February 13, 2025

Turning GenAI Possibilities into Reality

Gen AI isn’t just a playground for creativity—it’s a tool for real business impact. But while some marketers are embracing the possibilities, others are stuck in experimentation mode without a clear strategy. So how do you go from dabbling to driving real business impact with AI? 

In this episode, Lisa Gately, Principal Analyst at Forrester, joins Drew Neisser to break down how CMOs can lead the charge in AI adoption, avoid common missteps, and harness Gen AI to create real business value. Lisa also shares a sneak peek into her session at Forrester’s 2025 B2B Summit, exploring how AI is reshaping marketing, sales, and customer experiences. 

What you’ll learn: 

  • The top mistakes marketers make when adopting Gen AI—and how to avoid them. 
  • Why Gen AI success requires change management, not just technology. 
  • How CMOs can go beyond efficiency to drive real competitive advantage with AI. 

Want to take your AI strategy to the next level? Tune in! 

CMO Huddles members also get a 10% discount to Forrester’s 2025 B2B Summit—use code CMOHUDDLES25 to save!

Register here: https://www.forrester.com/event/b2b-summit-north-america/  

Renegade Marketers Unite, Episode 436 on YouTube 

Resources Mentioned 

Highlights

  • [1:03] Meet Lisa Gately  
  • [1:58] 3 GenAI mistakes B2B marketers are making right now  
  • [3:41] Don’t neglect AI literacy & change management  
  • [8:02] Don’t over-focus on tech  
  • [11:02] Where to prioritize GenAI usage  
  • [16:32] Real world applications  
  • [19:27] Adopting a GenAI center of excellence  
  • [21:18] Cutting headcount vs. enhancing creativity  
  • [25:42] GenAI for better event feedback   
  • [29:11] GenAI as sparring partner  
  • [30:52] Orchestrating cross-functional collaboration  
  • [39:44] Avoid micromanaging AI adoption  
  • [42:08] AI for personalization at scale  
  • [44:55] Dos and don’ts: Starting or scaling AI   
  • [47:28] On Forrester’s B2B Summit

Highlighted Quotes  

“People think of GenAI and stop at content generation. I look at this as: How does GenAI enable you with better planning, better precision, and more customer centricity?” —Lisa Gately 

“For this company’s AI literacy program—people were reporting time savings that equated to 14 FTEs for the year.” —Lisa Gately  

Full Transcript: Drew Neisser in conversation with Lisa Gately

Drew: Hello, Renegade Marketers! If this is your first time, welcome, and if you’re a regular listener, welcome back. You’re about to hear a bonus huddle where experts share their insights into topics of critical importance to our flocking awesome community. In this bonus huddle, Forrester Principal Analyst Lisa Gately will give us a sneak peek of her keynote at Forrester’s 2025 B2B Summit in Phoenix in March. Be there or be square – I’ll be there. The topic is generative AI and how savvy organizations are going way beyond content development to exploit this transformative technology. I’m excited to be attending. If you’re going to be there or want to buy a ticket and need a discount code for our community, we’ve got one. So just let me know. If you like what you hear, please subscribe to the podcast and leave a review. You’ll be supporting our quest to be the number one B2B marketing podcast. All right, 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, Huddles! I am excited to introduce you to Lisa Gately, Principal Analyst at Forrester, who’s joining us today to provide a sneak peek at Forrester’s 2025 B2B Summit through the Gen AI lens. Like, is there another lens? I don’t know. It’s hard to find one right now. We’re also, side note, delighted to know that Huddles receive a 10% discount on the event. Okay, with that, just a little bit more on Lisa. She has 20-plus years of experience in B2B technology, content, communications, events, and services marketing. Over the last two years, Lisa has concentrated on Gen AI and the transformation it is enabling. Okay, with that, Lisa, how are you and where are you this fine day?

Lisa: Hey, thanks, Drew. I’m doing well, I’m excited to be here. I’m in Oakland, California.

Drew: We’ve got some other Huddles not too far from there. So, all right, I’d like to do this. This has proved very effective. Let’s just, in case our audience has to leave early or we need to convince them to stay, what are three top – not to focus on the negative – but top three mistakes you see marketers making when adopting Gen AI right now?

Lisa: Yeah, there are so many things because it’s a fast-evolving topic, but number one is, I see a lot of organizations neglecting AI literacy and change management. One marketer said it well – she said really, if you think about all the time communicating and handling change management, triple it. I thought she had a great point. But really, why it happens is a lot of organizations may assume people are going to figure this out. They are really enabling an experimentation mode. It’s been this early period the past couple years, but really it underestimates how much cultural and skill gap there is. The second thing would be over-focusing on technology, and that leads to that narrow mindset. I know we all read the news stories about cost avoidance – it’s the AI buzzword – but I really think this has much bigger implications, and marketers overall need to help refocus on some of those outcomes that matter, like revenue growth, customer retention, things that we really help stand up for. And the third thing is treating AI like it’s a standalone initiative or a siloed project. It happens naturally. I know that pockets of teams get started typically. The longer run is you’re going to be working across the aisle. There’s a lot of cross-functional collaboration to do well across marketing, product, and sales, not to mention how much we work with agencies and vendors and our partner ecosystem.

Drew: Yeah, so interesting. All right. Well, let’s go through them one at a time. I want to get deep on all of them because I think they make a lot of sense, and I’ve certainly seen it. I think a lot of folks last year, when we had Huddles, the CMOs would say, “I’m just telling my team, go play.” And that is not necessarily change management – that’s distributed “go figure it out.” So talk a little bit about, sort of, if we were to sort of say the problem is change management and neglecting it, what’s best practice? What’s a good approach to this?

Lisa: Yeah, I see this approach of some of the best organizations so far, where they are really setting up that this is not one and done, meaning you don’t have, let’s say, some kind of course or guest speaker and continue. Then once the tools are released, it’s not just leaving people to figure it out. It’s putting some rigor around it. When I talk to a lot of leaders who have teams who are reporting back, if there’s pilot project teams, you’re treating it with the same rigor that you would some other launches or major adoption projects. It’s also thinking about how this gets into your regular workflows. Yes, you have this play or pilot period, but it’s also tapping some of the experts – it’s officially part of people’s roles then to weigh in on how this is changing the way that people work. If you’re moving from your current state to future state, you’re really keeping an eye on that, and you’re also, as possible, offering some kind of what’s different – you’re giving some findings, some ratings, some measurements about that so you could tell a story about what this is doing.

Drew: It’s interesting because there’s a lot going on in that, in terms of the rigor and reporting and not being one and done. When I think of workflows, there’s the workflow of the information that’s happening as a result of the experimentation, then I think there’s this whole bigger opportunity. Because a lot of people look at Gen AI as this is a content thing, a content play, and we’re going to be a lot more efficient and a lot more productive and hopefully equally as good. But workflow is actually, to me, probably a bigger opportunity that Gen AI can do, because there’s all this massive – you know, if you think about meetings and how meeting information dissipates and the opportunity – so do you see that? And when you were saying workflow, were you addressing that, or were you just addressing the Gen AI, sort of how people need to share this information?

Lisa: Oh yeah, that’s a great one. As I bring it up because when you start to bring on these capabilities – you know, just think of some recent announcements – if you are helping people do much more precise work, or if you are helping people do a lot more powerful – I’m thinking of some aspects, yes, of content – there’s a cascading effect. If you’ve got some team members, their work changes, whether it’s the speed or how precise nature you’re able to do things, or you enable some self-service. I then look at that flow of work across marketing teams. We frequently talk about how someone else’s input is somebody else’s output. You know, those two teams may be at different speeds of picking up and using these new capabilities, and who may be doing some of these tasks. So I know that gets really deep into workflow or process analysis, but putting it together as people get more comfortable with…

Drew: Right? So with the content creation team, for example, it’s just cranking stuff out, but the legal team can’t keep up, or the web production team can’t keep up, or the SEO optimization team can’t keep up. You have a problem.

Lisa: There’s some of that. And my hopes are too that people are using this – I love your analogy – because people think about you can crank more content. How are you creating the right content? How are you understanding your audience, or where you have some gaps? How are you being a lot more precise about it? Or how are you working? Let’s say, in some companies, are you helping some of those geographies or certain verticals who really need a lot more precise help? So it’s not do more because you can, but definitely, like you say, it’s then partnering with those other teams because their – call it volume, or how much, not just how much, but the degree of what they are doing may need to change based on some of those specific needs.

Drew: Interesting. Okay, I want to keep going back to the – so the second area that you were talking about was focus. Don’t focus on the tech. Talk a little bit more about that and what we should be focusing on.

Lisa: Yeah, I think of it as – and marketers are really versed in adopting technology, but in this one, there’s so much that the broader picture in corporate life, people are thinking about cost savings, efficiency, productivity. They rotate so much there that I think marketers can do a better job. Leaders especially help highlight these opportunities where these kind of initiatives have helped you, if you’re achieving revenue growth, or you’re achieving better conversion rates, or all of the things that we are able to see that it did something for us with our buyers and customers. It’s also challenging your team. Yes, we want efficiency, and we do talk about how can we focus on high-value activities if we’re automating repetitive, mundane stuff, but it’s also challenging the team. How are we able to do some things that we weren’t able to get to before? It’s more of unmet needs from our audience, or how are we able to maybe do something really responsive to market conditions that wouldn’t have been possible?

Drew: So it’s so interesting because you – you know, and we talked about this – is that the pressure to do more with less is so prevalent that in the expectation that you could do more with less, and that Gen AI is enabling it, is that efficiency is sort of the primary goal. It feels like with using these tools right now, as opposed to what you’re trying to do, which is, you know, bigger problem solves that will help the company be better at whatever it is that they’re trying to do. And I wonder if this is a progression, is this a maturity model, where we start with efficiency and we sort of get that down, and then we realize, oh, we have more time so we can do bigger projects – is that sort of what you’re seeing?

Lisa: You’ve got it as people develop more expertise that, yes, you should be able to, and this is what help of leaders framing the things where AI can help, so that you can get on to other things. And what are those other things, if you’re helping prioritize that?

Drew: Yeah, the thing is that I can’t figure out a thing that AI can’t help with. So then I wonder, it’s sort of just going back to what are your big priorities as a company and as a marketing group, right? Because it feels like, if you wanted to, you know, whatever it is – help me get a better understanding of my target audience, help me figure out what sales enablement should look like, help me find the blue ocean space, or whatever – there’s so many different ways of applying these tools for marketers that it’s back to priorities. Again…

Lisa: It really is that the more you have a clearer focus and you’re able to help people prioritize, that directs those efforts. Especially using that power if you’re understanding the audience and then moving quickly into concept or innovation. If you’re partnering with other functions in the company about what is possible, it then gets into mega prioritizing, so that jointly, you’re doing things for the company rather—

Drew: Rather than go to the next one, which is focusing, which is about making AI standalone, I want to go deeper now on priorities. When you think about this in terms of the things that get you most excited about, or the things that you’re seeing that you’re going, “Oh my God, that’s amazing,” let’s talk about what those priorities could be or should be, in terms of usages and use cases for generative AI right now.

Lisa: Yeah, so this is a really rich one, and I’m excited. I do, in my work, work with marketers of all backgrounds across the content lifecycle. Content is usually talked about as the low-hanging fruit, but people think of it and stop at just content generation. I look at this as how does this enable you with better planning, better precision, being more audience-centric? I know you’ve had some other guests who talk about this, but I think of it as really, there are things that every marketer means to get to. I’m excited when I talk with some clients who talk about how they’ve been able to customize messaging, or how they’re able to understand personas at a better level and really develop things that are meaningful, that would help the audience and really focus on some of the areas to enable better decision making.

Drew: And so, I mean, as you’re talking about, I’m thinking about, okay, so typically it was, you work with your product team, you work with the files you decide, or the sales folks, and you create some piece of content, whether it’s a report or not, and you have everybody read it and check it and so forth. Maybe use generative AI to help you do it. Then you just put it up. It feels like in this new world, what you would do was you might do that exercise, and then you might create two other versions of it, and you’d say, for example, which of these are likely to do better against this ICP, right, or relative to all the content out there. How can we make this more different?

Lisa: Yes, I completely agree with you on are we filling a gap that’s meaningful that buyers and customers aren’t finding this first, if you’ve analyzed content available they find in other sources, but also, if you were looking against your own existing content inventory, if you were looking at all of the questions that they’re asking. If you go down that, I think the trail of this is something that really helps them. Based on what we know about our customers, we’re much better at putting out the content we have. And to your point, though, yes, you could test different types of content. You could be quicker at reformatting, repurposing, being able to get out with all the places where your audience currently is.

Drew: Yeah, I mean, that part of it is, again, this is sort of the low-hanging fruit. You do the big original report, and then you say, okay, create a slideshow version of this. Okay, create a one-minute video of it. Create an auto podcast out of it, you know? I mean, there’s just so many that all is great, assuming that your underlying original IP actually has value in the market against your target audience, right? Because if you do a study, and nobody cares about it, or it’s not really important, or doesn’t hit a pain point—yeah, you can iterate against it. But so what?

Lisa: Yeah, you can iterate. The other thing is, we talk about B2B, the nature of your really appealing to buying groups. So you also get into that element of hyper-personalization. If I’m trying to appeal to, from our latest study, if it’s 13 different members of a buying group, how do I get to being able to reach an audience like that? I know that we’ve struggled over time. Marketers think about if you were at least doing something that is vertical-specific, let’s say, or how you might do some adjustment, maybe at a local level, this gives you greater potential. If you are getting into it, it doesn’t have to be absolutely one-to-one. I think we still got some lessons to go on that, but I see some opportunity that you are not trying to do the one-size-fits-all and then maybe only one or two variants.

Drew: So have you seen a use case like this? So we’ve done a big research study for a particular vertical market, and we’ve got a lot of data points, and we know, because we have first-party data that this person coming into the website is a CFO. We could, in theory, serve up the data, probably in real time, that says, “Here are the five things that CFOs care about relative to this report,” and generative AI would help you create that iteration. Or if it was a push thing—is that what we’re looking at where we have our own information, and then we’re sort of personalizing it, I guess, against another sub-persona within that thing. That’s the idea, right?

Lisa: Yeah, yeah. I think you got it where you’re connecting what you know about your buyers and customers, and definitely take advantage of the signals that you are letting people reveal to you through more complex conversational-type questions, perhaps your website example, so you’re recognizing what’s the level of their knowledge, who they are, all of those things to then, what are these common questions? And we’re associating some of that that way we’re able to customize some of these responses, or some types of call it content. I really look at, how do we get into some smart reuse that if you’re looking across a set of personas who work in the buying group, where do they have some shared needs, making sure they get that and still being able to answer some of the unique things that your buyers are looking for.

Drew: So this feels like we’re sort of in 201, or 301, advanced applications. And you know, some folks, I suspect, are still just working on, how do we get a steady workflow in terms of marketing materials that we’re creating? And I guess from your conversations, content, real-world applications—who’s doing it well? What’s that? You know, let’s talk about what that looks like right now.

Lisa: Yeah, at a macro level, we have some survey data back, and I’m really excited thinking about organizations who have generative AI in production, and they’re pursuing content use cases as an example. What it looks like is, I see more of those organizations have a foundation, you’d call it for operational excellence, meaning they have some habits where we see from some of the data, they are very data-driven. They have a more robust tech stack. They are using more use cases that signal some of that history of experimentation. But it’s also kind of what we think of as mundane things like calendar and communication across teams. You’re looking at this as even attitudinally. They’re less worried about resources. They waste less of their content. They use more of what they have. So some of that looks at you’re handling some of these things that are foundational activities. We’ve all heard content and data that really fuel your ability to do other things with AI.

And if you want to hear specific examples, like when I think organizations—a really practical one, content is a foundation for things. I’ve been talking with a marketer from a large tech company, and they really focused on an AI literacy program in 2024. What that meant for them was, yes, there’s basic skills class that all is required for marketers, but they then develop their ongoing people who are helping them with every week, a 10-minute challenge, having office hours with different experts and experts of different backgrounds, talking about how they’re using generative AI, also setting up a resource center. They’re sharing their prompts and outputs or examples from people having a community. There’s a ready place where people can ask questions or talk to others who are working on some of their initial projects. I link that back to content because, yes, a lot of times when I talk to people, that’s an area where it’s approachable for getting started and for them, especially think of high-volume things marketers do, like landing pages, emails, you could take off all that kinds of stuff. Yes, they’re having really good results, by the way. It also though for them this literacy program, they were doing surveys and tracking over time when people were reporting it self-reporting level of how much time saved, it equated to something like 14 FTEs for the year, and just think of that. I mean, as constrained as some teams are, what could you do if you had some additional team members, or if you were able to redirect that focus? That there’s a common understanding of where do we want to reprioritize?

Drew: So it’s interesting as we focus on this notion of literacy and what that means. And again, this is the change management part of it. Unlike a lot of other things that we’ve faced in terms of transformational change in the last 20 years, this one every month—the technology moves forward, if not every week. And so you’re kind of caught up for this moment, but you’re always going to have to keep it—feels like bigger companies at least, are going to have to have ongoing Center of Excellence, where there are people whose job it is to make sure that companies are, you know, and if I were a marketer. So this is a question, then for you, should marketers start to think about having the generative AI—is the wrong term, but just that individual whose sole job is to be know what the world is doing, know how we can apply it internally?

Lisa: Yes, I do see, look, the past couple of years, this has been an additional responsibility, somebody, usually there’s a hand-raiser or an expert who has taken this on, and I’m starting to see the glimmers even in a few companies now. When you hear of AI operations roles in marketing, it is, as you say, it becomes more of, how do we help our teams? Because we’ve gotten this far. How do we go further? The organization-wide adoption is really still—it is a lot of challenge on top of the initial levels of the pilot projects and success in a few use cases.

Drew: Yeah, it’s true. I mean, marketing is often leading the way in this. And I know some places where marketing is actually driving organizational adoption, which is great, I think, in many ways, a wonderful thing. So what I also see happening, which I think is problematic, is, oh, we need fewer people for content. So that’s what we’re going to do. We’re going to save that money. We’re going to put it in the bottom line, because we don’t need as many people, and we certainly don’t need as many freelancers as we did before. Some folks are keeping their head count steady, but they’re moving them into product or moving them into other areas. And I just wonder if the opportunity, as you described it, is okay. What we’re really talking about right now is just doing content more efficiently. What does better content? What was it more dynamic content? What does more personalized content? And can we reallocate the resources so that we’ve stepped up, as opposed to just doing stuff faster and more efficiently? And I know that’s been a big point of yours, and I just, again, I’m going to ask, is somebody doing that out there?

Lisa: I see pieces of it. No one has all the pieces put together. And that is indicative of where we are, because you’re right. Every week, things change. I do see this pervasive attitude. You all have probably seen that recent press about cost avoidance, and now this attitude of “it affects your headcount, don’t expect backfills.” That kind of attitude is out there. So what I see of it as existing content roles as the example is that with every launch of something, it makes you question if everybody can take on some creation-type activities. More and more as we go forward and you look across marketing where perhaps there were activities that went to a creative team, well, now there are things that your field marketer or others could do for themselves. It doesn’t mean you’re going to cut specific roles. That’s a really tricky one to assess based on where your organization’s starting place – maybe you don’t have to add some things as you grow. Or it could be that, back to workflows, if you are looking at the other thing: assessing the skills. Just because you are putting some high-power tools in people’s hands, does your team still know? For example, is everybody going to create quality video with it? Are we really sensitive about, depending on brand guardrails, how much we know from localization as we’ve known it, how much cross-team participation there is? Is this really right for your audience, not only language but cultural nuances and being able to check content? So it’s really tricky to say that we will see certain jobs across the board go away. I think it really depends on an organization’s starting place.

Drew: I mean, if I were running an organization like that, I would want a superstar editor, a person very top of this, who understands headlines, understands good writing, understands excellence there. And then you need the same thing for video. You can’t – I mean, let’s face it, PowerPoint is a tool that everybody’s had. One out of 100 people are actually decent at presenting, you know, creating really good PowerPoints. Maybe that number is worse than that, and it’s going to be the same thing. Just because you can do it doesn’t make it good. And because the quantity of content is exploding, the premium on being great is even higher now. So I think again, there’s this missed potential. So recognize that efficiency is great, but that’s not the endgame here. It’s to solve certain problems better, faster – better, faster, right?

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Drew: So I’m wondering, because we’re moving from content a little bit, and if you’re selling, if you’re CMO right now and you want to sell, “don’t cut my team, I’m going to take it and we’re going to create some pilots that are going to blow you away” – what are those pilots? What should some of these folks who’ve gotten through the content phase, they are doing it 30% more efficiently than they were before, not necessarily better, again, same quality – what should some of the pilots that CMOs could be thinking about that would show massive sort of organizational change, like we’re closer to our customers now, we’re providing better service, we’re doing sales enablement better? What are you seeing in terms of pilots?

Lisa: Yeah, so I see some of those pilots we talked about understanding your audience better, and the elements of, let’s say, the content examples of content distribution – it’s also being able to give some kind of a feedback loop. So another area of marketers – this is from some of the Forrester surveys – we know that marketers struggle with event data. We put a whole lot of effort into some events. So whether we’re doing this for our customer event or even participating out in the industry, if you’re able to ingest and analyze a larger set of some of that data and be able to say how much we are seeing that this really engaged some of our audiences, particularly if it is your own event with customers, and what topics they need, also their sentiment, and being able to then get back to some of the experience you’re providing, linking that to what other things you’re doing in terms of other parts of the organization who are helping your customers with further adoption of your offerings, or cross-sell up-sell opportunities. If you’re able to make that kind of linkage, there’s still some areas where marketers admit we don’t have a good picture of what’s happening with our customers at these different stages, even though we’re investing, we’re doing some good things.

Drew: I don’t know if this is out there yet, but I imagine that it should be, or could be very quickly, which is, you’ve got a marketing ops or a rev ops team. They have a ton of data. It’s accessible on some kind of dashboard. But what generative AI should be able to do is, with prompts, turn that into really interesting presentations or analysis, or slice and dice and look at this stuff, which is kind of what you were talking about, just with the event data on a basic level, right? But in theory, the visualization or finding the information – is that happening yet?

Lisa: That’s classically pretty hard, and so that’s what I say. I think that is the promise of what we want to do, whether it’s the event data. I hear pockets of it. I was talking with a product marketer who was looking at his team, was looking at their company’s customer data. They were going in and looking at themes, topics, what kinds of opportunities their sales team was pursuing, and it was helping them refine some of their messaging, for instance. So it is – you’re right – generative AI should help an average marketer be able to access or ask questions of data, use some of the analytical capabilities. I don’t hear of this widespread across organizations. That’s definitely indicative of where we are of access to data. I hear a lot in our survey data that backs up confidence in the quality of data if people trust their own data. So there’s definitely foundational work to be done there.

Drew: Yeah, well, I mean, I think we had conversation – that probably Noah Briar just talking, or something else we were interviewing – but it is about data. I mean, if you have great first-party data that’s proprietary to you, you have a chance of creating content that will be proprietary to you. And if you have really good data on events and the people, then you should be able to do that analysis. I suspect there are a lot of steps in all sorts of development of whether it’s content or marketing plans or whatever, that are not going through the sort of analysis phase where you just normally, it’s just, hey, you think it through, you present it, but now you have this other sort of sparring partner that could say, find the errors. Find why this is different from our competitors. What are we missing? What haven’t we thought of? Again, depending on the data that you provide, if you have your own sandbox and you have really good data, then you have a chance of getting, I suspect, a unique answer.

Lisa: Yes, I love that because you brought up where we’re not used to having that thought partner, or the classic marketer – you’re struggling just to hit the deadline or the big meeting and have, like you said, here’s your best deliverable based on your efforts, and then look to your point of being able to examine the gaps, or being able to compare to competitors, and have that kind of back and forth. That’s new for most marketers, and really being able to use that in everyday work, never mind their big, high-visibility deliverables.

Drew: So I want to go back to the sort of collaboration part of it. It’s not something I thought about really – I mean, we talk about collaboration a lot in CMO Huddles, but the notion of how generative AI is going to impact team collaboration. Again, we’ve sort of now given everybody these very, incredibly powerful tools, and they’re all going to think that they are geniuses on every topic in the universe. And so this notion of handoffs and impact on other teams – how do you orchestrate out better generative AI collaboration?

Lisa: Yeah, that is a crux of an issue. I’m hearing a lot this past year where, whether you call it by any name – a working group, a steering group, an AI Council – that is what I hear in a lot of organizations, of people trying to get off the ground. Sometimes it’s just in marketing. Other times it’s really reaching across other teams. And it’s indicative too of maybe, as you said, if marketers are involved to a certain extent, you’ve got to eventually pull in legal, some other crucial groups. But in having, let’s say, a steering group, if you want to call it that, working on where are the nearest-term opportunities we have underway – what have we seen so far with findings? Who are the vendors we’re working with? How can we leverage them? Be smart about getting some outside expertise. Learn from others. You know, in each team also, if you’re looking at some of your next big goals, if you’re aligning together instead of everybody independently running their parallel path. For a lot of those AI councils, prevailing opinion is, you know, it’s not just your executive team – either usually you’re tapping different experts or some of these hand-raisers within each organization so they’re able to come together and report back.

Drew: Yeah, it’s funny. You mentioned legal. I remember last year, and this was just like early days of the internet. Remember talking to some big companies about, hey, you guys should get excited about the internet. And they said, “Oh well, we don’t – we’re not even letting employees have access to the internet because they’ll probably just watch porn at the office. We can’t have that.” Last year, there were still lawyers who were telling their companies you can’t use this stuff. Are you hearing that anymore?

Lisa: It’s less common, very much 2023 but less common now. Some of that is also where are some acceptable uses. And that’s where, if people are talking about what this is – you know, if you’re starting with some things that are already external-facing or from their point of view, you know how much this involves intellectual property that is still fast-changing, you know, with a lot of capabilities, where uncertainty about how some models have been trained. But also, the thought that really still in my mind is how many people are still allowing team members the “bring your own AI” dynamic. If you are not in some tools that will protect your company’s confidential information, your customer data, that really is where you’re talking with legal about how can you at least bring some capabilities to your team that protect the company and your customers.

Drew: You need your own sandbox. I think the biggest thing is, I’m thinking about this very broadly, is every department, every individual just doesn’t know what they don’t know. And when you look at generative AI, you only know what you’ve heard about other people doing. But the difference between AI and any other technology is you can say, “I don’t know what I should be doing now. How do I start on this?” Or “What problems are people using generative AI to solve at companies like mine?” and you will get answers. Yeah, that’s not true – nothing has existed like that. So just a reminder to folks, when you don’t know what to do on anything, you can just say, “Hey, I’m starting on this. How should I go about it?” Ask for the outline, not the answer.

Lisa: Great advice, because it’s very subjective too. Like you say, you can hear about use cases, but someone else’s star use case may not be your best bet, and so you’re right. Of it, you always want to hear what other organizations are doing because, to your point, there’s no authority on Gen AI. This has come along so quickly, and there’s no accepted, quote-unquote, best practice. There are things quietly emerging, but there’s no right answer right now.

Drew: I love that. So speaking of that, one of the use cases is to have an engine that knows your brand and knows whether you’re using a writer-type thing or you just created your own GPT. The question is, will the AI engine be too positive or brutally honest? Could it ever just say, would this resonate with the audience? Ask it if it would resonate with an audience, and the response is, “Hell no.”

Lisa: Some of that is, you know, also teaching a lot of the marketers about the prompting skill of what you really want is not yes or no, but help me with the suggestions to make this resonate. And you’re right though, the brand guidelines and knowing you, that is some real power. So it’s also incumbent on us in identifying our best experts about what is right for our brand, whether it’s voice, tone, all the things in our brand guidelines, also how to get in there. And you’re right, ask these questions – you can get some brutal responses, but you really want this to be a lot more helpful.

Drew: I think this is where, I mean, I’m seeing it, maybe you’re seeing it too. While right now, this is sort of this distributed everybody’s using the raw material, part of it, and touching the GPT LLMs, more likely this next layer will be about these application layers where, I mean, and not a Jasper type thing, but close where it knows you have your own – it’ll be the Forrester GPT. It will have prompts for you to help it to sort of get to the outputs that you want. It feels like we shouldn’t be individually creating these things very long, right? It should be company-wide, where we have that in and again, in these sandboxes, and then we’re continually testing.

Lisa: It is. It’s sharing what other people have done. I also see the technology is only getting better. So in some of these tools, you’re right, we may – I heard another expert say, we may look back and laugh at how much we’ve done the text prompting already. If you’re looking in, let’s say the design world, there are already some tools where it’s more pull-down menus, or the generative match based on an image, or something else, where you could get a lot more control specific compared to the prompting that we’ve known so far.

Drew: Yes, okay, let’s see another question from the audience. Is there a good place to go start building an AI Literacy Center with training and resources?

Lisa: Yeah, I think of it in several ways, meaning, yes, some of that you may have some experts within your company who would talk about it, particularly if you’ve got some AI policies. Depending on sources, I look at this – I’ll give positive shout-outs, whether it’s organizations like Forrester or the Marketing AI Institute. I could go naming names, but there are some great sources. I’m glad to riff on more. But I think you can look at some external experts. Look across your company, though too, that there may be some people who surprise you in different functions, who could talk about what are some things they have thought about in the nature of their job, their department, and put together some of that to give team members perspective. I think, along with that, yeah, the AI literacy is talking about – really, you want your team to understand what AI is and can do. I do see some of these companies I’ve mentioned probably have that intro of AI for marketers type offering, thinking of Marketing AI Institute again. Then, if you are thinking of in your organization, it’s a great project if you’ve got some people who are really already deeply involved in this. I think for a lot of marketers, it’s really understanding where’s potential for your day-to-day, and having people understand again, partnering then what’s acceptable in your company environment and protecting your company. So some of that might be you have a legal or IT partner who could help.

Drew: For the Huddler community, we do have a list of folks that are doing this. Next week, we’re also interviewing Tawny Perry, who is doing sort of boot camp-like things, as is Noah Briar at his company, Ellyn. So we have a list for you. If you need that, just ping us, and folks are feeling really good about these – these are folks that did it in 2024 and now are doing as Lisa talked about, which is, it’s not a one and done. That’s the hard part. You can’t because, again, things keep changing so quickly, it’s impossible to keep up. But at least there are folks out there that are trying. Okay, so wow, we covered a lot of ground, and I feel like we could talk for another half hour, but we don’t have time, so let’s start to wind down a little bit. So I had a question in the notes: how can CMOs lead effectively without micromanaging AI adoption?

Lisa: That’s a great one. I remember our conversation on this is really as a CMO, you’re helping establish that clear vision and strategic priorities. Occasionally I meet CMOs who are just so enthusiastic themselves and seeing this potential. I see this as it’s super helpful that you articulate the why and what this can do for the organization. You might find, depending on the mix of team, you might find some people who are very worried. So it’s having some of the practical conversations about what does this mean career path for marketer or for your job. But it’s also you’re helping people. Again, we talked about prioritizing what are some of the outcomes you’re going after for use cases. It’s also helping the team in understanding where they can go for support. If you’re being a good exec sponsor, let’s say if maybe the AI Council, or you’re helping some of your team members who are involved in varying stages – maybe you got some pilot projects underway, if you’re helping make some introductions for them. That kind of support is super helpful, even as you’re excited and you’re using it yourself. I think it’s great to be a role model, but not tell people the how or specify these are the only use cases we’re going to work on.

Drew: Yes, it’s like just basic leadership again. It’s like, what do we want to do? You go figure it out. I mean, well, within guardrails. Okay, so set the vision and the priorities, the AI councils, and one thought I remember in the notes that – and I talked to a CMO who had a huge skeptic in their creative department, they put that individual in charge of the program, the council that individual subsequently became the champion. So it’s just interesting how that can work. It’s like the old play when you have two employees who aren’t getting along, have them sit next to each other.

Lisa: Yeah, it’s powerful too, as you said, to identify some unexpected or some really great AI champions. You could find a real mix in your team. And I think that kind of support in nominating or putting people forward, or helping them see it as part of their job, or really a lot of your high performers, this is a great career opportunity for them.

Drew: So I think personalization at scale has been a holy grail for marketers for a long time. I think as individual consumers, we all want to be treated as individual consumers. Is this the moment where, you know, within a matter of months or a year, where there are going to be marketers, besides Amazon, who are achieving personalization at scale?

Lisa: I do, I see it, and it would get away from some of these really dreadful emails that we get. I think of it as a lot more individual experience that you’d see whether again, is that event example? Are you able to offer some of your attendees better recommendations or responses? Are you able to do things again on the website, really rich area that you think about how you could do some real-time responses as you’re gauging and using some of these signals. What you’re able to do, I think of it even as you get into, let’s say you’ve got your customer advisory board, or you’ve got some really important events coming up to help and look at a different makeup of some of your customers together. Some of those are opportunities that you’re looking at again, back to, you know, we think of it as, yes, the Holy Grail, or the persona by persona level. But even as people, you do know if you’re able to take some things forward there with the data you have, while your team, I am excited talking to some marketers who really are trying to expand their vertical marketing, or one marketer’s talking about customized messages, they’re growing their partner ecosystem, so the different kinds of partners, how they’re able to go out to market together a bit better, faster.

Drew: Yeah, you know, I think about as you’re talking about personalization and record, you know, it’s not hard to imagine that I’m wearing my, you know, Google glasses, and I am at a trade show when I recognize, oh, there’s Lisa, and it remembers, oh, Lisa lives in Oakland, and, you know, the weather’s bad there right now. Hey, Lisa, great to see you again. You know, right, that opportunity just to have a personal interaction, because you know that it could, this could get scary, creepy. This could get amazingly personal and wonderful at the same time.

Lisa: Yes, that is the delicate balance that I think a lot of that it depends on. As you say, there’s a lot of human good judgment, good common sense about where, where is the line that makes people feel uncomfortable, versus I feel very welcomed, or I felt like, hey, you were thinking of me. I appreciate that.

Drew: All right, so we’re gonna have to do a whole separate show on Gen AI and its impact on search, because it’s just so huge. And you know, I mean, we talked about the Google Apocalypse last year, but we can’t get to that, but we can talk about before, as we wrap up, think about four CMOs, two do’s and one don’t for CMOs who are starting or scaling their AI journey.

Lisa: Yeah. So I think of rapid fire, kind of the, you know, we were talking about investing and building an AI literacy. I love the people in the chat I just saw were giving some suggestions. I would think of this as you know, if you are going to help your team learn effectively, yes to those intro courses, if you’re there, if you are moving forward a bit, even think of some role-specific training. I talked to some marketers, not just the actual role, like what you were doing your digital marketing team versus, you know, you could compare different parts of the marketing organization the nature of what they do. I also think of it as someone who is segmenting, let’s say AI champions, or people who are the more forward-leaning people in the organization having some sessions for them, versus, let’s say people managers or individual contributors.

You could bucket your teams in different ways than, let’s say, the usual of their role, the team they’re part of, or their geography. I also think of as engage your vendors and your agencies. Some of them probably have some rich experience. You could be pulling them in if they’re part of, let’s say, you know your all-hands or a team meeting. Or if there are ways to talk about, what have they been doing, get some ideas from them.

Drew: Cool, and a don’t?

Lisa: Yeah, I would say it’s still that thought about this being a standalone initiative. I would really communicate the bigger picture in AI is it’s a tough one, because it does seem like it is such a challenge, but I think that bigger picture about how this is going to change work, and what does this do for your company and in ways you want it to be good for your customers. Have people thinking along those lines, rather than just yes, efficiency, yes, productivity, but it’s really also the longer game is it’s going to be part of your everyday activities, so part of your workflow, it’s also understanding your current state. I talked to some marketers who are really challenged because they may have adopted there’s really great tools in one area, but they’ve said, once you get out of one tool, or once you get out of one particular area, and you start working across departments, people aren’t sure what to do when, and so that’s where I think it does bear some of that earlier conversation we had about, know your current state and some of the workflows you have experts who can probably tell you right off, these are things we should change. This would be a relief, or these are things that are going to get really sticky. So have them help you with that.

Drew: I think there’s a couple of really clear messages, which is this is going to change work. And if you think about that, that’s everything, I mean, that’s everything from hiring to leadership to communications to customer retention. We can talk about, probably at length again and a whole other show on just making a better customer experience, and how this enables that in a way that really hadn’t existed before, that there’s so many opportunities so you can’t get there without starting, yeah, and I think that was a big part of this. And the good news is you’re not behind, because everybody’s just been playing so far. There are a few folks that have really are pushing it, and chances are, half of what they’ve done, they realize, ah, that wasn’t such a good push, because they were such early adopters, right? So there, you know, you’ll be able to benefit from the learning curve, but I don’t think there’s any doubt. So anyway, I’m excited to see your keynote at your summit in Phoenix. I imagine you’re going to be on on the first or second. I was at the summit two years ago. How do you think this one will be different?

Lisa: Hey, thanks for asking. This year, we’ve really made a push. In addition to classics like keynotes and breakout sessions and the Executive Leadership Exchange for CMOs, we have more interactive opportunities. And what I mean is we have purposely built in more round tables and workshops, because we want attendees to feel like you’re not only growing your network while you’re at Summit. You should get some practical ideas that you could take back the following week. You’ve got something really actionable, and that’s, I’m a former client, that is one of the things that at a summit event, you really will get some frameworks or some practical thinking, and you’re going to talk to other people about, how did you do this? What did you learn, good or bad? Help us avoid some of those pitfalls, or help us get started.

Drew: Well, that’s awesome. I’m that much more excited. And Lisa, thank you so much for joining us. People can find you on LinkedIn.

Lisa: Yeah, thank you for having me.

Drew: If you’re a B2B CMO, and you want to hear more conversations like this one, find out if you qualify to join our community of sharing, caring, and daring CMOs at cmohuddles.com.

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!