, and we would much rather meet someone prepared than someone who has not considered what they are signing up for. The problem is not using AI to vet a partner. The problem is letting it do the vetting.
This is the same balance we advise clients to strike in AI in Sales Leadership: Navigating the Critical Balance: AI should raise the floor, never set the ceiling. For fractional executives evaluating any firm, including ours, five practical suggestions:
Use AI for research, not for the relationship. Let it build the shortlist; reserve the conversation for yourself.
Edit the list. Keep the three questions that matter most to you and add two that only you would think to ask.
Listen for the follow-up. Your best question will be the one that is not on the page.
Challenge the assessment. Ask the model to argue the opposite conclusion and see which case is stronger.
Verify the facts. Confirm anything the model asserted about a firm before relying on it.
So, bring your AI-generated questions to our next call. We are happy to answer every one of them. Then let us talk about the questions only you could ask, because that is where the human side of the conversation begins, and where a good match is actually made.