[00:00:00] Foreign.
[00:00:04] This is Sales Globe Signals and I'm Mark Danolo.
[00:00:08] In Sales Globe Signals, we asked two questions. First, what are the market signals? And second, what does it mean for profitable revenue growth? And Signals is a written publication we put out each month on our website and on LinkedIn. And what I'm going to do here is just cover some of the key points and if you'd like more details, you can, you can go to the written issue on salesglobe.com or on LinkedIn on my page @markdinolo.
[00:00:34] So we've been doing a lot of work with organizations recently about how to integrate AI into their sales process.
[00:00:40] And in the premise that a lot of companies have as they get started is, oh, we're just going to, we're going to be able to cut out a lot of heads, we're going to reduce headcount, we're going to increase efficiency, those kind of things. But what they realize is that the sales process actually has a lot of variations in it where AI can play really well in the more transactional parts and where it doesn't play so well in the parts where you need more human judgment or better problem solving or more human oriented approaches.
[00:01:11] So I want to talk about a few signals that we see and then talk about five actions you can take in terms of how you might think about AI for or your sales organization.
[00:01:23] So there are a few data points and you've heard about a lot of the potential or supposed job cuts due to AI. And I think a lot of companies have done that under the COVID of AI because maybe as a public company, it's the expectation that they're going to leverage AI or they're going to do job cuts anyway. So they can call it AI and it just makes it a whole lot easier. But regardless, in 2025 alone, companies attributed over 55,000 job cuts in the US to AI directly. So that's a pretty decent chunk. Could be higher, could be lower, but it's a significant amount.
[00:02:00] But the twist is while a lot of that gets the headlines, when you look at a lot of these company examples, they're now adding people back because what they did initially is they cut heads. They said, well, we're going to get all this productivity increase, whether it's in sales or whether it's in operations.
[00:02:20] And now they're realizing, okay, we cut too far, the pendulum swung too far in one direction. We've got to start to come back and we've got to start to add back and figure out what we really need. To do. And the reality is you can get a lot more out of AI, at least in the sales process, from productivity improvement and efficiency improvement and lifting your sales organization to a higher level than you can get from cost cutting. Because if you look at your budget for sales resources, you know, compensation and all the things that go around a, the cost of a salesperson, the number you can reduce it to is a lot smaller than the number that you can grow your revenues. So a lot more opportunity there.
[00:03:09] So let's take a look at the five signals here. And to set the stage, the, the more complicated reality, as I mentioned, as companies are cutting back heads and then adding them back, is that there are a few sticking points. One of them is high customer opt out rates. As you know, if you're a person that has called a company and you have to talk to AI, a lot of times you opt out, right? You start hitting zero or you're calling operator, agent or whatever. So high customer opt out rates could be 40 to 50%. That we've seen a lot of companies, human relationships still matter, human relationships close the sale. And so in areas where we need high trust, judgment, understanding of human situations, empathy, complex problem solving, then AI doesn't work so well, at least not right now.
[00:04:04] So it's more about addition, as I said before then subtraction of head count, five signals. I want to talk about adoption, productivity process, leveraging the sales process, the build versus buy landscape and human preference signal. One is adoption. AI adoption and sales nearly doubled in two years and it's still accelerating. So it has gone from pilot stages to full production. It is now an expectation in companies that you're going to be leveraging AI and customers are asking about how companies are leveraging AI for them. And when customers asking that, by the way, they're not saying we want to talk to your AI, they're saying we expect a lower cost from you because you're going to leverage AI. So it's to their benefit. And investors and markets are asking about AI. They're asking public companies what you're doing around AI. And there is that expectation.
[00:05:00] Salesforce state of sales survey from salesforce.com, 81% of sales teams are experimenting or will have fully implemented AI, up from 39% in 2023.
[00:05:12] Our own research at Salesglobe, when we look at specific uses, say around sales compensation and quotas, we had about 29% of companies using AI one year ago and it's up to 69% now in 2026. So that's taken a huge jump. Although not being leveraged fully, it's being leveraged kind of in the chat functions and not as much in the areas that you would expect around efficiency and processing data.
[00:05:39] HubSpot Individual rep AI usage rose from 24% in 2023 to 43% in 2024.
[00:05:46] So the stats are all saying, look, the usage is going up. What we're finding is a lot of it is grassroots. A lot of it is not fully implemented within companies at an enterprise level.
[00:05:56] So there is a gap between organization adoption and individual rep adoption.
[00:06:02] Think back a few years. We saw this with CRM as well. CRM started especially when you look at companies like Salesforce that were doing it in the cloud. CRM started at a grassroots level and companies had a critical mass of people that were then using that particular CRM or that product and then they started to move over to enterprise level. So we're no longer an early adopter phase. We are moving toward it being table stakes. So the pressure is intense to make the AI shift. So that is actually happening. Signal two is on productivity.
[00:06:36] This one's interesting. Sales Reps spend about 50% of their time selling, which drains sales capacity. We have known this for years. So our research at Sales Globe tells us that sales teams spend about over 50% of their time selling. I think it's about 52% of their time selling and only about 30% of their time actually in front of customers. And the other 50% evaporates into things like administrative activities, operational activities, things that don't leverage their true sales talents or their sales skills. But there are also things that become very comfortable at the sales organization over years. So they don't like to give those things up because you know, doing, doing those milk runs is very comfortable. Even though it's not a high product, product productivity activity or, or doing that, those call reports or operational activities, that stuff's very comfortable. So we, we have a human element as well. But with all the billions that have been invested in technology over the past couple of decades, that 50% of time that sales spends on actually selling is, hasn't changed much. That stayed about the same.
[00:07:44] So where does AI come in? Well, what AI can do as a tool is it can help us do what we call decontaminate the sales job. Decontaminate the sales role. So we can take those contaminants, those non sales activities out of the sales job by having AI do a lot of those repetitive things, those operational things, those service things that can free up or boost sales Time and increase sales capacity without adding headcount.
[00:08:11] A quick example, if you have a $200 million company as an example, and they've got 100 reps, and those reps spend about 50% of their time selling, if you can through AI, increase that to about 65%, which is quite realistic. What you're doing is you're adding about and say that additional time that those reps got back, you only had say half the productivity with that additional time. So half the replacement revenue per hour of that additional time that you did with your original time, you increase sales capacity by about $32 million for that $200 million organization. Or that's also the equivalent of adding 14 reps of sales time without adding headcount. So you can see there's tremendous upside even with a conservative estimation like that in terms of using AI versus saying, well, let's just cut heads with that. So if you're first instinct is to cut heads with AI, you might be solving the wrong problem versus how do we get increased capacity, increased growth through increased productivity.
[00:09:21] Signal three is around process.
[00:09:24] So AI is creating leverage at different points in the sales process.
[00:09:29] Not all parts of the sales process are going to benefit in the same way from AI.
[00:09:35] It is, at least initially, creating the most leverage in the areas that are high volume, lower judgment.
[00:09:43] So things like order taking, things like dealing with administrative activities that I just mentioned to free up sales time.
[00:09:51] So it could be around awareness creation, lead generation, lead qualification according to certain criteria, responding to increase, doing transactional closes.
[00:10:05] Right. If you think about where the human element comes in, as I mentioned, all businesses are human and all businesses are based on solving human problems. Because if you think about it, whether you're buying a new suit or a new car, or an altimeter for a 747 or a bolt that goes into a machine, in the end, it all solves a human problem.
[00:10:30] A lot of those things require a higher end of human problem solving, human judgment, human empathy, human decision making, which humans surprisingly are better at. Right? So what you can do is you can create more leverage in that by using AI to be able to elevate your team to those more human centered, what I call sweet spots of the process.
[00:10:54] So what AI is not doing yet, and at least in a customer acceptable way, is understanding complex customer needs, navigating organizational politics. So I often think, you know, in the consulting business, we go in and we work with a client. If we have an AI agent sitting with us at a conference room table or walking the floor, does it have the ability to understand the human dynamics going on in that organization? Probably not. And even if it does, are humans going to be open to that kind of interpretation? So organizational politics driving creative solutions are coming up with creative solutions to ambiguous problems. Right?
[00:11:33] Building trust. And we can see, you know, we already have trust issues with AI, but building trust that can turn a prospect into a long term relationship, a long term customer or a long term client. So those are the kind of human centered sweet spots that we're talking about that we're looking for in the sales process.
[00:11:55] Signal 4 Build vs Buy the AI tools market's evolving and it's evolving from buying a product to building or to hybrid solutions. So the first wave, more than 70% of enterprises bought off the shelf tools. So you know the names of them, obviously, you know, ChatGPT and Claude and Copilot, etc. So off the shelf, very fast deployment, low initial cost.
[00:12:26] And there are a lot of these that are specific for specific purposes. I won't go into the names, but in sales areas around lead generation, revenue intelligence, CRM of course, and AI has been integrated into CRM, proposal development, forecasting, account planning. Some great AI tools for account planning by the way, don't replace good account planning process and good account planning discipline. But there are tools that can accelerate that territory and quota and compensation. So lots of AI tools that are purpose built for those, for those reasons. But we're seeing more limits being hit around using generic tools.
[00:13:09] They have broad application, they can be expensive, they have ongoing recurring licensing costs. And now companies have the ability with AI tools to actually build the AI tools that they need and customize them for themselves, themselves or, or create hybrid tools that are going to better fit their needs. So we're seeing that start to shift into companies where they're saying, well, we can actually build something that's going to work for us and give us an advantage. And it's not going to be perhaps the same tool that everybody else is using, especially if it's a customer facing tool that will give us an opportunity to differentiate.
[00:13:42] So the winners in this area in terms of what they're doing around their tools, they understand their sales processes, they're leveraging specific points within the sales process before they're selecting or building tools.
[00:13:54] They're operationalizing with clear communication and change management. And the reason that's important is AI is not like a part that you can plug into an engine called the organization.
[00:14:06] It actually has to work with humans and with people. And so we have this thing called change Management that has to happen to help people understand how to leverage AI and how to work with AI. We have to turn it from the fear of AI is going to take my job to how can I use AI to be able to elevate what I do at a higher level and signal 5 human preference.
[00:14:29] Customers are still humans who want humans. I mentioned this a little bit earlier.
[00:14:34] So at the end of the day, business and customer needs are based on human needs. Like I said, whether you're buying a car or a suit or an altimeter and a 747, ultimately all driven by human needs.
[00:14:46] And so as long as humans are on both sides of the equation, you're going to have to have humans there. And still, until we have your, your AI email talking with my AI email and we're no longer talking as humans and we're off doing something else, we're still going to want to have those interactions as people.
[00:15:05] Few interesting stats here. Gardner did a survey in early 2026. 87% of people said it's essential to have access to a human agent when using AI. So I'm just not going to be boxed out of human interaction. I'm not going to be just limited to AI. 53% of people said they would consider switching to a competitor over the company that they're using if they force them to use AI and customer service.
[00:15:30] So just because you're putting AI doesn't mean, it doesn't mean your customers want to use your AI. And there are very high opt out rates still.
[00:15:38] So what does it mean for profitable revenue growth? It's not a replacement story with AI for sales. What it is is it's an, it's a capacity and an elevation story. It's lifting our sales organization to be able to do some new things. So I want to give you five steps, five ways to break this apart. And you can see a lot more detail. As I mentioned in the written version of sales Globe signals and also some very cool illustrations that kind of lay this out. Step one is efficiency.
[00:16:07] So mapping your sales process and building for AI efficiency opportunities. So think about the first thing that comes to us when we think about AI, which is efficiency. Let's go find that first. So map your sales process for each customer segment.
[00:16:20] Break it into its component stages. So generically you might think of stages like awareness, lead generation, qualification needs, understanding, needs, solution development, proposal, close onboarding, customer care. Each of these areas is going to require something different, as we know, because we have different sales roles, but each is going to benefit differently. From AI, whether it's increasing efficiency or it's in or it's elevating people to be able to do more. So for each of those stages, understand what kind of tasks are being performed, what could be automated by AI and where might humans play better?
[00:17:00] So quick client story to illustrate this commercial real estate firm, they do leasing for commercial properties, so office industrial properties, that kind of thing. Traditionally they would get their leads and they still get a lot of them through sites like Crexi and Costar and other commercial real estate sites.
[00:17:19] And for years it's been an order taking operation. So agents would take those leads and they follow up on them and they'd follow up on the ones they could follow up on. And a lot of them didn't get covered because of just capacity or people didn't call back or they had to leave voicemails.
[00:17:34] And when they mapped out the sales process, they thought, okay, what can we do? Where AI is going to play more efficiently? And what they found was that agents weren't spending enough time doing real problem solving with clients or trying to find different ideas or different solutions that because maybe, you know, certain properties didn't fit what they were looking for, what they were doing is just doing a lot of order taking. So they could take this order taking, they could build an AI tool to actually help with that response. So leads coming in from, from costar, from Crexi could be responded to immediately without having to have callback situations.
[00:18:13] And you could reduce that order taking by humans and move those humans to other parts of the process where they had to do more complex problem solving and work directly with clients. And they could also back up on the opt out rates for the people that didn't actually want to deal with AI. So a great efficiency play there. So ask yourself what parts of your sales process are high volume, low judgment, admin heavy and those may be leverage points for you. For AI, step number two is elevate. So identify where you're going to elevate your human reps to human centered sweet spots, that higher level work. So if the first step is efficiency, the second step is okay, now let's use the tool to elevate our people to those higher level activities. So once you've found the leverage points, figure out where you can elevate the team to higher value, more complex relational work.
[00:19:07] Financial services client traditionally, and this is an advisory company, very big advisory company, traditionally works with high net worth individuals, high net worth families, and it's a human business model.
[00:19:20] What they know is that There are other markets, more emerging, evolving markets, which are basically younger people, younger generations, younger investors who they can't get to because the human model really doesn't work economically to be able to work with people that really don't have a lot of assets right now. What they also know is that there is the great generational wealth transfer happening. So we've got about $110 trillion shifting from the baby boomers and also the silent generation shifting to those next generations. And those people are going to be recipients of significant wealth over the next couple of decades. And we wrote a sales globe signals issue on the great generational wealth transfer as well that you can check out on on LinkedIn or on salesglobe.com, but they knew this is happening, right? So they're saying, well, we have all of these high net worth individual, high net worth family relationships, human to human relationships. But we also know that that next generation is going to be receiving a lot of wealth, inheriting a lot of wealth, and we aren't there to be able to help them.
[00:20:29] So by the time they receive it, they become high net worth. We're going to then have to establish those relationships. So let's establish them early.
[00:20:36] We also know that a lot of those younger generations are a lot more comfortable with using technology than say the baby boomers or the silent generation, right? And so what they did is they used AI in a different play to be able to elevate their people and also access a new segment. So when they looked at the younger generations, they were able to build an AI tool and an AI agents to be able to work with those younger generations more electronically in a much more highly leveraged fashion.
[00:21:04] And those younger generations then will become human to human clients at some point as their, as their net worth increases. What they were also able to do with their AI tools is for the clients that were comfortable with it, they could supplement their human advisors with those AI tools. So that provided again, elevation, leverage to bring those people up to higher level work and, and free their time up rather than doing a lot of the manual work themselves.
[00:21:33] So interesting story there that you know about how you might access a different segment and also elevate your team.
[00:21:42] Step three is differentiate. So use AI to differentiate, not just replicate what competitors are doing.
[00:21:49] I talk about this all the time. You know, why do we look for answers in what competitors are doing? Why do we look for the benchmarks or the quote, best practices?
[00:21:57] And we don't actually differentiate and come up with something that's going to be A unique solution for ourselves.
[00:22:03] So tools are tending to cluster by industry. So I talked about some of the different types of sales tools before for different parts of the sales process, lead generation, account planning, that type of thing.
[00:22:15] But tools are also clustering by industry. So once an industry has a tool that is a successful tool, they tend to have a herd mentality. So they'll all follow suit and they'll become fast followers and start to implement that tool. Right. Isn't it great that we're implementing AI? We're going to give it its own name, in fact. So it's our AI tool, but in reality, especially if it's a customer facing AI interface, it is essentially the same as their competitors are using.
[00:22:48] So yes, they're gaining efficiency, but all they're doing is keeping pace with their competitors when they work with their customers. There's nothing differentiated that they're doing with those customers. So look for ways to be able to make that level of differentiation or create a level of differentiation when you're putting in tools that are the same as your competitors tools. And we've seen this a number of times and typically what happens is, is they get the AI up and running because that's the major lift. And then they realize, okay, now we have to start looking back at our customer experience. And they go back to the drawing board and they say, okay, what are we gonna do about customer experience with our AI to actually make this better for the customer, not just make it an efficiency play for us.
[00:23:37] Step four is capacity.
[00:23:39] So before you cut heads and before you move ahead with different levels of expectations for what your organization is going to do, plan your new world sales capacity.
[00:23:51] So one of the most overzealous mistakes is cutting headcount based on AI's potential without actually modeling what's going to happen. So what I mean by that literally is if we're looking at what capacity levels we have, sales capacity levels we have, those are going to change with AI. So sales capacity very simply is understanding how much time we have available. We talked about sales time earlier, about salespeople typically having 50% of their time to actually sell. So how much sales time we have divided by the work that we do. So how many hours does it take to manage an account? How many hours does it take to close a deal?
[00:24:35] What is the workload that's required to do those things? So if you take time divided by your workload, you're going to get an amount of deals or amount of accounts that can be managed on an annual basis.
[00:24:51] You multiply that times the productivity per deal or the average deal size and you get an approximation of sales capacity.
[00:24:59] Well, with AI, that equation can totally change.
[00:25:03] And I think too many companies don't really look at that and remodel what their new world sales capacity is going to be.
[00:25:10] So how can that change? Well, it can change by of course, freeing up more sales time, which can change the capacity expectation. It can change by changing the workload to win an account.
[00:25:21] So that could actually decrease because AI is picking up certain parts of the sales process to increase the amount of hours or decrease the amount of hours required to manage an account. So as you change those things, you know that's going to change your capacity. Also your average deal size could increase because in theory, if you're freeing up people from those transactional activities, they have more time to work on higher level things like perhaps getting to the C suite of a customer and working at that level. And that can increase average revenue per deal. Now of course you have all the human elements to consider in there as well, which is people aren't going to want to do that because they don't know how to do that. Right? So you have those human elements about how do we teach our team to do those things. But your sales capacity can and will fundamentally change as you implement AI. So understand your new world sales capacity and number five financials, redesign your sales compensation model and understand your AI investment roi.
[00:26:25] So if we are changing the sales process and we want people to do things differently and we want AI to pick up other parts of it, unless we change something with how they're motivated and how they're paid and we, and we teach them how to do that, they're likely going to continue to do the same things. So if we said, well, there's a certain part of the sales process, the order taking part of the process that we're automating so people can move to higher levels, higher level buyers or other parts of the sales process, or maybe going out and, and developing accounts further.
[00:26:59] Unless we tell them how to do that and unless we change the motivators around compensation and measurement and things like that, they're going to be just going, well, all my leads went away, I took all my leads. Well no, that's kind of the point. You're supposed to go somewhere else and do something else, right? So think about your metrics, your measures, your compensation plan mechanics, and also the financials around your compensation. Because you're going to be paying different levels for different types of things. If you want, you want them pursuing new strategies. Also understand your ROI from the total equation, including the cost of your sales organization and the investment in AI. So if we said we're going to get all these efficiencies, we're going to be able to increase productivity, we have returns like that divided by our investment. Our investment is not just what we're changing in terms of reducing the headcount. We're, we're shifting what we're paying people. But it's also that we made this big investment in AI and that's gonna have an implementation cost and likely an ongoing cost. So understand your ROI and model that for your best case, model that for your worst case. In most of the situations we've seen, the ROI is actually very positive. But we have to look at the entire situation, the entire equation, including all of your costs.
[00:28:18] So your call to action.
[00:28:20] The question is not whether you use AI, because you probably will in your sales organization. The question is how you use AI.
[00:28:27] And the point I've been trying to make is not to look at it as just a cost cutting tool, but look at it as an opportunity to increase productivity, to increase capacity, sales capacity, to increase revenue, to increase growth.
[00:28:41] And to do that again, follow those five steps. Look for those customer centered sweet spots where you can lift your human reps to be able to do higher level work and where you can increase efficiency. So look at these signals from two angles. How do they affect your customers and their ability to grow?
[00:28:57] And how do they affect your organization, your productivity and your ability to grow? And if you'd like more, check out SalesGlobe Signals on LinkedIn and also on SalesGlobe.com and if you want to know more about what it means for your business, reach out to
[email protected] or you can go to infoalesglobe.com this is sales Globe Signals. I'm Mark Tonolo and thank you for listening. We'll see you next time.
