The 4 Mindset Shifts CMOs Need for AI Transformation - with Liza Adams

Speaker A: Welcome to Growth Activated. I'm Mandy Walker, Your host with 15 years of experience leading marketing teams ranging from small startups to large service organizations. I've built high performing teams of all sizes and have seen firsthand how fast the landscape is evolving, making marketing leadership more complex than ever. Today, I help marketing leaders elevate their strategies, lead with confidence, and build careers they love. If you're ready to drive impact and unlock growth for yourself and your company, you're in the right place.

Speaker B: Let's get started.

Speaker A: If you've been adding AI tools, but the actual work hasn't changed, this conversation is for you. A few months ago, Lisa Adams pulled up a chart for me on a call that showed what a real human plus AI marketing team looks like.

Speaker B: I left so fired up that I

Speaker A: spent the next weekend in a cloud code hackathon. That episode, the weekend Hackathon wake up Call, became one of my most downloaded ever. This is the conversation behind it. Liza is a former cmo founder of Growth Path Partners, and one of the clearest voices on AI transformation in marketing. Today she works directly with CMOs scaling human plus AI teams, and she's built the frameworks they're actually using to do it. We get into the four mindset shifts every marketing leader needs, why productivity gains are just the floor of what AI can do, and the case study of one team that built 300 AI teammates and had to cut nearly all of them to make AI actually stick. Let's dive in.

Speaker B: Hi Liza. Welcome to the Growth Activated podcast. We're so excited to have you here today.

Speaker C: Hi Mandy. Thank you for having me. I've been, uh, looking forward to this.

Speaker B: Me too. It has been a long time coming because I believe it or not, I know we spoke for the first time probably three months ago and during that call that we were having, uh, to just sort of chat and me learn from you, I had my own little oh shit moment when you pulled up your, your, um, sort of all the automated workflows and team members within a marketing organization and it sent me down this path where I ended up spending. I was in Wales at the time that we spoke and I ended up doing like this weekend hackathon to really dive into cloud code and start to immerse myself. So you've been a huge inspiration to me. Yes, I did a podcast on it. It's one of my most popular episodes at this point and I know everyone's really exc. Excited to hear from you because I did mention you, uh, on that podcast as one of my sources. Of inspiration. So thank you for inspiring.

Speaker C: I'll have to listen to your podcast because I'm sure I'll learn something from what you did.

Speaker B: So I don't know about that, but, uh, I learned so much from your newsletters and it's just such a, um, so excited to pick your brain today. So, Liza, I'd love to start with when you think about AI in marketing and all the things that could be done, I would love for you to set the vision for us as CMOs. Maybe everyone's at, uh, different, very different stages of their own AI journey and it'd be great to just learn if people were to follow what you're going to teach us in terms of, um, organizational transformation. What is the end game? What is the real today, future state that can be created that you think CMOs should be, um, keeping in mind.

Speaker C: Yeah. So I love, um, Simon Sinek's Golden Circle. It's the why, how, what? Um, I think nowadays we get enamored by the tech and we focus so much on the how and we focus so much on the tools and the magic of AI. But I think we need to have some grounding principles, um, so that we can make better decisions as we move forward. Um, one of my key principles is people first AI forward. What that means to me is that we apply a people lens in every AI decision that we make as we use AI to push us towards work that wasn't possible before, not just faster work. When we are people first AI forward, that means that we're committed to upskilling and reskilling people. And when we upskill and reskill people, we give them a gift, right? It's a gift of being able to compete in whatever comes next, whether that's in a new role, in a different team or in a different company. So understanding that AI can have a lot of benefits to the business is one thing, but ensuring that people are secure in their careers moving forward, even if it goes beyond the company that they're in today. So that, that's first and foremost in my mind and then for CMOs, um, and you know, I was a former CMO and I lived this throughout my multi decade career. We won't say how many decades. Um, you know, uh, the tech is um, amazing, right? And it could be used for good, but it could also be used for bad. But I always anch it on the customer. We talk about, um, improving productivity and efficiency with AI doing more with less and those are all, um, good places to start. However, anchoring it on how Customer behaviors and their buyers journeys and uh, how they make decisions are changing is going to be super important. Right? Because when we have that kind of foundation, then we can figure out how we can better serve our customers. That has always been our North Star. Better serving our customers nowadays might mean using AI and in many instances it will mean that when we anchor there and then we figure out how we can better serve them moving forward as our teams become more hybrid. Meaning that they will no longer just be um, a bunch of humans, we will now be a combination of human and AI teammates. Then we have a true purpose and we are not deviating from our North Star. Those two things from my perspective, if we can anchor on those, it will be a lot easier to make decisions moving forward. When it comes to technology and um, change management.

Speaker B: With the first one that you were talking about with upskilling and reskilling, I am curious because I think there's this broader question. I have it for myself, but I. What's your perspective in terms of the burden on the company to be in charge of upskilling and reskilling around AI,

Speaker A: their internal employees, versus what burden should

Speaker B: be on the individual to learn, uh, maybe outside of work or to sharpen their skills? I'm curious because sometimes it feels like. I think, I'm sure you hear this all the time. It's like we have such a hard time making time to learn AI and to implement it in a lot of ways. And sometimes it feels like if you don't do it on the nights and weekends, it's just not going to happen. So I am curious to hear your perspective on that.

Speaker C: Yeah, Mandy. And um, I think it's an interesting choice of words. Um, burden, um, on the company and burden on the individual. And um, I'm not judging you by the way. I just found it interesting. Um, I actually believe that it's a, ah, responsibility. It's a fiduciary responsibility of the company to upskill and reskill people. Um, we hired the people to do a specific job when the market was something different. Now the market has changed and I think um, it is our responsibility as brands and as companies to help people evolve with the market. Right. And put them in a position to better serve that market and to ultimately compete. Um, and there's so much to be said about upskilling our own people and reskilling them versus hiring from the outside. Uh, and those are some key considerations that we need to think about. As brands and as companies. There are certain roles where you need the experts, right? Away. Right. And we're going to pay highly for that, um, because there aren't that many AI native experts out there. You know, the generative AI for the masses has only been around three plus years. So you know, for someone to say, I need somebody who knows generative AI and has done this for 10 plus years is kidding themselves. Right. Um, and there's a lot of value in our existing people who deeply understand the culture, um, the customers, how things work, what makes the company tick, uh, the soul of the business. Right. And those are really hard to replace. Um, uh, especially if you're simply expecting AI to do work faster. So I think it's truly a responsibility. But here's my fear. My fear is that we're all working in a pressure cooker, right? And upskilling people. Change management takes time. It's not easy. The hardest part of AI transformation is an AI. The hardest part is human change management. This is around shifting mindsets and behaviors, putting hands on keyboard, giving them space to learn, not just tacking it on on top of what they do on a daily basis. You know, I have CMOs reprioritizing the work, um, and you know, deeming certain days of the week or hours as, um, time to learn and use AI. I have a CMO that does, uh, thriving Thursdays and failing Fridays, where they get together and share what worked and what didn't work. Right. And she has reprioritize the work so that um, they are creating the space and she is aligning new workflows to strategic initiatives so that they have a better shot at succeeding. So those things are hard. My fear is that, you know, the pressure cooker is going to intensify and when we're under pressure, we can't be our best selves and we make rash decisions and we um, we get pressure from CEO and the board and so on. And um, I fear that we won't have the time, um, to give people, uh, the space to learn and the opportunity to upskill themselves.

Speaker B: Yeah, I love the term, I guess pressure cooker. It feels very, ah, real. What do you. Is it, where's the pressure coming from? I guess where is it? Where's it? Where do you feel like the pressure

Speaker A: is really closing in?

Speaker B: Is it to be AI forward and have deployed all of these agents and workflows and things like that? Or is it to have an AI strategy or something else entirely?

Speaker C: I think it's much bigger than that. Um, the technology is one thing. It's moving fast, you know, upending a lot of traditional Beliefs, um, on its head. But you know, we have economics, right? And we have uh, geopolitical challenges. We have, you know, all sorts of things where you know, when business models change and when um, the market shifts, you know, many companies I believe are starting to lose product market fit. Right? The market has shifted, but the products have not shifted and the go to market strategies have remained the same. And you know, when you lose product market fit, um, there's a lot to be, you know, untangled there, uh, because you could have the best AI, you can have the best, you know, strategies and best messaging and positioning, um, best campaigns. Those things could be awesome. Right? And I actually use this analogy quite a bit is you could use AI to uh, help you with personalization and do integrated campaigns and um, offer all sorts of content. But if you lose product market fit, um, it is like doing an all out campaign for snowblowers in Florida, right? It will never land because now the market is not viewing your product as something that can solve their problem today. So uh, I uh, think by and large that is contributing to it. And product market fit right now is happening. You know, we constantly have to pulse the market because it's shifting so fast that we have to consistently ensure that we're still, that the ICP is still what it needs to be. Right. So given all that, plus the pressures of for example, you know, a PE back company, um, you know, sustained, uh, profitability law, uh, rule of 40 or rule of 60, whatever it is now. And then there's public companies that are judged on a quarterly basis that's diametrically opposed types of metrics to change management that requires multiple months to happen. Um, you got to change the mindset and then the behavior happens and you have to do it consistently. It's hard to rationalize those two pressures.

Speaker B: Mhm. Mhm. Yeah, absolutely. And then customer behavior changing so much for sure, which I know you had mentioned as well. So it's a lot to keep a

Speaker A: hold of for sure.

Speaker B: Yeah, absolutely fascinating. Now, um, I'd love Liza to talk a little bit about one of the charts that you'd shared with me on our original call. Just sort of transferring into um, the AI organizational team, organizational, I guess, transformation. One of the things that was really interesting to me is you talked about four dimensions of growth within AI and you, you had this really great chart that kind of broke out, um, was, was a matrix, if you will, of breaking out the different areas to leverage AI. Could you walk us through that? Because I think when I, that really helped me I'm someone who like, really responds well to frameworks and um, I think it helps just sort of self assess and, or assess our teams in terms of like the current state of their AI leverage and maybe comfort, um, and usage.

Speaker C: Yeah, many, my frameworks are not best practices. Right. Um, I always say best practices come over time. Um, and I don't believe that there are many AI best practices yet because it's evolving so fast and we're moving with it, we're learning with it. Um, but my frameworks are coming from a place of, um, uh, from a practitioner's perspective and from a place of, um, seeing patterns, pattern recognition, working with a number of marketing teams. So what I'm observing right now is, um, the teams will build based on what they perceive AI can do. And that's a limitation. Right. And you know, there are four mindset shifts that need to happen in my mind before the team truly embraces what AI is capable of doing. Um, the first one is around shifting the mindset from uh, primarily using AI as a question and answer machine or a fancy search engine to a thought partner or a sparring partner. Right. And the reason why I say it's important to um, shift the mindset before I go into that thought partner piece is in the early days of the smartphone, we all thought that this thing is just going to be a fancy way to make phone calls, right? That, um, it's a flat screen, it's a touchscreen, and then we realize that it's a wallet, it's a gps, it's a music box, um, it's a camera. And if you want it to be, it could be a baby monitor. Right. And then we change the way we work and live around it. And in fact, today I use it the least for making phone calls. I use it for all those other things. And same thing with AI, if our teams primarily use it as a question and answer machine in a fancy search engine, then that is all they will ever build with it. And there's a huge gap between, you know, question and answer machine, where ChatGPT or in Claude it says ask me anything in the conversation box. And one where it's fully integrated workflows with human and AI teammates working together, reimagining the work. That's a Grand Canyon between ask me anything and fully automated systems. Right. So the first mindset shift is really thinking about AI as a thought partner and as a sparring partner. Right. This is about being comfortable in being wrong and asking AI to challenge our assumptions and evaluating our, our content. And giving us other opinions and. And, um, you know, there's something liberating about, you know, uh, being okay with being wrong and being so intensely curious on the reasons why. If we can treat AI as a sparring partner, I think we will have much more nuanced and much more richer thinking, um, to back up our strategies and our content. That's one thing. The next thing is around primarily using AI to do things faster, improving productivity and efficiency and doing more with less. I actually believe that that should only be the floor of what we can do with AI. We hear many CEOs say, hey, we need to improve productivity. And I think it's great, but I think it needs to go way beyond that. Because if we simply train AI to do our existing work faster, you can almost project how we can automate the human out. We need to actually push AI to help us, uh, improve the quality of the work and then ultimately help us reimagine the work so that we're actually doing new work that wasn't possible before that actually grows the business. So, you know, we're at that Henry Ford moment where you can't reimagine the future by simply automating the past, right? And, you know, I can't see a situation where we're being so productive, but we're not growing the business and we still require more humans. That's literally impossible. Right? But if we are now doing new work that is growing the business, we're reimagining what this thing looks like, then humans are essential, right? And then we can improve profitability and so on. So that's the second mindset shift. The third mindset shift is around, um, primarily using AI as a tool, like a chatbot, like many use today, right? To building and guiding AI teammates, meaning that we actually train AIs to do specific work and they are trained on our, um, unique expertise and our unique company knowledge, and they are part of our jobs, right? And then ultimately being able to orchestrate multiple AI teammates into a workflow. Um, not just in productivity workflows, but also in reimagined workflows, like I mentioned previously. That is a big shift from m AI as a tool to teammate, and then ultimately, um, orchestrating AI workflows. Then finally, the last mindset shift is around, um, going from hierarchical and siloed organizations to, uh, organizations that, um, there's no daylight between functions, they begin to converge. Um, it's now about outcomes and less about functions. What I mean by that is I always, um, reference the Harvard study Um, with P and G professionals where they gave cross functional teams AI. And the result of the study was that the people in these groups began to care less about the boundaries of their job because AI doesn't care about our, uh, roles, our titles or our functions. It only cares about the outcomes. So in the world of marketing and go to market, AI doesn't care about marketing, sales and cs. It only cares about the overall outcome and the customer experience, which is great because our customers don't care about our silos. They only care about the experience. Right. So I actually have a lot of hope for customers in this case that, um, seamless customer experience will now be table stakes. And those that are not able to provide that will be in a difficult position to compete moving forward. Anyway, uh, those are my principles of shifting, uh, mindsets. And once people grok those four principles or mindset shifts that it gets a lot easier, um, in helping people figure out how we can best use AI going forward.

Speaker B: Yeah, no, I. Super, super. Um, interesting. And one of the things that I've been challenging myself a lot on a lot lately is how can I go from, how can I guess when you take your strengths and you dump them in, like, I don't want to necessarily go from an A to an A plus using AI. I want to go from like a D to a B or to an A. Right. And like have that jump. And for me personally, product marketing has always been a gap area of mine because I'm much more of the demand gen side and the operations, that's sort of where I came up in. And AI has been so powerful for me to like fill in those gaps and still have my business and customer hat on. But now the capabilities, my capabilities are so much stronger because I have this tool behind me. Um, so it's been really challenging myself and I saw myself in a lot of what you were describing in those four mindsets of how can we, um, really reimagine, uh, I guess the work that's being done and how to do it. And I love your point about the outcome over the task too. Um, and I noticed that too, like when you, I don't know about you, but I know myself. Like when you get started on something you're driving to an outcome, it also then can send me into a little bit of a spiral because it's like, oh, then I need to do this and then I need to do this and then I need to do this and all of a sudden you've now just given yourself like 20 things to do.

Speaker C: Yeah, absolutely. And, ah, you know, um, many people say, hey, AI has allowed me to save time and I do a lot, a lot of my work faster. I actually am working more. Yes. Uh, but it's not working more in areas that I don't like. I enjoy the work that I'm doing because it's the stuff that, you know, it's the strategy, it's the thinking, it's. It's finding out new things and it's expanding my, my, my knowledge. It's the growth mindset.

Speaker B: Right.

Speaker C: Versus the, the tactical things. So, you know, I really just love the fact that, you know, we continue to grow used responsibly. I think our curiosity will allow us to continue to grow as a human being. Right. We learn about other people's perspectives because as humans we generally have, you know, we're beholden to our truths, right? We have our own assumptions and we're belly button gazing and, you know, it's hard to get different perspectives unless you talk with lots of people. And then now I still believe that we need to have different perspectives and we need to take those other perspectives into consideration. But it gets a lot easier because we can ask AI for example, how might someone in different phases of their buyer's journey perceive my messaging? Uh, or how might this newsletter be perceived by someone who is a skeptic versus someone who is AI Forward? Then you can, it's essentially challenging your beliefs, right? And then you can determine, um, you know, how you zig and zag or course. Correct. And, and maybe have a more nuance or richer point of view as a result of understanding other, other people's positions.

Speaker B: So, yeah, I actually was just thinking this morning, uh, man, I should create like my own buyer, um, agen that vets all of the work that's being done and really, like, challenges me from, from my actual. From the different buyer Personas. Because I work in a. I work in an industry that has a lot of different buying Personas. And so sometimes I find like the, My teams will get locked in on, on a few of those, but we're not thinking about all of the different angles and how all those different buyers will perceive what's, you know, what's being shared out. So really interesting.

Speaker C: That's actually an exceptional use case for AI Mandy. Like simulations, right? Um, buyer simulations. You have, uh, financial manager Persona, IT manager Persona. You can even have like your buying committee, your decision maker, your influencer, ratifier, user champion. Right? And then you can have your digital twin. So I have a digital twin. I have A couple of them. One in ChatGPT and then one in Claude. It's trained on my, um, my frameworks, my newsletters, my approaches, case studies, best practices, um, beliefs, purpose, uh, LinkedIn profile. I did deep research on myself and it, you know, AI output like a 28 page research report on Lisa Adams and I'm like, oh my God. That became knowledge for the digital twin. Right. And the way I use my digital twin is not necessarily to do my work, but I, you know, in the, on days where I can't be my best self, the digital twin challenges me and I say, hey, what did I miss? Right. Uh, because as humans, you know, we can't perform at the highest levels every single day. But because it's, it has so much knowledge about me and when I'm, you know, testing my ideas, I could say, you know, based on my best practices, did I miss anything here? So I just think we can really elevate ourselves, um, and AI can help us overcome our weaknesses and then likewise we can overcome AI's weaknesses. Right. AI doesn't have a moral compass. It also doesn't understand context in our environment. That's why I have defeated a lot of things. So when you put humans and AIs together and use them responsibly, uh, I think we can achieve so much more.

Speaker B: Totally agree, Liza. I'd love to, ah, transition a little bit into the transformation journey, the journey to transformation. Because I have to say, while I was so inspired back in, I think it was January or February and I did a cloud code hackathon, um, I have not opened cloud code back up since now. I've been in cowork and I've been doing other tools and things and I've definitely leveraged AI a lot. But um, I also see this in other peers and teams and I'm hearing that this is happening. Like we get excited, we go all in. Maybe it's a day long workshop or whatever it is, or we spend a weekend and then it's hard to maintain. And I see this in teams too, right? Where we, or even in teams where they're kind of building separately, they're building their own thing and we're not kind of bringing everyone together. So when you think about how a CMO can kind of bring their organization through real meaningful change with AI, how, how do you see that in terms of like the different phases and how we can really be shepherding people through.

Speaker C: Yeah, um, and you know, we talked about change management and it's a journey. Right. And you know, the the very first part of this is really that mindset shift, you know, and grounding it on customer behaviors and the changes in the buying patterns and, and showing them what's possible. Right. Like, once you shift the mindset, we have to actually show people what's possible, you know? Yeah. When I talked about those four mindset shifts, I'm like, okay, what does that mean? Like, what are the applied AI use cases? Workflows that, that, you know, give me some examples so I can, you know, wrap my head around it. Um, and then you show them what a human plus AI organization might look like. Right. And, and how, you know, we have complementary superpowers. So there's, there's a lot in that foundational phase of it. Right. And then ultimately, once they see what's possible, humans, you know, we're not stupid. You know, we, we just need to see the, the body does what the mind believes. Right. So now you believe that this thing can be a teammate. This thing could be a sparring partner, and it could actually, they could be orchestrated. Then now we put hands on keyboards. So we do like, do hands on keyboard workshops or give them the time to actually test, uh, and experiment with AI. I do these workshops where, let's just say there's 20 people in there. We come in as 20 humans. We come out as 40 members. Because now each human has created an AI teammate. So now we're 40 members strong. And not all of those teammates are, are good, you know, especially the first ones that you built. My first one was crap, but it's okay. It starts to build the confidence that we can do this. Right?

Speaker B: Yeah.

Speaker C: So, uh, but that's just the starting point. Like shift the mindsets. You show what's possible by function and marketing. Because you can't just like, show marketing ops use case to a product marketer, and you can't show a field marketing use case to a digital marketer. Like, you kind of need to show them by function. They put hands on keyboard and then now, um, hard work happens. Right. Because it has to stick. Now people are really excited. They got the confidence to build. They have one or two teammates. The hard work happens in the consistency in the, um, uh, support, uh, of the leadership team, uh, and showing, highlighting trailblazers. I lean in on trailblazers. There's got to be like a handful of people in your organization who are leaning in hard. Right. And they're intensely curious and they're already reimagining the work. And these people hold on to them tight and elevate them. And, um, show others through the trailblazers what is possible. Right? And those trailblazers will begin to mentor others and they will help drive momentum. So that's one of the things that needs to happen during that change management process. Again, as I mentioned previously, reprioritize the work and give people space to learn, safe space to learn. Right? It's okay to fail because even in failure we learn a lot of things and we need to understand the limitations and the possibilities with AI. And that bar continues to shift every single day. Like every single day, I'm like, oh my gosh, I didn't realize I could do that. Oh, no, I can't do that. But what it can't do today, it can do tomorrow. So we just keep going, right? And that's why failure is okay, because that failure today is a success tomorrow. Right? So do those things. Um, I have a number of teams. They have dedicated slack channels or teams channels where they share what works and what doesn't work. Right. Um, they have, uh, show and tell, um, days. The CMO has, um, like I said, reprioritized the work and began to operationalize. Right. Because this whole thing around, you know what I'm talking about here is like encouraging people to just build. There's this notion of democratized building, centralized enablement. Right at the beginning you really want everybody building. At least that's what my pattern recognition is now telling me. Because the people who are closest to the work are the ones who can reimagine the best because they understand the processes they have lived through the environment. They know what's broken, they know what's possible that everybody can reimagine. But those closest to the work have a higher probability of being able to do that. Right. Um, not to say that tops down doesn't work, but give the people the opportunity to actually, um, uh, reimagine their own work. Once you get everybody building and people get comfortable, you have a ton of teammates now. Now in the change management process, the problem becomes different. It's now around AI sprawl, because everybody's built and you don't know what's up and you don't know what, which ones are good and which ones are bad. And this comes to the point where, You know, you just have a bunch of digital twins. Nothing's, you know, orchestrated in a workflow. This is when, like a hackathon, uh, I call it a hackathon, but it's really more like a, you know, it's an extended period of time where people have maybe In a matter of two, a couple of months, people build and then there's like a three or four day event where everybody shares what they build, right? Or you know, they, they, they share their best of the best. And then in that hackathon people see what everybody else has built and, and now the company is able to rationalize, use this hackathon to rationalize. I have a, um, you know, a marketing team that built over 300 AI teammates and workflows. They did a hackathon and then now it's called down to like 57. Because to your point, not all of these teammates were good, right? Some of them were duplicates, some of them were just digital twins, some of them weren't integrated into workflows. So the 57 were the best of the best that were now being uh, integrated into um, uh, daily workflows. And then people now understand which ones they need to use, right? And how they need to um, assess those teammates and ultimately track the performance of those workflows. So that hackathon is the beginning of like the scaling and the sticking part, right? And in conjunction with that there needs to be like a governance team that actually works with legal and IT and finance. Because you know, once we begin connecting AI teammates to systems like HR systems or CRMs or marketing, um, automation platforms, all bets are off on the building, right? Because we can't give every single marketer read and write access into Salesforce or HubSpot. That is now something that needs to be governed and um, enabled by a team. Um, and in some teams it could be marketing ops, it could be rev ops, it could be a cross functional team. But this team M needs to have a little bit more technical abilities to build those connectors and then to ultimately work with the right departments to ensure security, to ensure compliance and also ensure that we're managing costs. Because every time you hit Those connectors, those APIs, this is no longer a $30 a month, all um, you can eat buffet. We're now based on the tokens, um, the economics of this comes into play and I've actually had one team say that in certain use cases they've determined that buying a specialized SaaS tool is more cost effective than building it using a foundational model. So that's a consideration, right? Like our tech stacks. Now to really be thought about, um, not just cost but also, hey, do we have the people to maintain this? Are we going to be able to keep up? Is there a vendor lock in and all sorts of things. So anyway, that whole scaling thing is A whole different animal, um, than the building and experimentation and giving people confidence, um, to build.

Speaker B: Wow. Wow. Well, I have picked up so many ideas to sort of bring to my own teams. I love it. Um, Liza, I'm curious, do you find that CMOs are struggling? Are there CMOs out there that are struggling that you've encountered? Um, because there's too much governance in place and if anything, like, their IT and security teams are maybe overprotective and they're not actually able to build and test or is that really not something that you're seeing much of today?

Speaker C: You know, I have empathy on both sides, right? Like, I'm so empathetic to the CMO who is trying to inspire what's possible, um, change the way marketing is perceived, um, truly changing the way we do work. Because I've been in that seat, right? Like, you understand what's, you know, that we can unlock so many things and, and we can serve the customers better when we can do these amazing things with AI. Um, but at the same time, I have empathy on the governance side as well, the legal, the IT and the finance. Right. Side. Because once, you know, these AIs are no longer just chatbots. You know, it's not just ask a question and get an answer. And it's not just. They're not no longer just reasoners where they can solve problems. Right. They're now agents. Agents do things on our behalf. They can now navigate our files, they can use our browsers, they can use tools. They can, you know, output, um, a document and put it on a drive. They can send emails on our behalf. And, you know, that requires a lot of trust to let an AI do that. Right. And there are certain things, you know, um, Bryce Shalom, who was the former VP of Innovation at Moderna and is now the head of enterprise adoption at OpenAI, has this framework, which I love because it's not just about the impact, um, of AI to the business, but it's the risk of AI if something goes wrong. The risk is like two dimensions. And the dimension is, uh, one dimension is who is it affecting the individual all the way to the company. Right. And then the other dimension is the level of impact of that risk. Is it just, you know, um, mildly annoying to catastrophic, Right?

Speaker B: Yeah.

Speaker C: And this is something that the company needs to think about. If it's just like, hey, if it fails, it just affects this individual and it's mildly annoying, fine. Okay, no problem. But if we now start building workflows and AI teammates orchestrated together, that is company wide and could potentially be catastrophic because it's a whole email that's sent to all of our customers with the wrong messaging, in the wrong position, whatever it might be. Right.

Speaker B: Yeah.

Speaker C: That requires a lot more governance, um, from, you know, from a cross functional team. So I think this whole notion of, you know, really segmenting not just what's great for the business, but impact to the business if it goes wrong is something that we still need to catch up in understanding. Right. So you know, uh, it's a really, really hard line to walk. And I think if we can have a think big, start small, move fast approach where we begin to say from the government side, okay, I'll give you a little bit of this. Right. Let's try this and then begin to push where that trust factor, uh, we're more okay with more things than awesome. But I worry about going so big so fast and not realizing all of the potential risks to the business. Our risk tolerance is different depending on our situation and size of the company, public versus private and all sorts of things. Right. And, and what kind of business we're in. Some smaller companies, you know, many of them have nothing to lose, everything to gain. So go for it, they're going for it. Right. And especially if, um, you know, there's limited resources and limited budget, they have no other recourse but to reimagine work and do things very differently. But if you're in a larger company, uh, there's lots of processes, you're protecting a lot of customer data. That's not an easy transition to make because we need to really think about the risks, uh, associated with it. Does that make sense?

Speaker B: Absolutely. Actually, it reminds me of one of my favorite operational books I read. It's actually for IT operations. Operations, but incredibly applicable across the business. It's called the Phoenix Project. I don't know if you've ever heard of it, but they talk about this concept, very similar concept of um, like what is the risk of the work being done and if it's low risk, it was really um, at the time it was sort of translated to don't be a micromanager leader. Right. Like get out of your team's way. Especially for low risk things. Um, but the higher the risk, make sure you put in the right approvals and you know, different peer reviews and um, so it actually, I remember I saw that graphic in your newsletter and it totally reminded me of, oh, this was an exercise. It's sort of a great evergreen exercise to ask ourselves as leaders to encourage your team to take more Risks within marketing, where they can and where it's, you know, low impact to the organization. Um, so it's, It's, It's. It's great. I really enjoy it.

Speaker C: I think this, this time in AI is. Is pushing us to really think about situations in a. In a more nuanced way. Right. Like, I came from product marketing, so it kind of comes naturally for me to do segmentation. Right. Like, there's no black or white answers. Um, right or wrong. Right. It's always, like, segmented. And depending on the situation, the answer, um, the right answer for that segment, uh, will come out. So anyway, I think it's going to be more nuanced, even more so moving forward.

Speaker B: Yeah, absolutely. Well, Liza, I could talk to you all day. I've so enjoyed this conversation. I know we're wrapping up here. I'd love to hear, um, maybe just some final words of advice for CMOs out there. What do you wish more of us were thinking about? Ah. Or what advice would you leave us with?

Speaker C: Yeah, I think, um, really the people first, AI forward, um, mindset or principle is something that I hold close to my heart. Right. Uh, regardless of everything else that's happening, as leaders, we will always remember the people who we helped and where, you know, and how well they succeeded in whatever comes next. Right. And, you know, we will rarely remember the product launches that went well or, you know, the. The big sales kickoffs, but we will remember all the people that we have helped along the way. And I think it's such an opportunity for us as leaders to truly make an impact now because we. Like, I've been in this role, you know, in marketing and go to market for. For a number of decades, and it's those moments where I know I have helped somebody in their career that really stands out for me. Right. And there is no other moment that's bigger than now that gives us an opportunity to do that. So I'm like, take charge. You know, like, give them the gift of knowledge. Give them the gift through upskilling and reskilling, and let the cards fall as they may. Right. Like, and not all of them will. Will. Will come along. Right. You know, uh, I believe in the law of thirds, a third will, will lead, a third will follow, and then a third will find their own way. But you, at least as a leader, you have done your job to at least give them the right mindset and the right, uh, skills for them to make their own decisions. So that's my parting guidance, I guess,

Speaker B: unsolicited by many no, no, it's a really great reminder. I think, uh, in a time where we probably wish that the people on our team were more AI forward or farther along, I think it's a really good reminder just to stay close to the people, um, that you have. And I love the law of thirds. That's really interesting, too. So awesome. Well, thank you so much, Lisa. Um, obviously, people can find you on LinkedIn. Where else can they learn from you? You are so generous with what you share and all of the knowledge that you make public for free. So where can people consume all of this great knowledge from you?

Speaker C: Yeah, I'm an open book. Um, because this isn't a job for me. This is my passion to elevate the strategic value of marketing, use business as a force for good, and ensure diverse voices at every table. So you can find me on LinkedIn. Follow me there. Um, you could subscribe to the newsletter, uh, so it comes out bi weekly, and they're pretty dense. You know, it takes a lot of effort to do it, but I enjoy doing it because I learn as I write those. And then lastly, my website, which is,

Speaker B: uh, growthpath.net awesome, I have to say, too, uh, really cool that you. I saw that you actually use Notebook LM to put video recordings or, uh, activate your content through video and through podcasts, which is really fun. I was checking one of those out today, which is a great idea.

Speaker C: And I use those to, um, cater to different learning styles and time constraints. Right. So not everybody's a reader. I'm not a reader. I'm actually an auditory learner. So I love listening to podcasts, and some people are video, are more visual people. So NotebookLM allows me to cater, uh, to those different learning styles.

Speaker B: That's really cool.

Speaker C: Awesome.

Speaker B: Uh, well, thank you so much, Liza. It was such a pleasure having you.

Speaker C: Thank you, Mandy. You have a great day.

Speaker A: Thanks so much for tuning into this episode of Growth Activated. I hope this conversation sparked new ideas, challenged your thinking, and gave you practical tools to help elevate your impact as a marketing leader. If it did, I would love for you to pass it along to a friend or a colleague in B2B marketing. The more we grow together, the more we raise the bar for what marketing leadership can look like. And as always, in the meantime, keep activating growth for yourself and your company. See you next time.