Revenue Builders · 26 Mar 2026 · From the week of 23 March
AI Adoption Requires Leadership Discipline, Not Just Technology with Marcy Stoudt
These are notes on the conversation, checked against its transcript. The episode itself has the full discussion.
In brief
Marcy Stoudt, founder of Revel Companies, joins hosts John McMahon and John Kaplan of Revenue Builders to discuss AI adoption as a leadership question rather than a technology purchase. She describes how a mentor pushed her past treating AI as a tech stack decision. Kaplan, citing her blog, notes that productivity gains break when work passes to people working at a lower level of AI use. The conversation covers how AI is changing sales prep, coaching and hiring. Her central argument is that leaders who wait on IT or governance, or let each seller adopt AI separately, will lose ground to competitors who drive cross-functional alignment and fix inefficiencies. The hosts add points on domain expertise in AI tools, over-scripted questioning, and sales manager responsibilities.
For founders
- AI adoption is a leadership decision about how work gets done, not only a technology or tool purchase.
- Productivity gains from AI are lost when work moves from a high-capacity user to someone not working at the same level.
- Fix inefficiencies that span two or three departments through cross-functional leadership rather than waiting on a generic AI governance program.
- Build hiring around a success profile of competencies, success behaviors and evidence, and assess candidates against it rather than relying on resumes.
For revenue leaders
- Run a two-column inventory of strengths against where the team is stuck, slow or losing deals, and treat the complaints as the list of what to automate.
- Update the sales script and the top problems you solve, because customer expectations about AI have changed.
- Unify how sellers prepare, since each rep using a personal AI can produce different questions and dilute one message.
- Use AI to clear administrative time so managers have more capacity for coaching, including reviewing customer conversations and giving feedback.
- Ask references what one thing you can help a new hire with most, since candid answers come from people who want the hire to succeed.
What was said 21, most useful first
AI productivity gains break when work is handed from a high-capacity person to someone working at a much lower level of AI use. Listen
Kaplan, referencing Marcy's blog, says that if one person has 10x capacity and the work stream is handed to someone doing 1x, the result is a train wreck, especially for the customer experience. He argues that people need to look at it at the same workflow level for the gains to hold.
“If you have one person with 10x capacity And that gets handed off. That work stream gets handed of to somebody who's doing one X capacity, it is just an absolute train wreck in my opinion”
Listen to the episode Sales process & deals Link to this Report a problem
Run a two-column inventory of where the team is strong versus where it is stuck, slow or losing deals, then look for problems that span several departments. Listen
Marcy describes an exercise she uses with clients: on one side, list strengths; on the other, list where you stock, where you are slow and where you lose. The complaints show what to automate, and a problem that intersects two or three departments is where cross-functional AI leadership should focus rather than generic governance.
“on the right side you take an inventory and you can put in where do we stock or where are we slow? Where do we lose?”
Listen to the episode Sales process & deals Link to this Report a problem
When every seller uses their own AI to prepare, their discovery questions diverge, and the leader has to unify the team's approach. Listen
Marcy says this is a bigger risk for large sales organisations because communication is usually tight, but now each rep has a different variation of the trap-setting questions. She compares it to the Braveheart charge, where troops run in many directions, and says a leader is needed to build AI fluency, fix inefficiency and get people on board with one direction.
“now everybody's using their own AI to prepare. So now those questions, like those trap -setting questions that you really want to hold to the right moment, everybody has their own variation of it.”
Listen to the episode Sales team, hiring & comp Link to this Report a problem
Build the hiring success profile from competencies, success behaviors and evidence of success in the role, and test every candidate against it. Listen
Kaplan says Force Management created a success profile for a major recent hire, and candidates and interview conversations were both measured against it. He says the profile is table stakes and that hiring decisions should be evidence-based rather than made on general impressions.
“for me the success profile is to center of the universe It's that you know The competencies and success behaviors Of what success looks like evidence? Of what Success looks like in the role”
Listen to the episode Hiring & team building Link to this Report a problem
Ask references what one thing they think you can help a new hire with most, because the answer is more candid than a standard reference question. Listen
Kaplan says he asks every reference the same question after saying they like the candidate, and that it worked well in a recent hire at Force Management. He says references who want their friend to succeed give honest answers about areas where the person struggles.
“I always ask the same question. Hey, we like XYZ person also. We like them a lot. What is the one thing that you think I'll be able to help them with the most?”
Listen to the episode Hiring & team building Link to this Report a problem
Coaching runs in four steps: tell people what is expected, show them how to do it, watch them do it, then give feedback, and AI now makes watching and validating far easier. Listen
The speaker says the watch step is where coaching usually breaks down because managers cannot be in every call. AI tools now allow managers to review customer conversations and validate what is happening, which removes the excuse for not coaching well.
“You first have to tell somebody what's expected of them. You next have to show them how to do something. You Next have to watch them do something This is the one that typically where everything falls down”
Listen to the episode Sales team, hiring & comp Link to this Report a problem
Overly programmed call scripts and pre-planned questions can stop reps from listening to customers, so preparation should inform questions rather than dictate them. Listen
McMahon recalls reps in the car telling him exactly what to say and ask on a call, and replying that he couldn't do that because it meant he wouldn't be listening to the customer. He says that when he went along with it as a young manager, he found he was thinking about what he would say next, and that questions asked naturally sound more authentic.
“I wasn't listening to customers only thinking about what I was going to say or what I Was gonna ask so I think there's real danger there.”
Listen to the episode Sales team, hiring & comp Link to this Report a problem
AI vendors often have technology expertise but lack domain expertise, which the speaker calls human factor knowledge, and that gap matters in sales. Listen
Kaplan says AI companies approached Force Management wanting to be partners because they were experts in technology but lacked sales domain expertise. He argues that customers have judged sellers in the same ways for thousands of years, so the human factors of selling must be built into the tools.
“They were the experts in the technology and what they didn't have was domain expertise or what I call human factor knowledge.”
Software development got AI tools first because practitioners embedded their domain knowledge into the tools, and sales roles are expected to follow the same path. Listen
McMahon says software developers took their domain expertise and embedded it in AI tools, and that the same is expected to happen across other functions. He predicts that sales-specific tools built on domain expertise will emerge, though he notes that current tools are mostly general large language models.
“The reason I think that software development occurred first is because software development people know software development so they took their domain expertise and they took the time to embed it in an AI tool.”
Treating AI as a technology stack decision misses the leadership questions of how to position, win and invest. Listen
Marcy says her first instinct was to ask what AI tech stack to use. Her mentor Edwin pushed back, asking why she was thinking like that, and told her there was no license agreement and to figure it out. She says she then realized the real questions were what the work looks like today, how to position the company, how to win, and how to invest to make that happen.
“But eventually I realized you know i need to hire What does it look like for me today? How do I position myself how do I win and then How do you invest to make that happen”
Listen to the episode Strategy & market Link to this Report a problem
Waiting on IT or governance to lead AI strategy lets smaller competitors take share. Listen
Marcy says her biggest fear for CROs at large companies is that they are waiting for governance and IT teams to produce a solution while smaller competitors move ahead and take share. She treats this as a reason not to wait for a formal program before acting.
“my biggest fear for our CROs at large companies as you're waiting for your governance and your IT team to come out with solution while your smaller competition has just taken share”
Listen to the episode Leadership & culture Link to this Report a problem
The old sales script needs updating because customer expectations around AI have changed, and sales managers should bring that voice of the customer back to leadership. Listen
Marcy says expectations have changed even in staffing, where clients now want better summaries and better scorecards. She says managers who take a year to catch up to these needs will lose their competitive edge. She argues the top problems the company solves need to be updated and the customer voice kept at the centre of the room.
“They want better summaries They want better scorecards like there's so much difference”
Listen to the episode Sales process & deals Link to this Report a problem
Alignment is the second most important factor after AI curiosity, and only a human leader can create it. Listen
Marcy says companies are losing people because each function prepares slightly differently and waits for case studies from marketing or features from product. She says a strong leader can pull the right people into the room and get them working on the problem together.
“the second most important thing other than AI curiosity is alignment. Only a human can create alignment”
Listen to the episode Leadership & culture Link to this Report a problem
Spend 20 minutes a day learning AI by copying useful material into an LLM and asking it to teach you how to apply it. Listen
Marcy says she commits to 20 minutes a day of AI learning and subscribes to a number of newsletters, many of which are vendors selling to her. She used to call her mentor Edwin about such offers. Now, when something is interesting, she copies it into her main LLM and asks it to teach her how to do it.
“Copy paste uploaded into your main go -to one and say teach me how to do this”
He learned AI by applying it to specific productivity, capacity and speed problems, not through conversations about it. Listen
Kaplan says he applied AI to the challenges where the promise was productivity, capacity and speed, looking at what caused him problems in those areas as a seller. He says he did not really learn the technology until he applied it to those problems.
“At least in my case, I really did not learn until I applied it”
Load a custom AI project with the strategy books you follow and instruct it to challenge your thinking rather than accept your answers. Listen
Marcy says she set custom instructions for her AI strategist, uploaded the strategy books she follows and her core thinking, and told it never to accept an answer based on what she says. She says the setup keeps her from feeling stale and pushes her to think bigger before calls.
“I uploaded the strategy books that I follow. I uploaded like some main core thinkings. And then I say have it challenge me never accept an answer based on what I say always thinking”
Writing that used to take hours now takes under 20 minutes when dictated as voice notes and processed with AI. Listen
Kaplan says he dictates voice notes while walking, riding a bike or at the gym, for pieces like his Monday motivations. Output that used to take him hours to write now takes probably less than 20 minutes. He says the notes need to be useful and purposeful rather than just vomiting up ideas.
“Those things would have taken me hours to write in the past. They take probably less than 20 minutes now from me which is fantastic.”
Sellers will judge employers on their level of AI adoption and will leave for employers with more productive tools. Listen
Marcy says sellers calling her about companies increasingly ask about the productivity tools available to them, and that companies will be judged on their level of adoption whether they know it or not. She says people will leave for employers that give them tools to be more productive and make their jobs easier.
“I'm telling you that you are going to be judged whether you know it or not about your level of adoption and the things that we're talking about cause people are just gonna peace out”
Listen to the episode Sales team, hiring & comp Link to this Report a problem
With AI-written resumes, the ability to interview and read a candidate's fit is becoming the key differentiator in recruiting. Listen
Marcy says job descriptions fed into AI produce near-perfect resumes, so noise is higher than ever. She says AI can speed up sifting candidates, but the discernment that comes from conversation with the person cannot be automated.
“So that discernment that you go through of really being able to interview and get a good read for who the person is going to fit is one of the most important things.”
Listen to the episode Hiring & team building Link to this Report a problem
Working preferences such as how often someone wants check-ins are an overlooked culture-fit factor in hiring. Listen
Marcy says small differences in working style, such as the need for frequent check-ins, often decide whether a new hire succeeds. She says her own preference for fewer check-ins could read as dismissive to team members who want them, while she would feel micromanaged working for someone with the opposite style. Her team's AI coaching tool includes a preferences test.
“I actually don't like a lot of check -ins with people but i'm very personable.”
Listen to the episode Hiring & team building Link to this Report a problem
Position AI as a thought leader in the room that gives options, the way a large consultant would, rather than a helper for emails and slides. Listen
Marcy says many teams use AI as a happy helper for better emails or PowerPoint decks, which misses the bigger win. She suggests treating AI as a thought leader that helps find cross-functional inefficiencies and presents options to leaders.
“that's the promotion of AI as your thought leader versus a person that's like happy helper, better emails maybe do PowerPoint or something like that but you really want it to be more of a thought leader that's giving you options just as if you hired a big consultant.”