Ep. 133 - Frontier AI: What the Highest-Performing Sales Organizations Are Doing Differently with Bob Kelly - Part 1

Speaker A: 1, 2, 3, 4. Welcome, everyone, to the Selling Intelligence podcast, where revenue leaders learn how to navigate the AI era with clarity and confidence. I'm, um, Marc Pischrouzzi, your co host.

Speaker B: And I'm KK Anderson. Join us, uh, each week as we break down the strategies, decisions and execution moves that are driving growth in today's market.

Speaker A: Welcome to Selling Intelligence. I'm Mark Petruz Kay.

Speaker B: And I'm KK Anderson. Every week we bring you conversations with operators who have been in the room and come out with something worth using the very next day.

Speaker A: Our guest today just completed a benchmarking study of 111 sales organization and what on AI adoption. The findings are not what most leaders expect. Only 4% of firms have no one using AI at all. But only 9% qualify as what the research calls frontier adopters. And, and those 10 firms are outperforming the rest of the field by, on average, 27 percentage points on sales objective achievement, 19 points on individual quota attainment, and nearly double the rate of sufficient selling capacity. The question this research forces is not whether your team is using AI, it is whether they are using it in a way that actually moves the numbers.

Speaker B: Bob Kelly is founder and chairman of the Sales Management Association, a global independent professional organization serving more than 10,000 sales leaders. He has no product to sell and no platform to push, which is exactly why this data matters. Welcome to the show, Bob. We're happy to have you.

Speaker C: Thank you so much for having me. It's so nice to be with you.

Speaker A: So, Bob, your research covers over 100 companies. But before we get into what leaders are doing, give us the honest snapshot. What is the typical sales organization actually doing with AI right now? And, and how does it compare to what people say, uh, they're doing and what the media outlets are saying people are doing as well?

Speaker C: The word I would use is dabbling. The typical, uh, sales organization is dabbling with AI as opposed to integrating it in a pervasive and sort of formal way in the work streams in the firm. This is a reflection of the uneven nature of how AI affects the work in general and including sales work. But the interesting thing is to understand just how few firms are ignoring AI or are untouched by AI. When we look at the adoption curve and, uh, history of other technologies, CRM, for example, or other platform technologies, they've taken much, much longer to gain a foothold in most organizations. We're seeing very fast pickup in the use of AI, uh, even if that use is uneven.

Speaker B: So, Bob, when we had our preparation conversation for this podcast, you used a phrase that I hadn't heard anywhere else, and I thought it was fabulous. You said, there's a lot of machine stench, machine. So walk us through, like, what is that? And why is it showing up so broadly in this research?

Speaker C: Great term, isn't it? I was just about to think of that term when I heard someone else use it. So I naturally adopted it as if it were my own. But it is plenty descriptive, right? And I think we all have encountered AI generated content. I mean, the more common term is slop. We see it in social media, but we also see it in our inboxes. We see it in, uh, work product within the companies that we work for. And its problem is that it represents an inauthentic product. And so this, when used inappropriately or in the wrong context, actually I believe does more harm than good. It communicates sort of in authenticity rather than clarity and equality.

Speaker B: Uh, everyone, AI. It's like AI gave everyone a Ferrari, Ferrari's on the road and no one can move, and everyone sounds the same. So it's figuring out how do you take that superpower and that super intelligence and leverage it in a way to create differentiation rather than the stench of sounding the same.

Speaker C: I think the mistake so many make is that they're using AI to substitute for their own voice or work product, and when that happens, they're pointing out their own superfluity. Do we need a human if we're just going to have machines generate communication? So I think when used appropriately, we use it to augment our abilities, our voice, our, uh, productivity. And when we use it poorly, we've. We make the mistake of substituting machine, uh, generated product for something that we should have more say in.

Speaker A: So, Bob, you mentioned in this study that only 4 to 6% of companies are avoiding AI entirely. That actually concerns me that there is. Everybody's diving in, and only a very small percentage are not. But when it really comes down to it, there's still a huge disparity between those frontier adopters, as you described, and the laggards, the rest of the pack, is that the gap between the two of them growing. And how fast. How fast is that growing and changing?

Speaker C: Well, the answer is very, very fast. The study, uh, that we did was concluded, I guess about three months ago. It's likely out of date. So we see these adoption and the development of the products that we're even talking about moving so quickly. The, um, the thing to keep in mind is that, or a relevant point here is that so many AI Products are freely available and they are in the general population. In fact, the most widely adopted tools are those that anyone can pick up, chatgpt or Perplexity or any of these sort of language based chat, uh, based tools. And so we see lots of people picking them up, fooling around with them. And this is unlike other technology platforms that we've seen impacting the sales organization like CRM or SPM or sales enablement or any many, many other tools. So this does beg the question, will this be a phenomenon driven by consumers personal adoption, will it be democratized in that way? Or will uh, companies be required to adopt sort of institution wide highly controlled platforms to provision AI?

Speaker B: It's really interesting and one of the incredible benefits of leveraging AI in your sales organization is that you can take that trib knowledge of your best, your top sales performer and figure out what it, what is it that makes them the best and then automate some of those research tactics or techniques or processes in your, in your AI agentic workflow. And that's something you could never do inside of the confines of uh, a, you know, salesforce or HubSpot.

Speaker C: Yeah, this is the promise. This, that idea gets sales leaders excited. In practice it's uh, I don't know that we're quite there yet, but in general we see companies adopting the easy tool to pick up. These are chiefly language based models and they're used for language oriented tasks, things like communication and crafting emails, sometimes quite derivative machine stench sort of emails, but also doing things like uh, understanding, researching prospects and markets. And where we see less adoption so far is in the things that require more advanced tools, including agentic and sales specific tools. And so what we found in these so called frontier firms, which represent Maybe the top 90th, the 90th percentile of adoption and usage, is that they're much more likely to use tools that are customized to sales work and include agentic elements. So they're actually automating work and incorporating AI capabilities within those automation streams.

Speaker B: Talk us through what these frontier adopters in the research that you talked about. So what was the, what was, tell the audience what was the criteria you used to define them? And like what is that? What does a frontier organization actually look like in practice?

Speaker C: Well we had uh, as you pointed out, roughly 100 firms in the study. So we looked and we in the study measured their rates of adoption, the frequency with which the typical salesperson uses tools and the kind of tools that they use. So we took those firms that had the highest rates of adoption and uh, in which salespeople are using tools most frequently and in which they are using tools, they're using the general purpose tools, but they're also using agentic tools and custom uh, tools that are geared toward sales specific tasks. And so those, those are the basic criteria. We identified roughly 11 to 12 firms in that group and branded um, them Frontier sales organizations. We did this in part because the sponsor of this research who underwrote the research was Microsoft. And they're using this term in the way they are marketing solutions to frontier firms. So in part we did this to curry favor with our sponsor, but also because this term frontier has been widely adopted to describe the latest models that are used in these solutions. But also the sort of uneven and perhaps dangerous nature of adoption itself. Ethan Mollock's great term, the jagged frontier is widely used to describe how it's an uneven place, being on the edge of adoption with these tools. The tools do many things really well and other things, easy things weirdly quite poorly. So it's a shifting sort of uneven place to be. And that's why we like the term in addition to describing those leaders in organization, in our economy, in sales organizations that are adopting AI.

Speaker A: So Bob, I kind of echo that, that thought process and what I'm starting to see, like everyone, right, I jumped in early to just the whole opportunity of AI and what you can do and the research capabilities and then move very quickly into the agentix side and really creating agents and building them for our clients. And that moved to a whole nother level of productivity. But we learned something in that phase two and that is how valuable all the systems and tribal knowledge that a company has and how for AI really to be playing its best game, it's got to have that information as well. So that brings us to applied AI, right? That's kind of where the terminology is coming together. And when you can do that, uh, as an organization we at AGS do that for our clients. We do that with a couple of our partner organizations that we work very closely with, like Human Gentic. When you can go to that next level and really integrate within the systems that are already in place takes you to a whole nother level. Did you see that at all in this study? Uh, and what's your overall point of view on that?

Speaker C: We didn't go super deep to understand the degree to which firms are integrating agentic solutions within their own environments. We did sort of investigate. We ask, are you employing Agentix solutions? And we ask are you using custom solutions that are sales Focused. We also ask if they are making use of platform solutions, existing solutions like CRM or spm sales performance management platforms in which there are embedded AI capabilities. This is likely the most, this is the likeliest way that many firms will begin adopting these agentic solutions. Kind of pervasively. They will exist within the comfortable and secure minds of a platform in which they're already using. Which solves the chief concern about distributing this capability across the enterprise, namely security, governance, the keeping data secure and understanding just how people are using the solutions.

Speaker B: I thought it was incredible that the data showed that 90% of frontier organizations met or exceeded their sales goals in the preceding 12 months versus 63% of the non frontier firms. That's compelling.

Speaker C: Yeah, it's a big number. So it suggests that frontier firms, so called frontier firms are much more likely to be productive than more laggard firms. I mean it's a clear delivery of the promise of AI ah, as it relates to productivity.

Speaker B: Right. Really incredible. Okay, so your research study also talked about selling capacity. Um, and it's, let's see the data set. I believe it was 60% of frontier firms say they have sufficient capacity to cover available opportunity compared to 32% of non frontier firms. I'm assuming, Bob, that's going more towards the productivity as well.

Speaker C: So this is a really interesting finding. Again, this data is self reported, so it is subject to the caveats that you'd have in such a study. But it's almost the only way to conduct quick benchmarking research. But the fact that these firms are M so much more likely to indicate that they have sufficient capacity does suggest an impact of using AI that we all are hoping for, which is, uh, it allows us to do our work faster. Now if you follow the logic through, uh, it's reasonable to suggest that this surplus capacity will be short lived. So where we are perhaps in the curve of adoption of AI and M sales is that we're using AI to great effect to make salespeople more productive. But we haven't redeployed that capacity in ways that are likely to follow on from AI adoption. We're likely to see different kinds of organization structures, perhaps different spans of control. We're almost certainly likely to see different jobs in the salesforce. And as we absorb an understanding of how AI will impact all of the work of those new people, uh, we'll probably see them become every bit as overburdened and overworked as people used to be before AI they'll just be doing more. So that's Something to keep an eye out for those excess capacity is something that you don't want too much of it. But it's better to have a little bit than to be understaffed.

Speaker B: You heard it here first. Bob's prediction pendulum's going to swing back the other way, isn't it? That's pretty funny. And I believe it. Hey, I believe you.

Speaker C: There's another interesting difference in these frontier firms compared to other firms. We asked about sentiment about AI, what is the promise of AI and various aspects of managing the sales function, making decisions for the sales function. And we found that those firms that I'll put it this way, adoption is positively correlated with enthusiasm in estimating AI's impact. Those firms that are using AI the most are the most sanguine about how AI will help them in the future. And believe it, its impacts are far more broad based than firms with just a limited sort of naive understanding of AI stuff.

Speaker A: Um, Bob, let's move over to topic three, the management question. How AI changes the sales manager's role. And your research in this area shows that 100% of frontier organizations expect AI to have a high impact on first line sales manager responsibilities over the next two to three years. That is not a heads number. What does that actually mean for what a frontline manager does, uh, every day? And what does it mean for how CROs should be developing those managers over time?

Speaker C: Yeah, this is a very interesting question. It's very interesting to our organization given where we sit and who our members are. We have a lot of sales managers in our membership. It's important to understand that the sales management role, especially the first line sales management role, has been changing significantly before the introduction of AI. The role has had, and this is also a reflection of technology use and better data, but the role has had a diminishing amount of sort of supervisory responsibility and an increasing amount of focus on developing people, but also in a set of kind of integrative disciplines that I'll describe in a moment. So of course we all think of that first line sales managers may be a really good salesperson that was promoted into management. And it's, it's of course a much different job than being an individual sales contributor. The, the places where we see sales managers having the most impact are in actually improving the proficiency and effectiveness of the people that they are managing. That is a very much a role that requires human to human communication and intervention and relationship. It's hard to automate that. Uh, the supervisory stuff is relatively easy to automate. Now another way to Think about this question mark is to say what are the competencies in sales managers that will become in the forefront in the future? And increasingly we see this happening already and there are a small set of competencies that I think will characterize high performing sales managers in the future as it relates to AI. I do believe that proficiency or at least fluency in applying and understanding and applying AI tools to sales work will be required. Uh, for sales managers. Now this involves a lot of kind of subordinate skills. It requires someone to be able to take a typical sales job or task and deconstruct it into its component parts to understand how we might automate that. Which portions are appropriate to automate which portions should retain a human in the loop. And also it requires a process discipline. The sales function has always been process focused or at least it has been in the past 20 or 30 years. But in the future I think this uh, sort of process rigor and the ability of a manager to apply process discipline to the selling function and to diagnose issues as would a process engineer. These are critical skills that we'll have to have in sales management roles in the future.

Speaker B: So interesting.

Speaker C: Yeah. The, to return for a moment to this idea of developing people. Despite what I've said, despite uh, claiming that it's so important for people to be involved in this process, I believe that the currently, today the biggest impact we're seeing in AI and sales is in the area of learning and development. I think for the, for most firms the place where AI can have the biggest impact is in training, coaching and developing salespeople simply because the amount of quality activity in those areas is quite low or non existent in many uh, sales forces today.

Speaker B: So as sales organizations get smarter and sharper and the applied AI really takes hold and then the sales managers are not spending as much time on things like pipeline inspection or call reviews because the AI is listening to the calls. Right. And the AI is pulling out insights. The AI is predicting the forecast. Right. That this is like the vision. Right?

Speaker C: Yeah.

Speaker B: So if AI takes those off the plate, and I know you just said hilariously so that something else will fill that time on the plate. Uh, but what, what should the sales manager be focusing on with that time instead? Like they're going to be getting back so much time, where should their priority be? What's the, how will they have the greatest impact?

Speaker C: Well, let's also point out that the typical environment that sales organizations operate and is very change intensive in part for the same reasons that we're that were the same things we're talking about today. Their customers are also being impacted by AI and by technology. The way they prefer to buy is changing all the time. Their interest in meeting with salespeople and the value they expect to get from such investments and, and meeting time changes all the time. There are all these new competitors, etc. So often, even if only implicitly, we expect that sales manager to be the change leader to enact those adaptations that we have to have in the marketplace. So I expect that that will continue to be the case. Sales managers will have to lead change in organizations and there will continue to be plenty, plenty of it. It will be coming faster than it has in the past and there'll be greater change impacts than we've had in the past. Uh, so I expect managers to be highly focused in that they also are going to have to be skilled at diagnosing issues, diagnosing what's going on with pipeline issues. Will AI help our, uh, pipeline measurement and tracking? It may well make it easier to do. Will it result in better quality? I'm a little skeptical, but only because we've done plenty of research about pipeline management and we find that the sort of tracking constructs that many firms use to track deals or opportunities are often wildly inaccurate at forecasting results. So much so that I've come to the conclusion that we often, I believe, use these tools for more than trying to simply predict outcomes. We use them to foster conversations. So another way to think about this question is will AI result in better quality? Interactions between management and individual contributors to foster quality and figure out how best to close deals. I'll see that I'll, uh, believe the pipeline accuracy and efficiency impacts when I see them. But the good news is we blow a lot of time. Managers blow a lot of time fooling around with forecasting and pipeline tracking, especially in complex selling environments. And uh, if we could have that go away, that would be a good thing.

Speaker A: Excellent, Bob. Okay, this is where we will leave part one. In part two, Bob gets into what the research says about the management roles specifically and why process has to come before AI or you are just accelerating the wrong things. And also we're going to cover the three organizational levers that the data shows actually drives adoption. We look forward to seeing you there.

Speaker B: Don't miss part two next week. In the meantime, like and share this episode with your network. And if you're serious about improving performance, go to get-AGS.com that's get the, uh, dash symbol AGS.com and request a complimentary sales team benchmark, Mark to see how your team stacks up in the AI Era. Until next time.