Name: AI 101: AI first-step implementation for CMOs
Uploaded: 2025-09-02T17:16:51.212Z
Duration: 50 min 5 s
Description: AI 101: AI first-step implementation for CMOs

Transcript for "AI 101: AI first-step implementation for CMOs": Hello, everyone, and welcome to AI Marketing School. My name is Alexander Bleeker. I'm head of operations here at the AI Marketing Alliance, and I am super excited to have you all here. For those of you who don't know what the AI Marketing Alliance is, it is a network of CMOs, VPs, and senior marketing leaders focused on educating on AI from the top down. We have an incredible afternoon of content for you, uh, and I promise I will not keep you long. Um, but before we dive in, I just have a couple housekeeping notes. So first, a huge thank you to our partners. Um, we have quite a bit. We got Zapier, HeyGen, Jasper, 6sense, UserGems, Clay, Snapbar, and, um, especially Goldcast, who is our platinum sponsor for today. Thanks to them, we are trying something new. Um, we're hosting an event on an embedded format. So instead of the full user, like, full browser experience, um, that we've used in the past, This is a fresh way to bring you both content and resources together in one place. So we're really excited to have you here to experience it. We also have a Snapbar photo booth. So you can see just above, it says take your school photo. Um, so you can actually go and take your AI Marketing School yearbook photo, and you can keep it as it is or you can also let AI rewind the clock and make you look like uh, you were back at school again. Uh, and also just to note, uh, we will be giving away a grand prize, and, um, that is part of it. So definitely check it out, uh, if you want a chance at winning. I'm also excited to share that we are launching the AI Marketing Alliance community next month. This is gonna be a Slack based space for members to connect, share, and learn together. If you'd like to be a part of it, you can apply directly below on this page, or you can reach out at hello@aimarketingalliance.com. So here's what to expect today. We'll kick things off with our first session on how CMOs are driving AI adoption, then we will break into three concurrent tracks, event, content, and marketing leadership. Later, we're gonna regroup for an Goldcast session led by Goldcast, and then we're gonna wrap up with an expert panel on AI governance and councils. Now I'm just gonna share some slides because we do have some prizes to give out. So we're gonna have prizes for each of the individual sessions, which they will talk about once they start. And you can see here how to win, and then we'll also have a grand prize, um, and you can also, uh, win with, um, those details there. But you don't need to take notes now. Um, we will be sharing that shortly. A quick navigation tip. Um, so after this session, you are gonna be automatically placed into one of the breakout rooms, uh, for the concurrent sessions. If you wanna go to a different one, first of all, it is gonna be on demand so you can watch them later, uh, if you wanna watch more than one. But if you wanna see it live, uh, just head to the agenda and you can click on whichever one you wanna watch. And then don't forget to check out our partner booth to learn out more about them. Uh, you can comment or ask a question in there and they should get back to you, uh, within the day or two. Lastly, after each session, uh, please take a minute to fill out the short survey. Your feedback is super valuable, and it helps us curate content and the experience moving forward. So that's it for me. Let's dive in. Thanks for being here again, and let's get started with our first session hosted by Goldcast's very own, Kelly Chang. She is joined by Nicole Leffert, a marketing leader and one of the most recognized experts in applying generative AI to real world marketing. She's trained teams from start ups to Fortune 50 companies on how to integrate AI into workflows and drive better results. And alongside her, we have Ashley Gross, an AI teacher, speaker, and consultant who created the AI impact alignment framework. She's helped enterprises implement AI strategies that directly accelerate revenue, streamline operations, and transform decision making. So with that, let's bring up our awesome speakers, and we'll see you in a bit. Thanks for the intro, Alex. I'm so excited to be here. Uh, my name is Kelly Chang. I'm the CMO here at Goldcast. I'm so excited to be sharing the stage here with Nicole and Ashley. Um, I've met both Nicole and Ashley maybe two two ish two and a half months ago and, you know, had some really great conversations about, you know, AI transformation on marketing teams. And in this one zero one session, uh, we're gonna be really talking about, um, you know, how how, you know, AI how we're all adopting and learning from AI. The the best CMOs are defining direction. They're enabling teams, um, but they're they're starting small but smart. Um, so in this session, we're gonna see how, uh, Nicole and Ashley are enabling, uh, marketing leaders to lay the groundwork for adoption, uh, because you can buy AI tools, but if unless there's an actual workflow or use case for adoption, um, those tools are just being shelved. Um, so I'm actually gonna kick off this session with some rapid fire questions. Nicole and Ashley, are you ready? I'm ready. Okay. Awesome. Um, and if any of you in the chat also would like to join in in answering some of these questions, feel free to. Um, so I'll start with Ashley and then, you know, Nicole, you can also answer. Alright. What is one AI tool you'd keep if you had to throw the rest away? It's hard, but I would say Perplexity Pro for the competitive intelligence. Okay. Interesting. I haven't heard that one before. Um, Nicole, what about you? Um, I'm gonna be cliche, and I'm gonna say Chad GPT, and for me, it'll be my pro account. Alright. Um, okay. Next question. I'm gonna start with Nicole, and then Ashley can go after. Uh, what's the most overrated AI trend right now? I think it's thinking you have to have a different tool for every single thing you do versus, like, really understanding inside out how to use one of the core tools to their fullest capacity and only adding tools for something that it's not capable of. And, Ashley? It's a hard one to follow-up on, but I would say attribution modeling AI. So just this idea that software can figure out every single marketing activity that's actually making someone buy from you. Every single vendor, I feel like, is selling the dream of perfect attribution, attribution, and it doesn't work instead of using it for influence prediction. So Got it. Um, okay. Next one. I'll start with Ashley, and then we'll go with Nicole. What's the last AI experiment that you tried that failed? I built an AI system to predict which content topics would trend in our industry thirty days out, and it did not get the topic correct. But I learned a lot from that experience and that experiment, I should say, because it showed me what people actually care about specifically b to b. And it's really just budget cycles and fiscal calendars. So I was able to map content out to see if they're reporting schedules, and it was a happy coincidence. Awesome. And what about you, Nicole? So mine has nothing to do with marketing, but I literally did it yesterday. Uh, my dad has cat furniture that's really cool that my cat is obsessed with, and I wanted to try to figure out use AI to figure out, like, where I could buy the same thing for her for me. And, um, it told me that the Amish probably made it. So I think it kind of failed. It was definitely not. It was, like, company based. Meaning. Yeah. Yeah. I was like, yeah. This is not working. We are not identifying where this came from. Awesome. Um, so that wraps up our rapid fire questions. Um, I always love those just to see what if if we have hot takes or different points of view there, which is always interesting. Um, now we're gonna dive into the meat of everything. Um, so we're gonna talk about prioritization, onboarding strategies, and then workflow and design, and also team structure, and, you know, getting buy in in in different, um, cultures. Um, so kicking off with prioritization. Um, I'm I'm gonna start with Ashley and then, you know, uh, we'll have Nicole you build on it. Um, if a CMO comes to you tomorrow and and they say, you know, we wanna start using AI, uh, which is something that I actually did to you about two and a half months ago, Uh, where where do we begin? What is the first decision framework that you walk them through, um, you know, by helping them pick their starting point? I'm curious to hear if you have any, like, real life examples or stories that you can share with us. Always. But I try to start with just an easy question that everyone can answer, and I always ask what manual task is eating ten plus hours of your team's week. Usually, I get content creation, competitive research, lead scoring. And so from there, I kind of look at, okay, if you're saying that lead scoring is one of the items that's eating up your team's time, do you actually have clean data for that process? If you don't, let's just leave that use case as it is and then move on to the other two that you named. And then from there, I kinda like to take them through this workflow mind map of, can you measure success in ninety days? Um, can you pinpoint who on your team is excited versus who's scared about using AI to solve this use case that you're excited about? And then we come up with a decision tree together where we pick one high manual effort task that is eating up their team's time. They know it's eating up their team's time. They hate doing it. Um, we add on what we're going to need. So after we pick a process, what do we need to actually track it, measure it, feel good about it, and report back on it? And then we start building out the use cases that all level up to solving that large problem. Have you seen a trend in terms of what are the most common starting points that you've worked across across with your clients? Yeah. CRMs, they suck. I mean, it gets to a point where you have so much data in them that it's like you're gonna have to halt production for weeks on end to actually get it cleaned up. So that usually ends up being a big point. But where I usually hear it the most is at the executive level. It usually is to the point where marketing saying, we're bringing all these leads and sales is like, well, they're not great. And the root of that is actually just a dirty CRM, and both parties are right, but just being able to pinpoint what that problem is and how they can solve it faster using AI tools to get what they both want, that's something I've seen come up pretty often. Got it. And, Nicole, what about you? Um, you know, if if a CMO comes to you and says we we wanna start using AI, how do you typically approach that that statement? So I always start with what are we even allowed to do because I've worked with a lot of teams. And a lot of times, the CMO comes in with, like, really, really big ambitions that get squashed very quickly when we find out that their AI policy is not going to allow them to do the type of things that they want to do or use the type of tools that they want to use. So I always start with, let's find out what we have approval on. Like, where is your company, your you know, whether it's your security, your IT, whoever those decision makers in your company that are maybe beyond the marketing's team are. What are they and are they not currently okay with for your company to be doing. Usually, that starts with the tool. Right? So, like, there's a lot of things that companies might wanna be doing and cool tools they wanna be using, but at the end of the day, like, the absolute only thing that they are gonna be allowed to use is either a Microsoft Copilot or Google Gemini or Chad GPT or one thing that has been approved. And so a lot of times, we just have to make sure that what we're building out and starting with is from the place of what they're allowed to use. From there, it's also, do you already have access to any tools? Because why start loading in things to pay for that your company like, before you already look at what your company is paying for? So the biggest one I see that companies don't even realize they already have is Google Gemini because if they are on Google Suite, they probably have Google Gemini. And so from there, I'll look at, like, okay. What can we do with what you already have to start taking these baby steps while we start working on a longer term plan as far as everything else? And then once we know what do you have access to, what are you allowed to use and to do with it, then let's look at your goals, what your biggest pain points on your team are, and where we can move the needle the furthest. Because for some companies, their goals are efficiency, and for other companies, their goals are quality increases. And where you go are gonna, like and with this are gonna be very, very different depending on what the aspiration. Some, it's just strictly revenue. You know? Like, everybody has just very different goals. You gotta really understand what are we trying to do, how are we allowed to do it, and what steps can we take. And then a lot of times, you start having to go a parallel path with the goals and getting other things approved while you work on the baby steps with what you are allowed to do. Yeah. Nicole, you make such a great point about, you know, what you're authorized and allowed to do. And and, you know, for the audience here, stay tuned for our last session of the day because we're gonna talk about AI governance and compliance, um, for, you know, for all, you know, companies that are exploring AI tools and what they should consider because security is a big factor to consider here. I mean, Ashley, you mentioned, um, you know, CRM. Um, that's a lot of customer data and, you know, exposing that data sometimes may not be authorized. And so I know that HubSpot recently released their connector to, you know, um, GPT and with Claude. Um, but even at Goldcast, you know, we're not authorized to use that because we're SOC two compliant. So making sure that we're um, looking at all of the criteria for making us, you know, secure before actually being so trigger happy with some of these these cool two tools. Um, so thank you for sharing that, um, and kind of building on top of that, Nicole, I'll I'll start with you. Um, what is your litmus test for whether or not an AI tool is worth keeping in the stack versus cutting it before it becomes a distraction? Because I think, uh, just speaking for myself and some of the other, you know, marketing leaders out there, we're in this, like, interesting, like, trial phase. There's so many, you know it's it's almost like walking into a candy shop. There's so many different cool tools popping up here and there, different use cases. And it can be overwhelming, can be paralyzing, but you can also just be, like like I said, trigger happy and just, you know, buying a bunch of stuff and going on a shopping spree. Absolutely. At some point, that's gonna have to scale back where you're gonna have to, like, really, really understand whether or not these tools are are helping with, you know, whatever goals you're looking to achieve. So I'm I'm curious to hear, Nicole, how how do you, you know, measure that with your clients? Any real life examples would be great too. Yeah. So my first litmus test is I recommend every one of my clients has a core tool. So usually, like, the the recommended core tool would be either, like, paid chat UBT accounts, paid, uh, the Google Gemini accounts for Workspace. Uh, it can be Microsoft Copilot, or it could be Anthropic Squad. But, like, those are what I consider a core AI tool. And so my first litmus test for any other tool is, can the tool that main tool already do it? And if it can already do it, and it it can probably do it better. Nine times out of 10, that core two tool can do it better than the purpose built tools. Honestly, there's no exceptions to that, but usually. And so I will say, like, let's not spend the money and the distraction on tools that can do the same thing that main tool can do largely because you're not gonna get your team logging into 18 different tools. Right? You can build the habit of one and understanding, like, I always go to this one first, and I we build it workflows and everything around that specific tool versus having seventeen, eighteen different tools, and you've gotta figure out what do I use for what, how do I use it. They change their interfaces every other day. Now you got to figure out where they move the buttons, what it's capable of. It's just too much to keep up with. So my number one litmus test would be, can my course will already do it? If it can, don't waste the money, the time, the energy. The second litmus test I have is do that does that tool have the funding to continue? Because there are dime a dozen, like, AI tools popping up everywhere. Some of them are like I think maybe we're getting past the, like, in your mama's basement, no money, you know anything, but, like, that is still a thing. Right? So a lot of these tools have no traction to necessarily be here in three months, six months, nine months, and you do not wanna be wasting your time and your energy building out comprehensive workflows and all of your strategies in a tool that's just very likely not to exist in a very short amount of time. So my test number two is, is this tool actually going to definitely have the funding, the backing, the potential to actually last for a long time, Or am I gonna be building out things that are gonna vanish into thin air? Um, usually those two things alone will eliminate the vast majority of excess tools. Um, but then from there, like, let's say you've got other because it's not to say you're never gonna have other tools, but the others, then it's like, am I saving like, how am I measuring that this is valuable? Is it saving time? Is it saving money? Is it save is it improving quality? Is it helping us to do marketing in a better way than we ever could have before? And if you can't tangibly measure it, then it's just a cool distraction. Like, you have to know why you're actually using it. I love that. I I great three kind of, like, strikes for that litmus test. I especially love number two. I've actually haven't heard that before, the funding piece, um, because we're we're working so hard building these workflows and infrastructures that are so reliant on some of these tools. And if it vanished, then tomorrow, like, you know, it it that would be heartbreaking if you'd spend a lot of effort doing that. So thank you for AI Marketing Alliance is really expensive. So, like like, these companies can't last without money, unfortunately. Um, Ashley, what about you? How are you, you know, deciding on a litmus test for whether or not to shelve the tool or to continue using a tool for for an organization? I kinda take an opposite approach because a lot of enterprises don't know how to build the business case for AI tools, and so I kinda take the approach of we're as marketers, especially, we have tools in our tech stack that have feature updates that come out on a weekly basis that we don't know about. So the first thing that I do is audit their tech stack, and I will get them to start communicating and measuring experimentation in terms of what is your objective, what's your hypothesis, does the tool in your tech stack forget about AI, take that off the table for a second, but does this tool in your tech stack do the thing that you need it to do in order to make you a better marketer? If not, let's talk about it. If it does, great. And once we kinda get a consensus of what people do and most time don't know about their current tech stack, we end up finding out a lot. Um, one of the biggest breakthroughs is once people start to actually experiment with the tech stack that they've had, even if they've been using the tools for ten years, they start to realize the new AI features. Oh, Salesforce, HubSpot AI, Asana AI. I can drop a call transcript into Jira, and it'll populate a whole entire project for it. That's wild. So just getting them to think about not just stand alone AI tools, but the tech stack that they have and AI capabilities in it. Because most of the time, they don't know that they're there, so that's technical debt. And it's almost always something as simple as whoever has the, you know, the billing or the admin access doesn't know to toggle these things on, or IT doesn't know what precautions they should take so that they can allow access to the whole entire enterprise even though this tool has been approved in their tech stack for years. So I like to get them to communicate kind of like you do on your resume where you're experimenting, but you're communicating even better about what you're able to accomplish, and you're quantifying everything. So if we end up finding out that with, again, Asana AI, you can take a call recording and drop it in and it populates the whole entire project board and subsections and tasks and it designs people things. In one team alone, that could be ten hours. What does that cost? $25,000? That's a huge breakthrough. So I try not to take anything away from, oh, you're not experimenting with a stand alone AI tool? That's not actually AI tools then. I try to get them familiar with what they already have to kind of reassure them and bring that confidence back in that these these are not that different than what they're used to. You just have to communicate a little bit differently and get super hyper focused. And then, obviously, when we start to find some gaps and we end up starting to inevitably get frustrated that our tools aren't talking, that's when we start bringing in those AI tools to cover those gaps. But it's a nice little way to to keep the revenue in mind when you're thinking about these workflows, but also just to align a workforce on what actually matters and not getting so hyper fixated on the shiny stickers with AI. Yeah. I mean, you always have to bring it back to the baseline of, like, what was the key objective and and really make sure that you're grounded in that foundation. Um, because as you get going, you can very quickly just, like, you know, lose lose course if you're not, you know, if you don't have that objective foundation. Um, we're gonna launch our first poll here for the audience. So as Alex mentioned before, we do have some giveaways. We've got a grand prize giveaway. Um, and so all you have to do is, um, you know, answer the polls throughout all the sessions today. Um, and first one is has just been executed. And so this question is, when prioritizing AI tools for your marketing stack, what is your biggest deciding factor? Um, so we're I'm gonna launch that poll right now. You can see that on the on the right hand side of your screen, there's a poll tab with a red dot on it. So click on that and answer your poll. We'll take a look at some of the results, uh, from the audience in just a little bit. Um, but I'm gonna move on to AI onboarding strategies. So, uh, let's talk about onboarding. Uh, so, Nicole, when you're introducing AI to a marketing team for the first time, um, what is your sequence or or framework? Do you start with a, you know, single quick win workflow, or do you bring in multiple tools at once? Um, I know that you mentioned that you you like to anchor on one main tool, but I'm curious to hear, you know, um, as as, you know, a lot of the audience here may be in the early stages or mid stages of exploring AI. What is what is the secret success kind of algorithm that you've seen with onboarding team successfully? So for me, what I have seen is, one, just for clarity, I'm working more on the generative AI side than, like, the data analytics AI side, so I'm really kind of focused through that perspective. Um, but the first thing I think is really important to do is give everybody a understanding of that core tool that we've chosen for them to work with and some basic AI literacy. You cannot assume that literally anything with AI is common sense for anybody. You need to help make sure that they understand what they are and are not allowed to do in the tool, which is gonna be a little bit company specific. They need to understand where the limitations are and how the you know, these tools can make things up. They can hallucinate. You have to be fact checking everything. How incredibly dangerous it can be to do AI work without a human in the loop. Making sure that they really understand that they're the most important part of the process when they're working with these tools. We're not trying to automate their jobs away. We're trying to help make them have an assistant in the work that they are doing. So giving them that, like, understanding of some really important components of AI, not taking for granted that everybody just knows this. They didn't learn this in school. There is no common sense with this stuff. And then from there, building basic skills. How do you appropriately communicate with the tools? What goes into a good prompt? What is the tool that you have actually capable of? Because once you give people the skill set and the understanding, they will have a lot of light bulb moments go off on their own of how they can use this tool to dramatically improve their own workflows. And so we start with just understand what your tool can do, how to communicate with it, what it is capable of, and instantaneously, they're gonna, you know, two hours later, get better results than 98% of marketers who are trying to use these tools just from that baseline skills building, and they'll be able to see how to bring it into their own workflows. And then from there, we are working on, let's go through workflows and identify really high impact places to help you achieve whatever the goals that this team has are, and how do we need to bring AI into your existing workflows or create new workflows that are based around AI, um, to be able to do what you want to. But it's kind of a three pronged approach to general literacy skills building and then actually bring it into your workflows. But there's really two parts to AI. Like, use cases are really big deal and really important, but a lot of the biggest gains people are gonna get are things that are just because they have access to a tool like chat, GPT, or Gemini, have the skill set, have the understanding, and it's the one off thing that they just saved twenty five hours on because they understood how to use the tool and you never would have put it into a workflow. It just is the project that came up that they were able to use their knowledge, their understanding, their skills, and really move the needle very, very quickly to execute on. I love that framework, that three pronged framework. Ashley, I'm I'm curious to hear your reactions to that given that you shared that, you know, the most common use case that you've seen, uh, with implementation or starting point being the CRM, which is very, very data heavy. So I'm I'm curious to hear your perspective on onboarding. Yeah. I mean, I think it just depends. Even if you're choosing something like data, it's not that everyone's going to be experimenting in the same exact way. Right? Like, if you have email marketers experimenting with AI in their CRM, they're going to be playing around with things like email subject lines and conversion rates and, like, how many touch points to actually get a customer to subscribe. But in the same lens, if you're looking at data, you could have your data analytics team scrubbing up duplicates and using AI features in HubSpot to clean up their CRM and consolidate their fields so that HubSpot and Salesforce are playing nice. So there there's so many endless possibilities. It's more so I would just say, from my opinion, if I may get a little spicy, just aligning the top first. I think that that's where I start my approach because so often, we forget that, like, AI is an amplifier. Like, it enhances what's already there. So if there's misalignment at the top and maybe it's the board saying, we need to use AI, but not actually, like, giving resources or guidance or structure or bringing anyone in to coach the executives, that's going to be felt throughout the whole entire organization. So I immediately, in my discovery calls, pull the executives in and the founder, and I ask them to align on the biggest problem because I need them to all hear each other say, this is the problem. We're choosing to start to experiment with AI to help solve this problem, but this is a priority that's not gonna go away tomorrow or the next day or the day after that. And then from there, we'll break the whole entire enterprise into working groups. Maybe it's experience and activation and content or strategy, whatever it is. They're all going to be experimenting, and they're all going to be using different tools in their tech stack for different reasons, but it's all going to bubble up to what the executives want. The employees just are not gonna feel that pressure because they shouldn't. They're experimenters. Just like executives should not be the ones that are managing the experimentation, they should get out of the room and manage the stakeholder communications and just letting the board know what's going on and what's the ROI look like. But leaving the employees that are actually in the trenches of their own workflows to actually experiment in a safe way because those are the people that are going to be affected the most by it. At the end of the day, yes, this is tech we're talking about, but it's emotional. So what can you do to corral the whole entire organization to understand that you're gonna move the middle? If you have people that are fearful, let them be fearful. This can be scary. This can be terrifying. Stop trying to tell them it's not. If they think it is, just give them a minute. Keep having conversations with them and move the middle up. It's a lot easier to turn a maybe into a yes, and you don't have to go at it the same exact way with this aggressive, like, we're gonna do everything AI because that sucks, and we don't need any more of that. It's more so just what can we do to make ourselves better and, like, what does better even look like for our company? Apply AI to that. That's great. And and we're gonna touch on, um, cultural buy in, um, and executive buy in in just a little bit. I'm gonna share the results of our first poll. So when we ask the audience what the, um, prior oops. Sorry. We're gonna share that poll right now. Uh, when prioritizing AI tools for your marketing stack, what's your biggest deciding factor? And so majority of the audience is pretty split, um, immediate ROI potential, um, and how well integrates with your existing workflow. Any of these results surprise you, Nicole or Ashley? Not even a little bit. No. You know, we're not gratification. Um, awesome. We're gonna actually open up our second poll right now, which is, um, for the audience. What have your what's been your team's biggest challenge with onboarding AI so, um, so far? Um, and then we're gonna keep talking about workflow design and success stories. So, Ashley, I'm gonna start with you. So you've led, um, some AI rollouts were really impressive. You you've shared with me that, um, you know, you were able to deliver measurable revenue growth in months from rolling out AI. Can you walk us through one workflow that you've built, um, that was directly tied to hitting those numbers? Um, I'm sure they are be curious to hear. So I'll walk you through the 2021 because it was the wild west back then. So in 2020, when I first started using AI, I was able to consolidate my almost eighty hour work week down to fifteen by keeping track of how long tasks were taking me just by downloading Toggle, a free Google Chrome extension. Um, it's super depressing, so don't do it on, like, a week that you're getting your butt kicked. But, like, if you ever wanna know where your time is going, it's great. It'll it'll definitely keep track. Um, and so I got really, really curious about how much time could be saved with onboarding. And in 2022, March 2022, I believe GPTs had come out. And so the enterprise that I worked for at the time, they're saying, listen. Like, we have we have toggle. We have the extension. Like, we know where our time is being spent, but, like, there's nothing we can do about it. And I said, okay. Well, where is that time being spent? And they said, we're onboarding new sales executives. Like, our senior leaders are onboarding them, and it's taking their time away from in person events, which is bringing an ROI. And when I had a couple conversations with the senior leaders that were onboarding, you know, all of the new sales reps, they were like, I just want them like, it was very important for these senior reps to teach the newer employees, like, how they can optimize, like, time with clients. And it was really important to them and for good reason. Like, they knew what they were doing, but from an onboarding perspective, it still didn't make sense to have a ton of their work week being spent onboarding and training. Like, there was a certain portion of it that could be automated. And so I interviewed five senior leaders for about two hours, uh, asked them questions like, what is the most important, you know, aspect of onboarding within the first three weeks? What does success look like? All these different questions, and I turned it into a GPT. And the new sales reps for the first three weeks that they were getting onboarded as they were learning all about calling and prospecting and how our product fit into our prospects' hands and all these fun things, they were relying on this GBT with the knowledge base Google Drive from these senior reps to ask all the questions that they want so that when they did get the time with the senior reps, they were actually shadowing them in person at events. They were getting a lot more higher impact, um, onboarding experience just by simply taking away the busy work of asking questions twenty four seven and being able to because it's so easy when you have Slack and Teams. That's awesome. I love that story. Um, and so, Nicole, in in your work advising CMOs, where do you see the ownership of AI sitting most effectively? Um, I think, you know, across there's so many as as marketing teams get larger and larger and there's different functions of AI, I'm curious to hear your perspective on if there's a single AI lead role, or or do you think it's more effective when it's embedded across the team? It very much depends on the size of your team. Right? So, like, a startup with three people on their marketing team versus a big public company with, like, a 150 plus people on their marketing team, it's not necessarily going to be the exact same answer. Um, I think there's a couple of different things. I think you need some leadership around AI for sure. I warn against a single AI lead role, And it's not for the reason you think, but it's because I've been doing this for quite a while, many years now. And I have noticed an AI leads to consultant pipeline where the person who has on their resume that they were, like, the AI lead on a marketing team or at a company, there is such a strong pipeline of leave the company to start your own consultancy because the money is so good. And so if you have put everything in one person's hands, that person leaves to go start their consulting gig, and now you have no idea what is going on with your AI. And it is happened I have seen it happen so many times that companies of all different sizes that I I would strongly advise against giving one person the role of being in charge of AI adoption for that reason. What I have seen work extremely effectively is on each team itself. So, like, on the content team, on the, um, demand gen team, product marketing, each of these teams, you have an individual lead for that team on AI. And then you have those all of those leads that basically work together. They have, like, a weekly Zoom call or a weekly meeting in person if they're in person. Every one of them knows exactly what's going on on the AI holistically across the organization and the marketing because that's important. Like, you have to be not reinventing the wheel also. Like, if one team's doing something, it may be very easily usable by another team. So they need to understand inside out what everybody else is doing with AI, share their learning, share their adoption, be building it all together, but you don't have it sitting in one person's hands. So if one of those people leaves, that does not throw your entire AI system completely out of, like, whack. And then simultaneous to that, those people are responsible for adoption on their individual teams, building, like, the bigger workflows. Maybe they're the ones who are really excelling at building things like GPTs and the AI systems and workflows. And then they are helping their the rest of their team to adopt. So everybody still learns it. Everybody's still using it. This is like the Internet. Right? Like, everybody needs to have a basic level of using it, but that person is responsible for, like, kind of the whole adoption on their individual team. But this this combo of one person on each team bringing them together with everybody so you don't have all of that institutional knowledge in one person's hands. That makes a lot of sense. Dereisking your organization for more stability. Um, I I can I can imagine if you had, you know, one person holding the keys to the kingdom and then something had happened, uh, what that down like, that outcome might look like? Moving on to our next sort of section, it's actually our final section before we go into a couple of q and a. For the audience here, if you have questions for Ashley or Nicole, please do head over to the q and a tab and ask your questions. If there's a question that you really, really like in that tab right now, go ahead and upvote it. I'm gonna actually answer the top two to three upvoted questions, so please do go ahead and and check that out. Um, so last section here, team structure and cultural buy in. So uh, I'm gonna really, you know, sum this. We had a couple questions kinda floating around, but I'm gonna I'm gonna sum this up a little bit. Um, you know, having seen the results from the poll here, uh, from the audience, you know, what their biggest challenge with onboarding, This the the least voted, um, is getting leadership buy in for AI initiatives. I think they'll actually, a lot and the reality of things, a lot of AI, um, AI functions are being mandated from the top down. A lot of leaders are actually asking teams how can you do more with AI, do more with less. So my question here for you is, uh, when you're working with exec teams and marketing leaders, um, how how do you handle, um, the fear that whether it's fear or actually the the desire, I'd I'd love to hear your experience that AI will actually replace human jobs. Um, you know, I think that there's there's some fear out there that human jobs are going away, but there's also the flip side where they're asking, can can role be replaced with a an AI tool? So I'm I'm curious to hear your perspective on on that specifically. We We'll start with yeah. We'll start with Ashley. Um, okay. So as far as my my perspective goes, yeah, absolutely. This is a conversation. There's no innovation happening unless you hold safe spaces for these conversations. It's just not gonna happen. Um, and so I think first, just kinda getting leadership in the mindset of, like, you're gonna have these conversations. There's no, like, we're gonna skip this and not talk about it. Um, you're going to. And I would say my conversation directly with leaders, especially CMOs, is it's not your job to make sure that everybody's role stays exactly the same, and you shouldn't want that for your team. If you have one person that can learn how to use AI tools or optimize the tools in their tech stack to do more things that they enjoy doing or give them more experience, maybe they wanna hop over to product marketing. Maybe they just want to do something different and shake up their day to day. You should want that for themselves, and you should want to encourage them to do that because then you can actually start to recreate roles. And we see it every single day, like marketing engineer, you know, go to market prompt engineers. These are rules that didn't exist before. AI consultant. Like, I feel like I made that up, and I wear it as a badge every day. Like, I don't know I don't know how that's real. But the ability for people to take their domain expertise and use AI to get more time back in their day or make more money for themselves in their business. These are conversations that everybody has in common. Everybody speaks money. And so really trying to take the fear of the jobs and replacement with how is leadership actually showing that they are trying to encourage upskilling within their workforce? Do they have this attached to promotions and career conversations? Are they having at least a Slack channel where executives are talking about the ways that they're using AI? Is there anything going on that's being led internally by, you know, groups or experimenters or even leadership on these different conversations and what's going around and and acknowledging that, um, you know, every day we get on LinkedIn and we see that people are being laid off, and it's just it is what it is. Not acknowledging and it's not going to make your employees feel better, so just talk about it and acknowledge that that's really crappy. But, also, maybe that company had other things going on, and we're seeing that it might be because of AI and agents, you know, taking over, but it's actually not. Um, so I think just it's like a two parter of holding more honest conversations, pushing some accountability back on leadership to actually provide resources and training and education if they do want to take this seriously for their employees. Um, but then also just being honest with the executives and saying, like, listen. As you become more and more senior, you're used to having to know the answer for everything, and this is not what AI is like. AI is very much you don't know what you're doing, and you're gonna have to be okay with that. And if it's not okay and it doesn't feel comfortable, that's fine. That's totally normal. But just be honest about it because the sooner you're honest and you're like, oh my god. I have no idea what I'm doing, but this was really cool and I'm gonna keep trying it, you're going to make everyone else feel better. The more you hold it in, the more you pretend like you know what you're doing and your nervous energy is wearing off, like, people are gonna feel that and it's gonna freak them out, and they're not necessarily gonna translate in their minds. Hey. Our CMO doesn't know what she's doing with AI or he's doing with AI. They're gonna go to the worst case scenario, which is, oh my god. A layup's happening even though it might not even be happening. So get the weird energy out. Also, just address the elephant in the room. Yeah. Um, Nicole, what's your response to to that? So when I'm talking to a CMO about this, I try to have a honest and transparent conversation. And, you know, there's also there's the CMO and then there's the team, and those aren't necessarily the same conversation you'd want to have. But, like, I think it is important that we are honest. AI is going to lead to a lot of job losses. Like and I hate that part of AI. I personally really, really hate that part of AI. We should not be getting rid of people right now with AI. Like, AI is not at this place where it is replacing people. And but the reality is if you can have one person do the work of five people, why would you have five people? It's not so much that it's like, you know, you're gonna go in and you're gonna have AI just do specific roles. It's gonna become complete reorganization and one person understands these tools inside out and does the work of five people. And where I'm seeing it right now is a lot more is, like, we are not gonna hire more people. As people as we have natural attrition, as people lead, we're not gonna hire more people. So how does this translate to what a leader needs to understand is this is probably where whether you want it to be this way on your marketing org or not, it's gonna come trickling down to you that there is going to be this expectation. We all hate it. I don't think anybody gets in favor of the idea of AI job losses, but, like, this is just part of it. And helping your team to be as future proofed in this as possible because you when you give them the skills, the understanding, the ability to be the ones who are phenomenal with this technology, they are the least likely to be affected. Right? Like, who are they going to get rid of? Who would you let go of if you're being told every one person has to do the work of two or three or five? You're gonna keep the one who understands how to use the tool to be able to do the work of two or three or five. And so helping your employees understand that by learning this technology, by understanding how to take advantage of it and use it to do your job and expanding your skillset and your abilities and experimenting and getting really good with it, you are the person who is personally protected and insulated, not just in our organization because our organization may not ever get rid of anybody, but you want to go and get another job. Nobody is hiring a person without these skills. You would not hire somebody who doesn't know how to send an email. You would not hire somebody who doesn't know how to do a Google search. And in 2025, most companies, and definitely 2026, 2027, they're not gonna hire people without a basic level of AI literacy. And so it's really getting the team to understand learning this is not the thing that takes your job. Learning this is the thing that protects your job, and you being the human and because we're gonna need a human. We're always gonna need a human. You have the opportunity right now to be the human that is protected, and it's up to you. That's such a great point. Um, it it kinda reminds me I was on TikTok or Instagram, I think, a couple couple weeks ago, and I this might be click beta. I didn't verify it, but I saw that China was mandating, like, kindergarteners to learn AI now, which is wild to think. But that is the future of work. Yeah. So thank you for sharing that, Nicole. Um, we are we're short on time. We we have about five like, four minutes for questions, and we have a lot of quest and so, uh, I'm gonna again, audience, if you wanna go to the q and a tab, go through the questions quickly and help out your favorite ones. I'm gonna start with the the one with the most upvotes at 24 votes. So from e Smith. Um, I'm gonna direct this specifically to Ashley. Uh, what tools or processes do you use to clean up your CRM data? Okay. So this may sound, um, really lame, but, honestly, I will export fields from Salesforce and HubSpot, and then I will use Claude to recreate a new sheet. And then I will put it back in the CRM so that I'm not actually using an AI tool within the CRM, um, just to keep everybody safe and protected. Awesome. Thank you. And then, um, next question here, I'm gonna share onto the screen. I'm curious if if Nicole, Ashley have a perspective on this. Um, but SEO optimization used to be key. Now, you know, things are changing. Uh, we throw in the LLMs. How much emphasis should be to be teams be on discoverability on LLMs versus the legacy digital efforts? Um, we do have a session on content later, so definitely check that out, Natalie. But I'm curious, Nicole and Ashley, if you have a perspective on this. I would say that you need a really incredible content strategy above all else. So I would have your content team, your product marketing team, and your SEO, whoever your SEO is, working together because there's gonna be a technical side of making sure the AI can read your content and that kind of falls more into the SEO piece. And then you're gonna have this content product marketing hybrid where you need to make sure you have a really solid content strategy that tells the AI everything a potential customer might be using to help decide if they would want to use your product, come to your company, whatever that thing is. And so you need to be upping the game on the content you have out there. So in the very short version when we only have a minute, I would say, like, putting together a team with kind of those three areas is a good place to have it live. My answer is actually gonna be the opposite. So that worked out really beautifully. I was gonna say the experience team. So website, um, demand generation. I would say anything with digital marketing where you're super focused on channel and the overall user experience. It's not a game of volume anymore. You can have 50 blogs put out every single week. It's more so how fast can your prospect find value, and can you keep them there after you provide value to upscale them or teach them something new or entice them even further? So I I don't think that this should even be, you know, something that has to have its own plan necessarily. I would say, like, at a minimum, what I would do is I would put myself in the prospect's shoes of whoever you work for, and I would go on the website like you were trying to buy that product and go through the experience and write down everything that sucked and everything that you hated, and then redo all of it, um, around how fast you can provide value and and just create a really great experience because that's ultimately what AI is doing a lot faster. Awesome. Well, thank you, Nicole and Ashley. That's all the time that we have. Um, audience, thanks so much for staying tuned. We have about a five minute break now. So if you you wanna grab your water, go ahead. If You wanna go take your school photo. I'll click on that take your school photo tab. Check out that AI age regression. I did that up two weeks ago, and it was hilarious. So check that out. Post it on socials for a chance to win a grand prize. For our next session, um, it's gonna be three different tracks. So we've got marketing leadership track, a demand generation track, and then a content track. Um, so definitely, you know, choose your adventure and and what makes the most sense for your role. Um, but we'll be back in about five minutes. Again, Nicole, Ashley, thanks so much for joining me. It was a pleasure being here with you. Thank you so much. Have a great day. Thank you.