The CMO's AI Implementation Roadmap

 

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 6 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 Huddles, Quick Takes, our Tuesday Spotlight series where we share key insights from CMO Huddles, Bonus Huddles. Today, we're talking with Tahnee Perry about building a Gen AI savvy marketing team, and as a leading consultant in this space, she's seen where most organizations stumble. In just under 30 minutes, Tahnee reveals the three critical mistakes CMOs are making when driving AI adoption, plus her proven four-step formula for successful implementation. One more note before we start: AI Trailblazers Tahnee Perry and Liza Adams will be joining us for another Bonus Huddle in June to share how in six months, an organization transformed a lean, 25-person marketing team into a 45-member human plus AI powerhouse. If you want to join that one, apply for membership at cmohuddles.com. Okay, 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! I'm thrilled to introduce you to Tahnee Perry, a leading Gen AI consultant who's helping marketing teams transform their operations through responsible AI adoption while maintaining their human-centric approach. What could be better than man and machine? Anyway? Hello, Tahnee, how are you and where are you this fine day?

Tahnee: Good morning. Thank you very much for having me. As I was seeing people's videos pop up, it's great to see all these familiar faces. I'm in another group, Coffee Talk and so Nancy, nice to see you. I didn't realize there was so much crossover. So I'm actually calling in from the Bay Area. I'm just outside of San Francisco, and it's, I think it's like 37—oh no, 41 degrees today, which is that's like being in the middle of the Arctic for a Californian. So I'm feeling a little chilly myself, but all you folks who are in those 8 degree temps, I don't know how you do it. Bless you.

Drew: You don't go outside, that's how. And you have wonderful jackets and coats and boots and all those other good things. But I can't, you know, having now hearing the Australian accent, Sydney, Melbourne, you know, how do you end up here?

Tahnee: Yes, originally from Melbourne, and I try to get back there as much as I can. My dad is actually from the States, and so I grew up hearing about America in this wonderful country, and when I graduated from college, I decided I'd come over for a year and just do a year and try it out. And I never left. So I'm still here.

Drew: All right, decades later, we have that way. Love it. So, all right, I know that you are doing a lot of helping organizations sort of bring Gen AI across, particularly with marketing departments, adoption and so let's start with three common mistakes you see CMOs making when trying to drive Gen AI adoption across and just sort of list them, and then we'll go through them, one at a time.

Tahnee: The three most common mistakes I see CMOs or team leaders making, because it's not just in marketing, it's across an organization. The first one is not investing in formal training and just hoping that by talking about AI, everyone will figure it out and it will work. I don't see that working as well as it should. Second is trying to implement AI or looking for a tool, without sitting down and figuring out what goals you have. Or even doing your strategic planning, it's just like, let's throw some things at the wall. And yes, there's the place for that, but I think CMOs really need to spend more time goal setting than they do, and three, ignoring the fear and uncertainty around AI. So I think team leaders sometimes underestimate how much change management you need to apply when it comes to AI, because this is brand new, there is a lot of uncertainty around it. And if you don't take the time and you're intentional about that, then it can create a lot of angst with the team.

Drew: I love it. It's great, it's funny. I was working on one of my Saturday rants, and the headline is, "Just go play!" You know, said the CMO and, and I think that's so 2024 if not 2023 but let's talk about, what does it really mean when you say, invest in training? What does that look like today?

Tahnee: What's worked really well for me, and I do this with a business partner as well, is you sit down with the executive team and you run a discovery session and figure out, what is it that you have pain points around today, and how are you trying to address them? Where can AI fit in, and then plotting it all out and being really intentional about how you train your team. The thing with AI is that it really to get the most out of it, it's dependent on each role, right? There's no one size fits all for Gen AI, so if you are a search marketer, you're going to use it very differently than if you're a growth marketer. And so what's worked is breaking all your teams up into their functional roles, and then providing training for that role, because then they have time to talk about their use case, because their use case won't be a use case for someone else. And I think for people to really get the most out of it, they need to understand how to use it for themselves, right? So I think that's the main point there.

Drew: It's so interesting, because if you go back to go play, what go play meant was, oh, go get on ChatGPT, and start creating stuff. But you know, not everybody on the team is a content creator, so that's a problem, and or they might be visuals or so forth, and then they might try it. But without proper training, you just sort of start doing stuff, and you hit a wall pretty quickly. You say, Oh, that isn't very good. I don't need that. And so initially, at least. And you know, in 2023 and 2024 a lot of writers said, Oh, I can do better. This is stupid. Why am I wasting my time. So the challenge that I see in this is sort of and is built into the solution is people forget. They can ask these machines, how do I get the most out of you? You know? How do I solve this problem, as opposed to that basically summarizing that first one, it's training in context of the challenges that you have and the role that you play within the organization. So obviously, that takes a flexible training partner, whether it's, you know, it's an organization like yours or others, but you can't just say, I'm going to train you on ChatGPT, that won't, that won't be enough.

Tahnee: I just have quick note on that. I've seen a lot of companies say, you know, go out and get your own training. So go take a course. And there's nothing wrong with that. It is helpful. But what I would say is, a lot of those courses are very generic, right? So you're just kind of learning the basics, where teams really get the most and they really start to excel is when it's designed specifically for their job. And I think that's why it really helps a company and a team if you hire an AI expert in your industry who understands your use cases and what your customers are going through, so you can, kind of, you can align all of that together.

Drew: Right? And it's interesting because we had a huddle reach out who wanted to do a boot camp for their entire marketing organization, and I realized initially, and as I as I thought about it, that part of the boot camp is to sort of explain, kind of the art of the possible, but ultimately, if you don't get it into specifics, the context of the need, it's going to go over people's heads. They're not going to get the information they need. So this has to get very specific very quickly, right? Definitely. Okay. So we've seen this with all tool adoption is there's a bright, shiny object, it's a tool. We all love our new tools. We say, oh, let's go do let's go get that one, because everybody's talking about that tool. And so you've get your ready, fire, aim problem, which we see so often in so many different adoptions of technology and marketing, when it's working well and we're setting the goal. First, can you give an example just of a CMO saying, This is my goal, and then finding the tool that would that would work?

Tahnee: I am seeing this a little bit less now than I was last year. Last year, everybody wanted their silver bullet. They wanted to grab a platform and just, you know, kind of stick it into the tech stack, and that's going to solve all our problems. And what I was advising is you should sit down and do an assessment of the current stack, tech stack you have, because there are a lot of platforms that are developing their own AI functionality. Take Salesforce and HubSpot as an example. They are working really, really fast to launch AI features. Salesforce has Agent Force, HubSpot has Breeze. And what I was finding is you'd have these marketing teams that were going after these newer platforms and ignoring what they currently had in house. And I was like, You don't need to do a search until you sit down and you figure out what your goals are. You do an assessment of your current tech stack and then figure out what's missing, because yes, there are always gaps in some of these bigger platforms that maybe don't suit your needs. And so that's when you say, Okay, now let's go out and look for a platform that will solve our problem.

Drew: So this is tricky, and I want to push back a little bit. You don't know what you don't know, in terms of what problems these tools can solve. And so you might say, "Oh, I have a problem in the pipeline, moving from top of the funnel to bottom of the funnel," that's a problem. But you might not realize what you really have is a workflow problem where we've got content creators over here, we've got web managers over here, we got SEO people over here. There are a lot of different touches. And right now, lots of things move manually, but somebody has to sort of show and say, "Hey, this is a use case that you may not be thinking about," right? So that's the tricky part of goal setting and these tools, because they're solving problems that we didn't even think that we needed to solve.

Tahnee: Yes, not an exact science. Sometimes we find we have people who come and say, "Oh, we have this problem and we want AI to fix it," and we dig in and we ask questions. We're like, that's not an AI problem to solve. It's something different. It's either a people problem or, like you said, it's a process problem, and you can use AI maybe for a small portion of it, but you need to architect this thing in a different way. And AI is not going to solve it all for you.

Drew: No? Oh, come on, we just put it in there. Help me solve this problem. And you put it all in there, and they outline it for you. I do think there is a bit of "there's nothing AI can't solve" syndrome right now, right? There's a little bit of that. And I think it is important to at least give these tools a chance to help you think through a lot of this. But so, all right, the third point was ignoring the fear and uncertainty. Let's talk about that and how you help sort of brands think about this and solve that, specifically Marketing Leaders solve it.

Tahnee: I think this is something that you could partner with your HR leader, your team leads, so if you have VPs and directors, and what I've seen work really well is you sit down and you plan out exactly how you're going to introduce artificial intelligence into your organization, and many of you are probably already doing this because it's been such a big topic for the last couple of years. But I do think there's still time, a time and a place, if your team is feeling uncertain, especially if they're hearing about layoffs, to say, "Okay, here's how we use AI in our company and why. Here's our AI policy. Here are the rules." I think people get... There's a lot of fear and uncertainty when people don't understand how to operate, right, if there's no clear guidelines. So the first thing you need to do is, I think, have an AI policy around how to use it and how not to use it, because that's very helpful. And then the second is reassuring your team that your plan is not to replace them with AI like they might be hearing. It's to integrate AI as a part of their day to day to help them do their job better. If you encourage your team leaders to sit down with each of their solo contributors and say, "Okay, where are the areas where this could help you? And let's work on integrating it," then they'll see the proof in your statement that you're not going to replace them, and that, I think, builds a culture of experimentation, of support, adaptability, creativity, instead of a culture of fear, where everybody feels like, "Okay, I could be next. I might be losing my job here as soon as the AI bot is better than me."

Drew: So let's talk about two things separately. First, on policy. As you were talking about policy, I'm thinking about, man, this has to be pretty dynamic, because these new tools keep coming out and doing different things, and they keep getting better and better and better. So what does a good policy look like right now, and how do you keep it up to date?

Tahnee: Yes, what I've seen work is companies who develop an AI Council, or committee. It doesn't need to be super formal. It should be a collection of folks who are really passionate about AI. And you get a broad cross section of people, if you're just doing it for marketing, people in all your different marketing departments who sit down on a semi-regular basis and say, "Okay, how do we want? What do we want the rules around AI to be? What are the privacy concerns, the security limitations? Do we need to consider any legal aspects?" and then draft up a... it doesn't have to be like a 14-page document. It could be like the 12 commandments, for example, "Do not put PII information, you know, personally identifiable information into any chatbot, even if it's a pro account where some of the security is a little more robust, even then, don't put any PII in. That's a really bad thing to do." "If you are using a tool for company work that is not part of our tech stack, make sure that you let us know that you're doing that, just so that we have awareness." So it could just be simple things like that. And then the second thing I think you should do with your AI Council is make them available for people who have questions. Because every company, every team, is different, and people will naturally as they start to experiment and use these tools, think of things like, "Oh, am I allowed to do this? What are the implications if I do this? And should I be worried?" It's really great if they have somewhere to go to get that answer. And so I think if you have a policy and a committee or a council that can help people answer those questions, again, you're going to foster this culture of accountability, of openness, trust, transparency, and that will really help.

Drew: It occurred to me, as you were talking about that, that it would be very easy to create a little chatbot that had all the rules that you could ask, yeah, exactly. Create your own. So now we're using the technology to help us manage the technology. But that's really where this will go, right? You upload the information. "See, this is our policy. Talk to the bot if you want to get the baseline, talk to a human, if you really want to go deep or you have concerns."

Tahnee: Exactly, you know, it's funny, you'd ask me for some examples, and I have one. So I work a lot in the travel industry, and I worked with a travel manager who, if anybody travel has a works at a very big company, there's a travel policy, right? And the travel policy can be very long, you know, how much can you spend? What hotels can you stay at? What's your per diem? And travel managers, they get questions all the time. So what I do is I help them load their policy into 11 labs, and we created a voice agent, and then they just published the voice agent, and anytime they got a question from a traveler, they said, "Go to the travel agent bot, and it'll answer it for you." So you could do something like that.

Drew: Right? Yeah. I mean, again, you can use the tool to solve the problem. I want to go back to, "you're not going to lose your job." People are going to lose their jobs. There's no doubt, I mean, this is like saying to the blacksmiths, as Ford is getting his assembly line going. "Oh, don't worry, there'll be plenty of jobs for, you know, guys making horseshoes." No, those jobs are going to go away. And that's a very bad analogy, but in the sense, and we're already seeing this, that people are right now, they're moving people around because at least their content teams are getting that much more efficient. So I wonder if it's a false promise to say no one's going to lose their job, certainly the people who don't adopt these tools are going to lose their jobs.

Tahnee: Yeah, I wouldn't promise that no one's going to lose their job. I think you could say our intention is not to replace you specifically with AI if that is your intention. Obviously, if you do intend to completely rip out your entire marketing team and add in AI agents, you could do that. I don't at this point, I don't recommend that. At least I haven't seen anybody pulling that off successfully. I still... you need humans to drive the AI, but I think over time, what you can do is you can be honest with your team and talk about how technology is making everyone more efficient. There are going to be some roles that become obsolete, and you need to keep a close eye on what those might be. And then you need to go to the folks that are in those roles and say, "Hey, you've got a choice. You can upskill into something else, or you could go somewhere else and find something different. And we'll help you do that." I think if you just, like, sit back, relax and don't pay attention and then let it all like, hope that it gets figured out, then you're going to have mass hysteria in your company.

Drew: I think there's a couple of consistent things. We're training you so that we're upskilling you. We're giving you the opportunity to grow into this new world and get ahead. And so in doing the training, in a sense, you're taking the fear out of it, because you're showing them that they can do this. You're also showing how it applies to their job specifically, and then upskilling them. You're preparing them for the thing that feels like a very positive way of talking about this is that we're going to enhance your ability to do your job, and we're not going to leave that to chance by saying, "Go play." We're going to work with you to do this again. Having said all that, we already know that PE firms and so forth are saying, "Do more with less." Marketer, do more with less. And Gen AI came in, there's a presumption, at least among this particular finance group, that Gen AI and AI means that you can do more with less people. That's a tricky time. So all right, we've covered those three, and that was a lot. Let's talk about there are within companies, there often are these early adopters or trailblazers, if you will, that come out. Can you talk about some in your experience, where some of these champions have come from, and how they are driving real change?

Tahnee: Yes, I have a couple of examples. There's one client I've worked with, and I really love this client, because there were all these people. They weren't even in leadership roles. They were sometimes solo contributors. They were managers or directors, and they were really leaning in on the AI. So when I went in and I advised with them, they were already very far along and very open to experimentation. And there's this, there was this one gentleman who was part of the—it was a media brand in the automotive space, and this gentleman was in the, I think he managed the content platform, so he wasn't responsible for the website. And what he saw was that they would get hundreds of press releases every day from all of these automotive companies, and all of these companies wanted them to publish their press release. And of course, if you publish a press release, it's so boring nobody wants to read that. It's just, you know, like company boilerplate, but they're reporters. They had a pretty small writing staff, and they didn't have time to go out and interview every single client or figure out what exactly they wanted to publish. So this gentleman went to the engineering team and worked with them to use the OpenAI API and wrote a very long prompt that took the content of the press release, turned it into a template, using their style, what they liked to have in their articles, and then it automatically delivered that new template and PR to the writer and said, "What do you think of this content? Here's some where you like. Here are some sections where you might want to add in some of your own thoughts or commentary." And the reporter could spend maybe five or 10 minutes reviewing it, and then hit publish and it went straight into the website. So I was really impressed with that, because this gentleman didn't have any coding experience himself, but he went to the software development team and said, "Can you help me set this up?" So to me, that is a great example of a champion in a company who is improving workflow, saving time, helping them do more with less, all on his own. And you'll find people like that in every company.

Drew: And I love that example, by the way. We had this very conversation about, how could we use this tool to create this kind of workflow? And I'm so glad you're—we're talking about it, because, to me, that's where the most exciting use cases of this content is low hanging fruit. Yeah, great, awesome. If you are, have really good editors who can create content that's, you know, 95% better than most, awesome. But workflow, like what you described, if you had to do it manually, would have taken hours and hours and hours and hours and multiple steps. And I want to talk to that person how they did it, because I need that. We have a very specific use case for exactly that. And I know that as the CMOs start to think about their various steady content workflows or problems that they have, and realize, "Oh, my God, I can do things I could never do before." Either they're gonna have to wait for a Read.AI or an Open dot—you know, some of these other—Write, some of these tools that are coming out to try to solve these workflows, or they're gonna have to figure out how to create their own. So interesting. You said—do you have another example? That's a great one. Do you have another example like that?

Tahnee: I already told you about my travel policy. That was my other example, because that was another—this particular company. It was very large, and they had no formal AI policy, even though I was encouraging them that they should do that. But the travel manager had this real pain point, and was being inundated with his emails. So, you know, I was like, you could do this on your own, if you can get approval to use the tool, and then you just—then you just host it. And so that's another example.

Drew: I've got to believe that you could go on ChatGPT or Claude, and say, what are the—you know, outline what should be on a policy. Then you could start to, if you had a private sandbox, start to put in your own kind of things, concerns. Then you could work with it to get to a policy, probably pretty darn quickly.

Tahnee: Yeah. Actually, what you could do is you could take some of your corporate documents, you know, your employee hand guide, if you have a culture or vision document, a mission document, feed all of that in and say, "Okay, based on what you know now about our company, help me create an AI policy that fits for who we are."

Drew: Right. So, yeah, use the uploading capabilities of these GPTs to get to know you and write something custom. Yeah, it always comes down to original data. It's funny, almost all of this does, and that's such an important part of thinking about the applications of this is understanding that the better the data, the more first party, the more personalized, the more it is about your company, the better. The output is going to be fascinating. Okay, let's talk about your four-step formula for AI adoption. Can you walk us through what teaching teams to collaborate with AI looks like in practice?

Tahnee: Yeah. So I have four steps. The first is—we talked a little bit about this—setting goals and having a strategic plan. Two is building your learning program. Three is giving them the right access to the tools, and then four, giving them some latitude to fail. So to go through that in a little more detail, setting goals in the strategic plan. You probably already have a strategic plan as a CMO, so take that, review it, and see where you think AI fits in, so that you have very specific, measurable goals and tactics around AI. The second is, build your learning program. I always recommend formal training, which we talked about, but if you don't have the time or the budget for that, there are other ways to get around it. There are always people in your organization who love artificial intelligence and experimentation, so pull them in, create a series of lunch and learns, or ask folks to talk about their success stories on your all hands, maybe you spend five or 10 minutes where each department has to share what they've done in the last quarter that really changed their workflow and saved them time. So there are all these little things that you can do as part of your day to day, to help your culture learn and then giving them access to the right tools. I'd say again, go back and assess what you currently have and make sure that your team are using those features and holding them accountable for using them. And if they don't have an understanding of it, maybe you get in touch with your customer service rep and say, "Hey, you know, can we set up a training for the AI features that are a part of your platform?" And then if you don't have the features you want, that's when you go out and you do a formal RFP process for something new, and then finally, for allowing latitude to fail. People don't like being told that they've done the wrong thing or that they are in trouble for trying something new. So I think you have to be really clear. As the CMO you can say, "Here's your sandbox. Here are things that you can do. Here's the space that you can play in, and it's okay if it all goes wrong. Here are, if these are, if you have mission-critical areas of your business, that it would be catastrophic if AI did something that you didn't expect, then you'd be very clear, do not experiment in that section. Just stay away. You know, there's a tried and true process for that. Let's not mess about with it." But you have to give your team space to be able to fail at things that are less mission-critical. Otherwise you won't, you won't ever find out those things, those workflows, the processes, the tools that really help move you forward.

Drew: Boy, a lot of things to unpack there. And that's exactly what we did in the rest of the conversation. If you'd like to hear how these concepts play out in real-world marketing teams, Tahnee's favorite Gen AI tools and special guest Liza Adams, innovative human-AI org chart, continue watching on the CMO Huddles Hub on YouTube. We've included a time-stamped link in the episode description that picks up exactly where we're ending now. To get more Tahnee, I highly recommend subscribing to her newsletter, Zero to Unicorn, and following her on LinkedIn. And if you want to participate in future bonus Huddles, visit cmohuddles.com to join our free starter program. I'm Drew Neisser, and we'll be back with another huddle. Quick take very soon.

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!