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AI is suddenly in every product demo, boardroom deck, and vendor pitch and the pressure can feel relentless. We slow the hype down and ask the question most teams skip: what does “we need an AI strategy” actually mean for the business, the customer, and the day-to-day work your marketers are drowning in right now?
We talk about why urgency is spiking across Fortune 100 organizations, especially as consumers use LLMs like ChatGPT to discover products, set expectations for real-time personalization, and demand experiences that feel relevant immediately. That shift changes the competitive landscape, but rushing into AI adoption without direction can lock you into expensive decisions that don’t fix the real problem.
Our approach is simple and uncomfortable in the best way: start with the company vision and growth priorities, then go bottom up and map how work actually happens. We look for bottlenecks, monotony, waste, training gaps, data issues, and broken operating practices before we ever “add AI.” When you finally automate, you do it with purpose: let AI handle the repetitive complexity so humans can lead with empathy, judgment, and creative direction. We also challenge the default ROI story, because in big companies, hours saved rarely matter. What matters is what you create with reclaimed time and how much faster you can reach strategic goals.
Next week, we bring on Jorge, a former CEO and CMO who now advises companies on piloting, measuring, scaling, and proving meaningful AI ROI. Subscribe, share this with a marketer who’s feeling the pressure, and leave a review.
What’s the biggest workflow bottleneck you’d want AI to remove first?
Hello, and welcome back to season three, episode two of That Martec Girl, the podcast where Martech meets culture, the business podcast with personality. My name is Rachel Gray, and today we are going to be talking about having an AI strategy. But what does an AI strategy actually mean? Let's get into it. AI, AI, AI. It is absolutely everywhere. I can't have a conversation without it coming up. I'm sure the same is for you. And that is really a reflection of the discussions that I'm having with Fortune 100 companies where they're saying we need an AI strategy. And my response always is, okay, but what does that actually mean to you? It seems like this technology is suddenly, all of a sudden, overnight, in every single product, every single presentation, every single boardroom conversation. And there is this overarching pressure for us to do something about this. It's like if you're not doing something with AI, you're behind and you can feel it. You can feel it. But there is a stark difference between AI washing where you're just simply adopting AI for the sake of saying, yes, we're using it. There is 50 to 80% usage of AI throughout our organization. And a difference between that and simply saying, hey, here is what we're trying to accomplish. Here's what's blocking us. And is AI the best solution in order to accomplish this? So today we're really going to explore how exactly to answer that second question in the best way possible. Before we get into the answer to that question, I do want to just say I hear you and I understand the urgency that is currently in every single organization that I speak to. Not only urgency, but pressure. And that pressure is top down and it's intense. It is. I understand. Because there really is a lot changing overnight.
What I'm hearing from customers every day is that consumers and the way they behave and interact with their brand is just completely different. And that is also causing a difference in expectations. So consumers now, because they have access to LLMs, they have ChatGPT at their fingertips, they're using it on a day-to-day basis. Now their expectations around personalization and relevant experiences aren't a 25 expectation. It is truly an expectation of today, right in this moment. Another thing I'm hearing is somewhat of how I shop, right? And it starts with the discovery loop in the LLMs, where I'm starting to ask LLMs about the shade of makeup that I buy or the type of skincare that I'm looking for. And so the product discovery is really starting in a place where it feels sort of unreachable at the moment to brands. And so across the board, the buying journeys and competitive expectations are changing. And that is really feeding into this hey, I need AI. I don't want my organization to get left behind. And so the urgency, the pressure, it does make sense. I do understand and I do resonate with you. But I do want to caution that just doing something for the sake of using AI and this urgency without direction or with organization, it can lead to some expensive decisions that are hard to undo. So that leads me to this question. If a CMO was supposed to come up to me, which sometimes happens, and say, hey, Rachel, I heard on that Martech Girl that you're talking a lot about AI, you're talking about marketing technology and AI. What should I do? Where do I even start? Here is
how I would approach that. I would tell that CMO to lock everybody in a room for a couple days. And I know that sounds crazy, but I think really having an understanding of both the top-down, where is the company going, and the bottom up, how does the work today actually happen? Needs to be a discussion that happens even before we truly start to address AI and an AI strategy. My reasoning is number one, let's talk about the top-down conversation. I need to understand, tell me about the vision of the company. In five years, where is this company going? Tell me the growth priorities. Secondly, tell me about, you know, the markets you're trying to expand into. Where are the opportunities that you have identified outside of AI? And tell me about how customers are changing. We could probably have that conversation about brand and product discoverability, right? But other than that, how are you seeing consumers change? And then I also want to have a conversation about outside of AI, tell me about the capabilities that the organization will need within this visionary five-year period. But then for the people actually executing the work, I also want a separate session with them locked in a room where we talk to them about the actual work that is being done. I want to map it out. I want to understand from the people doing the work step by step how the work is done to get to that vision, right? I want to see where are the bottlenecks, where's the monotony, where's the waste? Where are you being bogged down on a day-to-day basis? And then I'd ask this question. I would say, hey guys, let's take a step back. If we could reinvent all of these processes and procedures and eliminate some steps, which ones would you eliminate first? Okay. So that would be my first step in that session or those multiple days that we're locked in that room. And then I'd take that information, go back into Rachel Land, and I would start to connect the ambitions of the business to the obstacles that are preventing the progress. And I'd rank them step by step. Before I got to AI, I would first look at how I can make this process better. Just take AI out of the equation. How can I make this process better? Maybe it's improving training, maybe it's data, maybe it's operating practices, all of these things that come prior to the AI conversation. Finally, once that is done, I would then take a look at automation. Where could AI put in the right places address the bottlenecks and redundancies that are currently happening? Because sometimes the problem is organizational-wide, sometimes it's about training, sometimes it is just about the structure of the organization. And just slapping AI onto a process that isn't working might even make it worse. So, yes, sometimes you do need AI. I do agree. But let's first take a look both at the top-down level where we understand the vision, and then secondly, how the work is being done today so that we can really prescribe the best AI fix for each organization. And every single time it's going to be a bit different.
So once we have gone through that process and AI and technology is taking some work off of people's plates, what do we actually want them spending their time doing? You know, sometimes I serve as a therapist for marketers because I talk to you guys on a day-to-day basis, and I hear your concerns and your questions and your thoughts just on your current setup and your job. And what I hear over and over and over is that you guys love being creative and you love the just beauty of marketing, where you get to really touch your consumers in an innovative way and just transfer this level of human to human connection at scale. And I am just always impressed by that, right? But right now, as it stands, in every single conversation I've had over the last years, year is I've heard, you know what, Rachel? All the time I just have to have these endless meetings, this manual coordination, all the systems are disconnected, all the tools don't make sense. Some people don't know how to use the tools. I have to train them on the tools, like, and then there's no AI tools to learn. I am so confused. I don't have time to actually do the job I love. And I hear you, I hear you. So what if we were supposed to go back to you guys doing what you love, having marketers spending 90% of your time doing that creative, strategic, experimental, customer-focused work because you're selling to humans and you need humans to sell to humans while having AI support that segmentation, the personalization, the analysis, and then eventually scaling that work, right? This lets you remain accountable for that context, for the empathy, for the judgment, for the creative direction. And it lets AI do that monotonous work that you hate doing, anyways, right? So let AI handle that complexity so that you can actually do why you have this job in the first place. So
now that we've given you your capacity back, let's talk about measuring that ROI. For a Fortune 100 company, simply reducing headcount or even saving some time for the employees that you do have isn't necessarily a big mover in revenue for these organizations. We're talking billions of dollars in revenue that these organizations have. So if we're supposed to eliminate a few hundred thousand dollars, maybe even a million dollars or so, that's not really going to move the needle. But where it gets interesting and where we can actually move the needle is if we've been able to consolidate these monotonous processes and take that time back, give that to the employees, and now align the work that is being done in an efficient way to the vision of the organization. So we can then get the organization to where it's going instead of in five years, maybe in one year, maybe in two years, maybe in even three years. A two-year gap is tremendous when we're talking about getting that organization somewhere with that same headcount that you have today. Imagine what that can do. Now that is actual ROI, right? We're talking more experimentation, more creative output, more personalization, speed, better customer experiences, and that will turn into better return on your investment. That, you guys, is the answer. And that is why having a strategy is so important. The question isn't just how many hours were saved. It's what is your team doing about that time savings? And do they have a plan for that time that's being given back to them? Right? Because saving time isn't necessarily the ROI. It's what does the organization create with that time that it gets back? So
now let's get back to how we started the episode, which is what does it actually mean to have an AI strategy? In this monumental time in history when every single thing seems to be changing, all the rules are being rewritten. The companies who win aren't gonna be the ones who get every single AI tool. They're gonna be the ones who know for certain where they're going, right? They know that very well. They know and understand how they work today, they understand what exactly is blocking their progress to get to that vision. And they truly value humans, they understand how humans connect with humans and how that can be done at scale, and they understand that their people matter. And then they truly start to grasp where technology can take them in this framework, right? So let's stop starting with where can we use AI and just go about that blindly that I'm seeing every single day. Please stop. Let's start with where is the business struggling? And what is the best way to fix it? And how do we get to our long-term vision in a shorter amount of time with the resources that we have today using AI?
So once we've now identified the right opportunity, the question is how do you actually pilot these AI projects? How do you measure them? How do you scale them? And then how do you prove that meaningful ROI that will scale throughout these humongous businesses? And I have the perfect person to answer it. It is Jorge, who was on the last episode of season two. He is a former CEO, CMO, and he is also on the boards of multiple organizations. He has such a great perspective. He actually owns and is the CEO of his own consultancy today, where he is advising companies currently on these exact topics. So we are going to be talking with him next week. I am very excited. Um, just please stay tuned because he's going to be answering those questions for us. Thank you so much for listening in and supporting myself and that Martech girl. We truly appreciate you. Have a wonderful rest of your week, and we will talk next week. Bye now.
