GenAI Isn’t a Toy—It’s a Culture Shift

   

Drew: Hello, Renegade Marketers! If this is your first time listening, welcome, and if you're a regular listener, welcome back. Before I present today's episode, I am beyond thrilled to announce that our second in-person CMO Super Huddle is happening November 6th and 7th, 2025. In Palo Alto last year, we brought together 101 marketing leaders for a day of sharing, caring, and daring each other to greatness, and we're doing it again! Same venue, same energy, same ambition to challenge convention, with an added half-day strategy lab exclusively for marketing leaders. We're also excited to have TrustRadius and Boomerang as founding sponsors for this event. Early Bird tickets are now available at cmohuddles.com. You can even see a video there of what we did last year. Grab yours before they're gone. I promise you we will sell out, and it's going to be flocking awesomer!

Welcome to CMO Huddles Quick Takes, our Tuesday Spotlight series where we share key insights that you can use right away. In this episode, Gen AI experts Tahnee Perry and Liza Adams explore how CMOs can build AI-powered marketing teams, from developing internal literacy to rethinking workflows to showing ROI fast. By the way, you can meet both Tahnee and Liza at the CMO Super Huddle this November in Palo Alto. To learn more and join us, visit CMOHuddles.com. If you're trying to move past bright, shiny object syndrome and actually operationalize Gen AI in your org, this one's for you. Let's dive in.

Narrator: Welcome to Renegade Marketers Unite, possibly the best weekly podcast for CMOs and everyone else looking for innovative ways to transform their brand, drive demand, and just plain cut through, proving that B2B does not mean boring to business. Here's your host and Chief Marketing Renegade, Drew Neisser.

Drew: Hello Huddlers. Five months ago, Tahnee Perry joined us for a conversation on building an AI-powered marketing team. During that huddle, Liza Adams popped in towards the end on request, and the conversation was so flocking awesome, we decided at that moment to bring them back again together. So here we are with two of the leading AI orchestrators who've been at the forefront of helping marketing orgs not just adopt AI, but truly operationalize it. So think of this as an ATA—like an AMA, but an ATA—as in "ask them anything." Please put your questions in chat. If we don't get to all of them now, we will after the recording. And so, one last note: both Liza and Tahnee will be speaking at the CMO Super Huddle this November, using the PechaKucha-style lightning talk format, which I think is a first for both of them, but they're going to enjoy it anyway. Today's huddle offers you a sneak peek of their thinking. So hello, Liza and Tahnee. How are you and where are you? We'll start with Tahnee.

Tahnee: Well, thanks so much for having me. It's always a great group to join. Thank you. I am calling in from, I think, just outside of San Francisco, so I am West Coast based.

Drew: All right. And Liza?

Liza: I'm joining you from Boulder, Colorado. It's going to be beautiful here today, and excited to see everyone again.

Drew: It is going to be beautiful here today. And so we've got this country covered at this point with the three of us—East Coast, West Coast, Midwest or Mountain Time—so it's all good anyway. Let's dive in. And you know, one of the things we like to do in these things is, just in case the audience needs to leave early, or we need to convince them to stay, propose two of the most common mistakes or blind spots you're seeing as CMOs try to build AI-powered marketing teams. I'll let you decide who goes first.

Tahnee: I can jump in, and if I miss anything, Liza, let me know. I think the biggest mistake that I see CMOs and leaders make is not dedicating enough time to change management. People get really excited about the tools and the shiny new objects and, "Oh, there's this amazing workflow." And they just expect people to naturally dive in. And you are going to have some people on your team who already have that ability within them, and they're excited about all of these new innovations. But you're going to have people on your team that this is very scary, and they don't like it, and it's going to be difficult for them. And you need to think about, how do you bridge that gap for them? Because some people just—it's hard for them to figure out on their own. And as a leader, I think your job is to think through the process and then at least dedicate some time to it. And you know, Liza and I have worked on a couple of different projects together, and the ones that always work the best are the ones where they're taking the time and they give their people the space to make the mental adjustment. And I think, you know, so it's dedicating enough time to think through the process and then time for people to make that natural transition themselves.

Drew: Got it, okay? And I want to go into that in a little bit more detail, but Liza, give us another sort of area that you see.

Liza: Yeah, so Tahnee took the best one.

Tahnee: That's why I went first.

Liza: Yes, but the other one that I'm now seeing is—and this is not all CMOs, right—but there are certain CMOs that feel that they don't necessarily need to put their hands on keyboard. Teams need to put their hands on keyboard. And I think, unlike previous innovations... You know, many of us have been around for a long time. We've gone through internet, cloud, mobile, social, SaaS, now AI. In other innovations, we didn't necessarily have to be hands-on keyboard or actually using those technologies. This is one where, until we put hands on keyboard, we do not truly understand what's possible. And if we are going to inspire and lead our teams through change, we need to be empathetic to that journey. And to be empathetic, we need to know how to use these tools, understand their limitations, and understand their capabilities. So this is not just for us as leaders for our careers, but also for us to drive change and really empathize with our teams.

Drew: I love it. They're great. Both of those are important enough—let's go through them, one at a time, a little bit more detail. So the change management and taking the time. Tahnee, when you talk about that, the whole emphasis on speed is one of the outcomes of having a tool like this, because suddenly you can do things faster. But training isn't necessarily something that you can do faster. So there's a contradiction here. Wait, this is—we have to slow down to train so we can speed up. Is that the idea?

Tahnee: Yes, exactly. I think don't short-change—I mean, yes, you want to be moving fast, but I think there's a difference between hesitating and waiting to see. Like I've been hearing a lot of people say, "Oh, you know, we're waiting for the dust to settle and then we'll figure out what we're going to do." Like, no, no, no, the dust has settled. Stop waiting and move into implementation. That doesn't mean to rush it, though, so take the time for each of those steps. So I think identify—as a leader, it's your job to identify, like, what are the next steps? When do we take them? And don't hesitate. I think that is the key.

Drew: Right? And so we're really talking about, again, the three roles of leadership. One is, you know, set the vision. What is it that we're trying to accomplish? Build the team, and then allocate resources. So the CMO needs to have a strong point of view on how you're going to, at least initially, use these tools and get up to speed. So that's one, and that sort of leads into Liza, your point of view. How far do you think CMOs need to go when it comes to, you know, getting their hands on the keyboard?

Liza: Yeah, you know, it's interesting. I always get this question, you know, "Where do I start?" Right? As a CMO, where do I start? And there's so much that we can do. You know, the first thing that people gravitate towards is really productivity, right? Help me do things faster? And we have all sorts of things that we need to do faster, right? From crafting emails to responding to questions and all those things, which is great, right? But especially for leaders like us, you know, CMOs, we get hit with really strategic questions. How do we allocate budget? We now have a new competitor in the space. How do we position against them? How do we now elevate our messaging? Just using AI as a thought partner, I think it's just one of the best places to start. You know, as marketing leaders, we have hypotheses, we have assumptions, we often don't know the right answers right away, right? So put in your assumptions and hypotheses and your thinking and your frameworks into AI and ask it to critically give you feedback, to challenge your assumptions, challenge your hypotheses, give you a different point of view. Because AI has a positivity bias, you will feel like a rock star when—if you don't ask it to challenge you—but that's how I use it, and it's really insightful to see your blind spots, and it's humbling to see your blind spots. And the beauty of it, it doesn't judge.

Drew: Could you have missed this, you dope? It doesn't do that. So, it's funny. You've been doing this a long, long time. And I think that if we go from this step of where do you start the challenge, I think for a CMO. And I'll tell you a funny story. In one of our Huddles, a CEO put in a chat a prompt that said, "Hey, our competitors just raised our price. Should we raise our price?" That was it. That was the whole thing. And it said, "Yes, you should raise your price," so that became almost the directive from the CEO. And obviously, garbage in, garbage out. There's a lot of things you don't really know that you don't know. When you're getting started and you say, "Okay, be a thought partner," you really have to put a lot of context in order to get good results. So how do you, and how do you know when you have enough?

Tahnee: Well, but I'd also say it's the approach you take. I never recommend asking ChatGPT or your LLM, your large language model, for that answer. I think the point, please, is right. It's about the process and helping you think through the problem. So what they should have said instead is, "This is what's happening in the market. Help me think through all of the different scenarios. Use it as a scenario planner." I mean, asking it for the answer is—you might get the wrong answer, and then what do you do?

Drew: Right. And you really aren't looking for the answer, eventually. But part of this, as a thought partner, is to think it through. I'm going to just pause on that, and I want to ask all of you that are listening right here live—are you asking for answers, or are you asking for help to think a real problem through? And then, as you're thinking and working with it, it should be asking you questions about information, but you probably also know context that you can add. So, okay, good stuff.

I want to go back now to the hands-on part of this a little bit more, because I wanted to produce—we're doing another show next month on video production. I had never used AI to create a video. I'm not a videographer or editor, but I thought, how hard could it be? Turned out, it was pretty hard, but I went through the process, and so now I have a great deal of empathy and I understand: what are the tools? What can they do? Where are the gaps? When do you need professionals? And all—and I wouldn't have known that. I might have just said to somebody, "Hey, go produce a video." Talk a little bit more about when you want CMOs and so forth to be hands-on to get their key—what does that mean? What does that look like from a video perspective? No, no, forget video. That's not the least of the worst. No, sorry, I just use that as an example of when you get hands-on, you get a better level of insight into what the challenges are—in this case, a production challenge. How deep do CMOs need to get? Do they need to get into the script to see what it can do? Do they need to, you know, is it mainly understanding how to use it as a thought partner? How far do we need to go?

Liza: No, no, we don't actually need to go that far, because what I tell people is we have to inspire ourselves based on the role that we're in, right? So think about your role and think about how it might help you start there, right? Because when we understand how it can help us in our role—and it could be for productivity purposes, it could be to increase quality—and then the third thing would be, hey, can we actually reimagine things? So it's not just better, faster, but also different, right? So use AI to begin to reimagine things.

But those same three things, once you understand how it does it for your role, others on your team can begin to apply it, right? So a content marketer can begin to say, "All right, how can I use this thing to improve productivity? How can I use this thing to improve quality? And then, how do I use this thing to actually reimagine the work?" So as a CMO, we don't need to, like, deeply understand, you know, the use cases by marketing function. We need to have a sub-level of understanding, but start with our own role and figure out how we could do those three things first, if that makes sense, Drew.

Drew: It does. But I want to push back a little bit. First of all, I appreciate the categorization of thinking about productivity, quality, and reimagining things. That's a great sort of framework. I think a lot of the emphasis has been on productivity. Can we get this done faster? And I think that has sort of seeped up to the C-Suite, where one CMO was asked by their CEO, "Hey, I think you can do marketing with 80% less staff," so just on efficiency, right? Not on productivity, not on quality. And in fact, I think there's a huge risk right now that the efficiency is not leading to quality. Sometimes it is. You can be efficient and just get garbage out. By the way, a CMO right now is having to answer that question and push back on the CEO on this productivity question, I mean. And then maybe this is a good time to get into a use case, because I'm all over the place here at the moment, and you've presented a great framework, but can you give us an example? We'll just focus on productivity; maybe we'll go to quality in the next one, and then we can talk. So either one of you want to share an example of where somebody you've worked with has found some incredible productivity gains?

Tahnee: Yeah, I've got a couple. But given that you talked about video, this was actually a client that Liza and I worked on together, and we consulted with their content development and video team. They had, I think, three people who worked in video production, and their job was to basically take orders from the marketing team, who would say, "Hey, we have this new product. Can you create a promo video or an explainer?" Whatever it was. And their original process took six weeks, because what they would do is they'd have the kickoff meeting. They would talk about what they wanted, and then the video team would go off and they would do their research. They would storyboard. They would come back in two weeks, and they would look at this beautiful storyboard, and they would say, "Yes, no, let's make changes." And they would go round and round in these meetings until they got to the final point where they were happy. And they'd go into final production with AI.

We helped them create a process where in the very first kickoff meeting, they would ideate and storyboard, and they would have the entire plan set in that first meeting. And what they were using is a combination of ChatGPT for ideas. They used Canva's storyboard feature to build out the storyboard they could look at, because they found that the marketing team needed those visuals to really understand what the final piece would look like, and they cut down their entire process to two weeks and they'd have something final. So those are huge productivity gains. And also it's effective, because the teams working, they had a much tighter feedback loop, so they were happier with the final product. So that's a use case where you get both—you get efficiency and a better outcome.

Drew: Right. And better buy-in, because there's a lot less guesswork. Because, I mean, particularly using Canva storyboards, you're not going to have this where you go out and produce and say, "That's not what I thought of," right? That's not the look and feel. So this really is—that's a great story. Liza, do you have another example?

Liza: Yeah, I do have another example that leads into the quality piece. First we started with productivity, and the team was using it for content creation, and we all know those use cases, right? It could help us create blogs and reports and all sorts of things, but they found that it wasn't quite landing. The content didn't have the quality, it wasn't as relevant, it wasn't personalized to the buyer's journey. And, you know, in AI search, you have to create content so relevant that it directly answers the question or inquiry of the user in AI search for the AI to actually serve you up, because if you don't answer that question directly—if your content and brand don't answer that question directly—you're not going to get served up and we're not going to get cited. So, big problem.

One of the key things beyond productivity was that we needed better quality content. So now we are using AI to actually figure out, anticipate, figure out what these questions are at the top, middle, and bottom of the funnel that customers might be asking. And what we did was we used customer reviews, publicly available customer reviews, G2, Capterra. We also use customer testimonials, Gong transcripts, all sorts of things to then ask AI to infer from these customer reviews, transcripts, testimonials, and publications what might be these inquiries at the top, middle, and bottom of the funnel based on that set of questions. So it gave us a response, we then validated that, and then, based on that validated set of questions, we created the content to respond to those questions directly. So now it's not just productivity. Now we have improved content as a result of that research and validation that we did.

Drew: Amazing. Thank you for sharing that. One note: I feel like every website somewhere has to answer every question that the customer wants, and that there's a Q&A—that's a new part of content marketing in general. But what's so inspiring about this one is that you're not guessing at what the content is. You actually have a body of information that is informing that. And I think if you think about that as our general rule, it's: the more original content and information you provide upfront at the top, the better output you're going to have. That's right. Well, if you start with a blank slate and say, "Hey, write a blog post on this," you're gonna get garbage. But if you say, "Take all of this information and quote it and use it, now create something," you're gonna end up with a better output. Fascinating and good.

Okay, we have a couple questions from the audience. We might as well get to them. Say to them, this one's for Liza: what advice do you have for successfully making the case to your CEO and executive team for creating AI agents that can help augment and extend the effectiveness of your marketing staff? If you want a phone or friend, or pun on this one, it's okay.

Liza: This is one of my favorite questions, because it is truly rethinking marketing and reimagining our organizations, right? Many of us have this challenge where marketing is seen as a tactical organization and we are seen as non-strategic. I'm not going to generalize for all, but there are many marketers and many marketing organizations that are seen that way. And I've also said before that, you know, it's one of the biggest reasons why we're not on boards as CMOs and heads of marketing. So I love it when a CEO says, "Hey, tell me about your evolution of marketing with the use of AI," because I go straight into the evolution. We will go from org charts to work charts, where org charts will no longer just be human beings. We will now be using AI as teammates, and these teammates will be built, maintained, and managed by the humans. And what does that do? We will relegate a lot of the mundane and repetitive tasks to the AIs to free us up to do more strategic work. "What do you mean by strategic work?" Well, guess what? We're gonna figure out product-market fit because we can't, you know, just like we can't out-exercise a bad diet, we can't out-campaign a bad product-market fit. So now we have the capacity to figure out good product-market fit. Right? When we do that, when we campaign, it will land and we will not be wasting resources. So that's a really tangible thing that I share with CEOs.

And then we talk about, "Okay, Liza, what are these teammates?" So I'm like, "Okay, product marketing, let's pick on that. They create battle cards, they create decks, they create pitch decks, in addition to all the strategic things that they do—segmentation, targeting, positioning, messaging, and all sorts of things. If we had AI assistants or AI teammates that created these pitch decks and created these battle cards for them, can you imagine how much better they can do on segmentation, targeting, and positioning? Same thing on digital, same thing on demand gen, same thing in the other organizations."

So I think this notion of crafting a story such that marketing is now viewed as strategic and truly a growth engine for the business, rather than simply saying, "Hey, we can make this efficient and we can be more productive," I think that doesn't bode well. I think that brings us down the path of, "How many people can you lay off in the next six to 18 months?"

Drew: As opposed to saying we can create superhumans, and we're going to get so much more done, we're going to get the efficient stuff out of the way. We're going to be more productive, but more importantly, we're going to be spending our time in places that are going to have a dramatic impact on the business. I love that perspective, and in many ways, that has been the path of automation thus far—augmentation versus replacement—but there is a lot of fear about replacement. So Tahnee, what's your take on this?

Tahnee: Well, there used to be this phrase that, you know, AI is not taking a job, but someone using AI will. I actually think that's just false reassurance, because AI is taking jobs. The thing is, it's taking the repetitive ones, ones where it's a lot of hunt and peck. So I think people who fill in spreadsheets—you know, there's been a lot of impact on graduate jobs, right? Those entry-level intern roles where you just have to do a lot of rote work. So I think we all just have to be honest and say that those kinds of jobs, there's going to be less of them, and maybe soon none of them. So as a person who's moving into a career, what kinds of things do you need to be skillful at? You need to understand how to use AI, and you have to understand how to drive value and more value at a higher level. Because to get into a position, you're going to have to prove that. I think, as a CMO, your job is to have a look at your entire organization and find the places where you can automate work and the places where you still need humans in the loop—places that require judgment, creativity, taste. Like taste—AI has no taste. And what we're finding is, I think this was Andy Crestodina, who quoted or she coined the term, is that AI is creating the average information because it's been trained on, you know, the world's information, so you get the average of that. So if you want to create something that has a point of view, that stands out, that differentiates your brand, you're going to need humans for that. So as a CMO, it's your job to figure out what do you give to the AI and what do you keep for the humans?

Liza: Hey, can I add to that, Drew? I'm looking at the chat, and I want to answer the question, but I'm like—my fingers are not fast enough. So there's this question around—well, it wasn't a question. It was an observation that CEOs go straight to replacement rather than augmentation, right? Which is such a typical—you know, I'm hearing it more and more now. My initial response about a week ago, somebody asked me this question, and I said, "You know what, if they go straight to replacement versus augmentation, then they probably feel that there was already bloat in marketing, and they probably feel that marketing wasn't as strategic, and probably thinking about it more tactically, right?" And if they go down the other path of augmentation, maybe they do feel that there's value in marketing, and what they want to do is to get more of that value with the use of AI. But then, as I think about it more, I'm now running into a lot more companies where it's driven by EBITDA, right? So it's sustainable profitability. And when you go to sustainable profitability, if you're looking at the spend—in the spend, typically, the highest spend area is people. So that's what gets picked on, right? So this whole notion around, "Hey, how do we reduce the number of people and help us with profitability?" is coming to be, and I think as CMOs, we need to really anticipate this question and get ahead of that question before it gets asked of us. So one of the key things is, I think the upskilling and re-skilling of the workforce is first and foremost. And I think about it in three layers, right? There's the senior team, senior executives, mid-level management, and then entry level, and I'm just formulating my opinions on this. So you guys—you know, I don't—I'm open to be challenged on this, because I've never gone down this path. We all have hypotheses, but I think at the senior levels, we need to figure out how to use AI to help us understand and do jobs that are one to two levels below. Middle management needs to understand how to use AI so that they can perform one to two levels above or one to two levels below, and that entry levels need to figure out how to use AI to perform their jobs two to three levels above them. The reason why I'm framing it that way is because I believe what Tahnee's saying—there will be less, and those that have the ability to flex and go down, up, essentially sideways will have much better potential of keeping their jobs. When the board and when the CEO says, "Hey, it's about people, it's about EBITDA," the chosen ones will be the ones that can do much more than what they're doing today, up and down, if that makes sense.

Drew: I mean, I'm going to weigh in here on a couple of fronts. One, there is no proof yet that a company that has more bots than humans is actually going to be more effective. We already know the use cases of Klarna, where they, you know, turned it all over. It's a powerful story. And obviously they went way too far, way too fast. But we still don't know. I mean, yeah, we can automate this stuff, but we don't really know yet whether it can be more effective. And so yes, a PE firm—if we were actually building our own business, we might look at it differently. We might say, "How do we build the best organization to serve our customers?" You know, growing, and we may or may not get to this place where it's 80% bots and 20% humans. I just wanted to put that out there, just to remind us of that. Number two, I think while we have seen a drop in entry-level jobs being hired, I think that there's a combination of things going on economically that are slowing that—they're just because people are nervous and there's almost so much uncertainty. But I also think there's this moment where a junior person can do so much more than they ever could before. And so I wonder, as we start to think about the future of this team, is it about having utility players who know how to use these tools and can move around and cover a lot of ground, because they now can move so much faster? And so that's about judgment and curiosity and willingness to learn. And you know, that starts to be the scorecard. And to me, that's sort of the perfect world. This is me, rose-colored glasses on things. But yeah, I'm not ready to say don't hire anybody junior, because you can replace them all with bots. That, to me, is silliness and bad for a long-term organization.

Liza: Just to give you a counter to that, and I don't know if it's a counter, right? I have a CEO—small, small company, $10 million company, right? And they lost their head of HR. But then they have an early-in-career HR manager. So they were trying to figure out, "Okay, do I hire another HR lead, or can this HR manager actually do all of HR?" So what they actually did was they have this HR manager working with four AI agents specifically designed to do functions—specific team functions in HR—and now they only have that one HR manager with that team of agents doing HR for the entire company. So this is like one scenario where entry level actually became the one that's now leading HR.

Drew: I would talk to me in a year or two years. Have they built a great company with a big culture? Have they done things that actually propel it, or have they just been efficient? And again, we have to differentiate in all these conversations between efficiency and effectiveness. And if you just look at efficiency, there's going to be a lot of mistakes made in these tools. So let's talk about efficiency. One of the questions is, how do you think of measuring AI investments, and what kind of things are you seeing out there, or what recommendations are you making when it comes to measuring AI investments?

Tahnee: I think it depends a little bit on your company and your team and the work that you're doing. So you have all of the usual KPIs that you measure as a marketing team, as a CMO, and it could be MQLs, SQLs, it could be leads generated, website visits. I think you need to keep track of all of those. But when you're talking about AI efficiency, I think the best way is to sit down with your team and you track or you transcribe the manual process that you were doing before, and then you do the new process, and you look at where you've saved time. And then you can do a comparison. And then you also want to look at, are you saving budget? So do you have to hire less agency time? Do you need fewer translators? So again, another project Liza and I did, they looked at it holistically, where they tracked the hours of the internal team. They also looked at budget saved. And then the other metric I really love that a lot of people forget is team satisfaction. What they found was that because people were spending less time on these boring tasks they didn't like, they were delegating them to AI, the team sentiment went up, like, I don't know, 15 points. It was really high. And you cannot underestimate the value of a happy team. A happy team has curiosity. They come up with new ideas, they innovate, and then they drive more revenue for your company. So I think of it as hours saved, budget saved, and team happiness.

 

Drew: For the rest of the conversation with Tahnee and Liza, including their favorite Gen AI tools right now, visit our YouTube channel, CMO Huddles Hub, and if you want to meet them face to face, make sure you get your ticket to the CMO Super Huddle this November in Palo Alto. Hope to see you there.

Show Credits

Renegade Marketers Unite is written and directed by Drew Neisser. Hey, that's me! This show is produced by Melissa Caffrey, Laura Parkyn, and Ishar Cuevas. The music is by the amazing Burns Twins and the intro Voice Over is Linda Cornelius. To find the transcripts of all episodes, suggest future guests, or learn more about B2B branding, CMO Huddles, or my CMO coaching service, check out renegade.com. I'm your host, Drew Neisser. And until next time, keep those Renegade thinking caps on and strong!