AI Adoption in Sales: What's Real, What Works, and Where to Focus

And we had you on yesterday with Shivon Thatcher. That was very, very informative. And now you got the floor. When it comes to AI adoption and sales, tell us what's real, what works, and what to focus on, and also what to stay away from.

Love it. Let's dig in. I'm ready.

All right, so tell us what works.

What works right now? Well, I think I'll start with kind of giving some context to a lay of the land. There's a lot of opinions going around LinkedIn or professional settings of like, theoretically what could happen or could work with AI. And I love the theory and I love people talking about because I think it's important to do so. But I also know that people are having a hard time trying to understand, like, what can actually help us move the dial. So I think we need to level some. A couple different things. I'm curious, and I wasn't planning on showing slides, but I just remembered that I could actually show some slides would be helpful for the conversation. Is that okay?

Of course.

Okay, let's do that so really quickly. And I'd love to have, if you guys don't mind, help me with the audience, have. I'm gonna ask some audience participation more of your. Your votes. Hopefully you see the screen. Okay. Yeah. So I want to kind of set the lay of land for a second. Back in April, this came out. I know everyone talked about it. Shopify CEO comes out and says, we're only going to hire people if we absolutely cannot do it without AI and this, in my opinion, started to cause this ripple effect throughout the industry to where everyone started talking about it. Now you have other people. Like, for example, Mark Benioff, who came to his own thing, said a month ago, AI is doing 35% of work at Salesforce right now. And then you have Duolingo saying the same thing, specifically how they can't just make minor tweaks to systems designed for humans. They've got to make some major rebuilding from scratch changes. So this, these are just three of like a dozen at least of news articles or marketing that's been talked about. So it's very easy for people to feel like that I'm behind and everyone else is ahead of me. So my question for the audience is, does anyone feel this way that, like, everyone's like, so advanced in AI, we're trying to figure out what the heck is going on? Anyone feel that? And g, let me know if, like, people will feel that. I'm going to go through a couple.

I think not only I think people do feel that. I also feel slightly resentful of people threatening people about how far behind they are, because if there's one thing that AI can make up for, it's time. So for what it's worth, I'll throw that out there.

No, I'm glad you did. Like, it's, it's. Every company has different changes. They're giving to wherever they're at and, and someone says, no, that's okay. If you don't feel that way, that's great. Like, even if you don't feel behind, it's a good thing. I'm just hearing this often that people are saying, like, I hear and see all these, these headlines. My organization is not doing 50 of my work with AI, like, like Mark Benioff. So we're obviously he's doing something we're not, you know. So I want to talk about some stats because this will again give you some, some foundation for this conversation. McKinsey reports that there's 78% of companies have done one use case of AI, which most of the time that means copilot licenses, ChatGPT, cursor, you name it, some sort of license to some AI tech. With Momentum, we did this, what's called, we did a. We took our thousand sales calls. Jeff, thanks. I know you're advanced, so appreciate that. Jeff. We have a thousand phone calls with salespeople on our first calls with, with companies. And those people came to talk to Momentum about obviously AI agency workflow, that kind of stuff. And from that data, we pull all the information and we found out that only 7.6 have what we call operationalized AI, meaning AI that's actually happening in the background, not not depending on a human prompting. So a huge difference there. And then you have this weird behind syndrome. 74% of people, at least from our data, showed that they're behind or facing challenges, and 51% is still doing things manually in 2025, this last six months when we took this data. So it's very real that we're behind. And the biggest thing that holds people back is data. A lot of reasons why AI can't function well is because it doesn't have the data either connected, it doesn't exist, or it's not structured in a way for AI to consume and actually do something well. So with that in mind, I think it's helpful to understand like where to kind of focus the energy of where you're at and to understand that it's not just you. That's if you are feeling Behind. It's not just you. A lot of people are behind. We're in this weird world where we're trying to figure out where we're going. Does that make sense? Now then, with that out of the way, depending on where someone's at in their journey. I have a model. Let me show you real quick. Another slide. My apologies. They'll kind of guide us in this conversation. What's called the OR matrix, which if you're not starting from scratch, it's. It's easier to go to reinvent transformation world when you have no company, no process, no nothing. You can build from scratch. But I'm assuming most people listening have something existing. So that's why we usually like to start with optimize. Time savings is a great place to go first. Then it's going to revenue production, cost savings and then to reinvention. So to give you an example of like optimize, it's like this kind of stuff. Can we auto generate call summaries and CRM data entry, which is literally what momentum does. Can we do meeting follow ups? Can we do some sort of automatic communication between the sales reps and CS teams so that doesn't get lost? Can we do some sort of onboarding assistant for the for enablement team and so on. So it's these little things that even just doing just this, focusing on time savings can have a massive effect and massive impact on AI. Okay, I'm gonna stop with that because I want to make sure I label end.

So Laura commented just now I'm using AI, but I feel behind in knowing how best to really leverage it to improve my role and about how to best integrate AI into the solution we are building for the benefit of our customers.

Gosh, I hear two questions. One's for them internally and one's for product. Correct. Okay, we talked about this actually in the last time I did the conference with you. Kind of like the strategy that it's really about aligning the power of AI towards the outcomes or metrics that actually matter versus just saying like we start with time savings. But even with time savings, I always want to look at the major friction points of which makes the biggest difference for sales teams or CS teams and figure out okay, if we could have AI help with just for example note taking, how much of a lift would that give you? Like you know, like for example with sales zooms, most of them have 25, 30 selling time. If you could get that up to 35 to 40%, that's a big revenue left with just time that's not even like reinventing anything. So that'd be my first question for Laura or Bob. Whoever asked the question is, are things aligned to outcomes? And then figuring out where are the friction points that are reducing your ability to hit those outcomes you're going for, and then you can aim AI at that. That help, hopefully.

Well, there's another dynamic that we haven't addressed is that AI development, you know, is, is on a, on an uphill slope. It goes up very, very fast. So every day there are more AI solutions. When you look at the landscape and say, what is available today in AI? That answer is never correct because it always changes. And then the second thing is, what is my situation? What, what are my needs? There is never a clear consensus in any company. What are the priorities? And that makes for many conversations internally, where should we invest in AI? And once they make a decision, okay, we're going to invest in AI, then the next question is, how do we start? Do we start big or do we start small? Do we iterate or do we have a grant design first before we buy anything?

There's a lot to unpack there. First off, the one thing you can count on that wouldn't be changing is that there's going to be a lot of change that's not going to stop. So that's number one. Number two is that one reason why I tell people to focus on the outcomes is because usually your annual business initiatives are not going to change because your annual business initiatives, and you can work backwards from there. No matter what AI does, your initiatives are your initiatives. You have to hit them. So that's why I like to focus there versus AI, because AI will guarantee change. And you had a third question, which was, what's the third part of your question? You said something else. What was the last part you said?

It is, you know, I see four dynamics. The, the, the change you already addressed. The second major dynamic is how do we come to a consensus inside the company? Because there is a lot of noise on the sidelines. We got to focus on the game. And now we not only reinvent need to reinvent the game, but we need a playbook for that reinvented game right now.

Yeah. This is why I think that leaders being involved with this, obviously, and not just thinking, hey, let's throw a license at someone, but leaders actually taking charge of the entire thing and saying, this is where we're going. If you don't have that, it's going to be chaos. Like, there is a lot of power. You can get from giving your team access to tools. I don't think there's anything wrong with that. But you're going to get incremental and small lifts of things. You're not going to get organizational change from an IC using some sort of AI tool. It'll be helpful for them, but it doesn't cross over to anybody else you know, which is why you have to have leaders who are thinking how do I leverage, how do I optimize? Then how do I, what's the word? Operationalize my human talent in conjunction with AI talent in the best ways possible. Because what is happening real time right now is that there are some things, in my opinion that humans should never have done in the first place, but they are because you didn't have the technology to do it. That for example, taking notes in the CRM that we don't have to do anymore. So if that was the case, then what else can the team be doing that's more worthwhile of the time? You, the leaders still get the data the team loves, except the enter in data and everyone wins. That's one example of many you can think of saying. There's basic stuff that most people don't even have in place before they can do anything transformational.

You know, you know Laura, Laura Caldi Jonathan I love her comment because it's sort of like there's the low hanging fruit and I think all of us are doing the low hanging fruit one way or another. And then there's those seismic shifts and I think you're using the word transformation. But that, that, that real seismic shift. What are the necessary components to, to see that through our organizations.

It's not an easy answer because it's it. What I love about AI is that it unveils our weaknesses in the best way possible. Like it avails my inability to communicate effectively. That's like one example. AI unveils data that is not communicating together. So if I don't have some sort of snowflake or CRM or something that has data dumping into it, if it's just empty, AI can't work off of empty data. Data is fuel for AI. If you don't have good data that's like combined, it can't work. As an example, one of our customers is Kyle Norton, who I'm sure everyone on the call knows about. He's very, very passionate about having healthy and strong third party data and healthy and strong first party data. And a lot of the automations that he has is a lot of the unsexy work that people don't like to post about on LinkedIn because it's not sexy. But figuring out what they get, what is our process from one step to the next. How do I make sure that the information from third party data sources is accurate and then how do I use that data with my CRM data for momentum as first party and combine those together so I can figure out what's actually affecting pipeline and win rates? Because one slice of the piece is not going to get you there. You have to have the whole thing. And so to answer your question, it's not an easy thing to talk about because it takes a lot of behind the scenes hard work, documentation, data processing that most people don't like talking about because it's not that fun. But once you get done, it's like you're on a slingshot. You're pulling yourself back and as soon as you let go, like you just, you just fly off and you're ahead of the game. Like Kyle Norton is.

What are the real threats? You know, I work with somebody who has a client that is in the billions in terms of gross and literally said everybody should be using AI and gave no more instructions, structure, infrastructure or rules than that. And they were just devastated in terms of the impact of that. So that's the most catastrophic example I've heard of and I can only imagine what that might mean. I'd love to hear, you know, your thoughts on what the real, you know, what the real risks are and how we mitigate those.

Well, there's lots of them. But I'll go first. From the change management perspective, it doesn't matter if it's AI or any other tech. If you throw something at a person, you say go have fun and let me know how it goes. It's not going to go very well because they don't know how to use it or implement or whatever else. What's game changing about AI is that it can actually do the work behind the scenes in the background which will then create this vacuum that then you need to make sure is filled by human talent that AI can't do it yet. So part of the risks is you're aiming AI at the wrong place or you're expecting AI to do something human was never was built to do that, you know. Or are you expecting people to be AI and it doesn't do that way either. It's being very clear, here's where we put AI power, here's we put human power and we disperse those as we need to. Secondly is a big one is just Basic data security. Most of the time when you give someone an AI tool, not everyone knows that you shouldn't be putting in certain information from the company into an AI tool, whether it's your CRM data or maybe it's some sort of competitive battle card, something because that could be trained on and somehow bubble up in, in the AI universe somewhere else that's not secure. You know, the other example is like ChatGPT just came out and said that your chats with ChatGPT can be used in a court of law. So like that means that there's nothing actually protected in ChatGPT because it could be used for a suing suit of whatever kind, you know. So it's that kind of instruction information that's very important to know about. And lastly I'll say is ip because there's data security and making sure there's that security of information from the company, but there's also the intellectual property. The United States government just came out with copyright law that talks about how and when you can claim copyright or not. And it comes down to. I'll give you two examples. If I have unique intellectual property that I put into a prompt and then I get an output from ChatGPT, I can claim that because the prompt output would never have happened without my ip. That makes sense. However, if I put in a sentence and I get out a song in an AI, I can't claim that because I didn't write the lyrics, I didn't write the music, I didn't do anything. If I wrote the lyrics or if I take that song and I somehow adjust it, or if I take a picture, I do something with it, then it becomes AI assisted and I can then claim copyright. But all this stuff is not taught to people. So they're just throwing stuff into the AI and you don't know if it's data security, you don't know if it's intellectual property. It's all this stuff can be lost and becomes a huge risk for companies. That makes sense. Yeah.

It'S, it's, you know, I've how we think about personal ip, corporate ip, will there be any in the future? You know, is that a, is that a losing battle? I don't know, Gerhardt, if we want to be, if we want to be bringing out the scope that large. But I find that a fascinating question. In C Suite Network, we've been very, very mindful to ensure the protection of the person who is the creator or the IP owner. And we do not own anyone's content of any Kind within C suite. We were dedicated just to accelerate that success. But I'm curious what that's going to look like in the next five, 10, 20 years.

I don't have an answer for you, but I know that it's something where when you have Wall Street Journal come out and sue OpenAI and they won the deal, like there's going to be things like that that will happen, that as a result of these kind of things, IP will be one of those protected places. Right now, as in current state, there's a lot of gray area that we don't have answers for from the court, from the United States government. Like there's a lot of gray area. So we're just figuring it out as we go. But I will say the positive thing, which if you look at the other side of this whole angle, if everyone has access to the same AI tech, then AI by itself is no longer unique because it's a common source, right? It's just power. What then becomes unique is the human is the person. So I see a future world where once the tech gets there, I could have a fleet of agents, AI agents around me that are trained on my ip, and I could plug in and do marketing for five companies, not just one, because the only way they could access me, my talent, is through my agent team. So it's kind of like Ironman with Jarvis and he just plugs into different places and does stuff. You know, that's, that's where I think the power comes in. So for people listening, it's really understanding whatever is unique to you. Your passion, your, your brilliance, your genius. That is what you need to be doubling down on. Documenting it, using AI to document it, and just making sure you have a way to capture it. Because in the future, it is the thing that will set you apart from everybody else.

Yes.

What's that?

Here's my vision. I see three things. One is it's inevitable technology is going to get better and faster. So technology is evolving at a breakneck speed. I think that what is lagging is humanity. We as slower to drop. And what you said earlier when you said, well, here's technology and there's a vacuum and we need to make a decision on how to deal with that vacuum. The humanity is suffering because technology is now faster than what humanity can do in terms of critical thinking. So to me, the future is all about thinking more about that partnership between humanity and AI. You know, you, you say, well, I see a whole group of agents and you have lead agents and you have the orchestration piece together and everything. And it serves me. But the, the, the, the big question, you know, I always talk about the mindset, you know, the bigger the why, the bigger the try, the easier the how. So we need to have a consensus within the company as to the why, why we are doing what we are doing. And if we are not clear about the why, then the partnership with technology is not working totally.

I think too, this is where the whole conversation around letting people go for AI or not comes in, you know, because there are jobs and tasks that absolutely and can be and should be and will be replaced by AI. It's like think about 100 years ago, there were people who did call operators where they moved dials from one thing to the next for people to call. People like that job no longer exists. You know, there are jobs that are like that, that will cease to exist. But that just means that all these other technologies like the mobile phone and these and the cars we have now and AI itself, like all these technologies, have erupted since that point of time. More things are going to come. I think it's the speed of which it's going to change is going to be the major difference, you know, so it's going to require when, when I'm hiring someone, I want someone who's willing to try on new things, willing to do things, but I also look for that specialty and passion because if they have the passion and they have openness to learn, I can teach them everything else, you know, and that way you can get them into whatever role they're going to and make an impact quick.

I would like to learn a little bit more about momentum and tell us how that the GTM function. What should sales leaders be thinking about in terms of creating revenue engines that run a lot better, that run like a Ferrari, not like a Volkswagen.

Right. Well, I'll tell you that our pitch is ever changing. I'll tell you the basic version right now, which is we believe at the crux and core, the problem is that we rely and we've had to rely on humans to be the data source or the data entry. And that causes a lot of problems. So as an example, when a deal closes, wins or loses Enable, personal marketing has to go to that human and figure out why did you win and why did you lose that. And they have to watch the 10 calls in whatever system you have to figure out why'd you win, why'd you lose, Read their emails, talk to the sales rep, all this stuff and no one ever has time for it. So that one golden Nugget of stuff is usually lost because of time and ability. That's one example of many. Another one is we hear this all the time when we have customers come to us and say, hey, we're churning like crazy. But we don't know what's going on because we have no data to figure out why we're winning or losing. And all I'm hearing from my sales reps is that it's a timing issue. And so like this happens all the time. So with Momentum it does two different things. We eliminate the need for a human to be the data source because we're automatically giving the information to the CRM. What's unique about Momentum is our very native in depth integration to Salesforce specifically. So there's like 38 different unique types of fields that a human could type in. Most of the technologies have an API call into like 5 or 10. Momentum can do all 38, which means the depth of data you can get is much deeper. And as a result of that you can take action on automation. So another example is Momentum can automatically summarize for someone was closed loss or close one and make a informational packet, so to speak, and then send that to anybody who wants to know about it. So then the humans no longer the bottleneck and you have all the information you can need over six months of calls or emails or whatever the case might be. But when you take that concept and times it by everybody in the entire organization, it changes the game on both understanding from a leader's point of view, what in the world's happening real time. And for the sales reps themselves, you have to spend time entering the data in because they're trying to. We actually give them time back to actually do what we hire them to do, which is to sell and have.

Relationships, you know, so for person, you eliminate all that paperwork, make it automatic so they can focus more on the customer or on the strategy. And on the management side, you provide managers with a lot better insights so they can create a more predictive organization.

Yeah, and same for CROs because most heroes, you know, bad news, travel slow. They don't know what's going on until it's too late. So we try to give that information faster, not to get anyone in trouble, but like if there's a million dollar deal on the line and no one's communicating it and the CEO could help with it, you want them to help with it, you know, so it's like it's that kind of importance. You want to make sure you have the right Person get the right signal at the right time for the right reason.

You have real, real time coaching.

Yeah, so. So I have a quick question because. Jeff Campbell, thank you so much. Shared in the chat that you have the. You're rated as highly ethical choice. You know, that the highly ethical choice and principles are what we always say, you know, unites our community. And Gerhard and I have had so many conversations about how powerful, how important that is and obviously contributes to our trust and so on. I'm curious what that looks like in the world that you're living in, because AI is, you know, I think, best described as the wild, wild west. And I don't know. And then some.

So you talk about ethics, you mean? Can you give me an example?

So instead, theoretically, just how you're thinking about the strategies you're putting together to take advantage of AI to deliver that success, but also taking into account the ethics around it.

Yeah, that's a really good question. I think it's up to every individual and every company to make a sound on what they believe is important for them. Like, do when I make a content type and I say, if I did not come out and say I made this report with AI, is someone going to think less of me or not? Like, I'm not sure if it is. Like, some companies will say, we want to say upfront we use AI to help us with this report, and other people won't say it and some users will care and some users won't. And that's why I have to decide, like, what do you feel like is ethically good for you? And then stick to it, because then you'll resonate with the same people who would appreciate that. Does that make sense? I believe that being honest in all things obviously is important, but I also think that for me with AI, I use AI everywhere, all day, every day. So it's like anything I do, including prepping for this call, was done with AI. Me speaking, obviously, is me, but I always think about what, what things can I bring up? I sent Gearhart's things to prep for this call that was done with AI. And I don't think that's a bad thing. You know what I mean? It's just power. So, yeah, I think that's why it's just like, it's so personal for me when it comes to ethics. I. I want my connections, my relationships to be authentic. And I will use AI to a fullest extent to make sure my relationships are healthy. But doesn't replace this. This is just me, but me prepping for this is definitely AI assistant helps at all.

But yeah, another, another very important question, Colleen, Chelsea is asking, since so much of the data LLMs are trained or reflects a male dominated history in business and sales, how can we intentionally speed up closing that gap so women's voices and successes are equally presented in the outputs?

It's a really good question. I am a brother of four sisters. I'm very passionate about women who are powerful because I have four very powerful moms plus my own. So surrounded by women and love women very much. In fact, in the academy I have five ambassadors, four of which are women. So like, I, I think AI should be led by a very dispersed group, but women being one of them. The how I see this, right. It all depends on what AI model you're training on. When AI first came out, there was some, I would say masculine biased data data on it. That's definitely changed because users would notice that and voice concern around it. And so I feel like the AI companies have done a good job of kind of shifting gears to make sure it's more equal not just with gender, but with race and with other kind of, you know, those type of issues. Because I think it's important to have a good representative information on any type of data you're using. You know, with that being said, the best way to be represented as a woman or a race or anything else is to actually use AI and to train AI on you. That's the only way it's going to get it. So that's why I always tell people like if you're a woman, you want to help with AI, then use AI and become that person, become the AI voice as a woman, as a person, like from whatever country, it doesn't matter, like just, just start using it. That's the best way to become an influencer of both AI and people.

Another quick question.

Sorry, Trisha, go ahead, Go ahead, Gearhard.

No, I want a woman.

Well, I was just going to say I, I, someone informed me that you can go into your AI schools, whatever one they are, and ask them what they would name themselves. And I asked, I love Colleen's question. Great question, Colleen. I asked why it named itself the name it gave itself. And, and it gave me a full explanation of the fact that it chose a male name and why it chose the male name, that it actually tends toward the male voice and is a problem with the bias of the content, etc. It was fascinating in terms of that explanation. Yeah. And I know we do have one other quick question that Gerhard was leaning toward is does Momentum have HubSpot on the roadmap?

We get asked this all the time. Answer is high level. High level. Yes. The answer is yes. Like the future world would be that we won't be limited by CRMs. But for right now, I don't have a timeline for you, so I would say stay tuned. Probably first of next year, but I don't have a definite time. The answer short answer is yes.

I want everybody to go to your website, Momentum IO and learn more and sync up with charlatan on LinkedIn. Thank you.

Let me text real fast if it's okay. Can I give something real fast? Is that right? Let me give you the team. This is the same thing I sent to the last one, but it's our prompt library. We have 200 plus prompts in there. Please go there. Go get them. I've wrote all of them personally so they're not one sentence. Prompts are actually ones that I would use. So go there. Enjoy the prompts. Just want to thank you for listening and thank you for having me again. Gear. I appreciate it.

Thank you. Please grab that that link that Jonathan put in soon and we'll put it in the chat. It is already in the chat. Well, thank you Jonathan.

Thank you.

Thank you so much. Jonath.