How Tech CMOs Are Embedding AI Across The Marketing Stack

AI isn’t a side project for marketing anymore. It’s becoming the way work gets done, and that shift is happening faster than most teams can measure, govern, or even fully see. We sit down with Ed from Callan Consulting to unpack what he’s hearing directly from CMOs and heads of marketing about real-world AI adoption in tech marketing, from early-stage startups to multi-billion-dollar enterprises. 

We talk about the move from experimental “skunkworks” use to embedded AI across the marketing tech stack, including LLMs like ChatGPT and Claude, AI features inside core MarTech platforms, and a growing wave of AI-native tools designed for specific workflows. Ed shares why so many leaders report major impact while still struggling to quantify ROI, and how “born-in-AI” companies are rethinking org design and productivity from day one, sometimes even putting agents on the org chart. 

Then we get into the tradeoffs: token budgets, tool sprawl, and the rising risk of overreliance. If everyone ships AI-generated content at scale, everything starts to sound the same, mistakes slip through, and the internet fills with “AI slop” that models train on again. We lay out a practical path that protects brand voice: keep the hero content human-led, then use AI for atomization, localization, optimization, and distribution. Finally, we look ahead at generative engine optimization (GEO), the early dip in traditional SEO traffic, and why “machine engine optimization” could matter as buyers use agents to research vendors. 

If you want a grounded, executive-level view of generative AI in marketing, listen now, then subscribe, share with a teammate, and leave a review so more marketers can find it.

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Transcript

SPEAKER_00 0:02

Hey everybody, really timely, interesting topic today. We're digging into the real estate of AI adoption in tech marketing with Ed from Cal Consulting. The question is Are tech marketing teams actually getting smarter and faster with AI or just adding another layer of complexity, maybe chaos with better branding? Big questions, Ed. How are you? Hey, Evan. It's nice to be here today. Well, nice to have you. Before we dive into that really juicy topic, maybe introduce yourself for those who don't know you, a bit about your background story and what you do.

SPEAKER_01 0:39

Thanks, Evan. Yeah, I'm I'm a longtime career marketer. I'm the CEO of Callon Consulting. Uh, we're a boutique-sized uh marketing consulting firm located in the San Francisco Bay Area. And our clients include uh everybody from early stage startups to household names like Google, DocuSign, SAP, um, Amazon. And um basically we help technology companies bring their products to market.

SPEAKER_00 1:05

Fantastic. Well, that that's quite a pedigree. Great to have you here. Um, tell us about some of the work you're doing recently on the state of AI adoption. Obviously, we're all AI crazed these days, but what's your particular perspective on the topic and describe some of the research you're you're doing there as well?

SPEAKER_01 1:27

Yeah, we've actually been, you know, sort of well, we've been in and around AI for decades, right? Um LL, you know, machine learning, AI, that sort of thing. Um, but we've been really focusing on tracking it since the emergence of LLMs about a couple three years ago, and how marketing organizations are using it and how it's impacting marketing teams. So in 2024, we went out and did a study. We talked to a bunch of marketing executives about how they were using AI at the time and it was early stage adoption. And um we went out this year, we we did a recreation of that particular study. Um, we talked to 19 heads of marketing, mostly CMOs from a variety of tech companies, including early stage startups, all the way through companies with more than $9 billion in revenue, including NetApps, Superhuman, HelloFresh. Our the median revenue of the people that we talked to is about $91 million ARR. And uh most of them, again, were CMOs of technology firms. And uh it was really interesting to see the where people are today in terms of their AI adoption.

SPEAKER_00 2:28

Wow, that that's a huge topic. What what a study. Um, so give us at a high level, you know, what is the state of AI adoption inside tech marketing organizations right now? Um, what's your perspective? What can you share? Yeah.

SPEAKER_01 2:42

Um, you know, it's really interesting. We found that we went out this year, it's it's very much a state of what we're calling embedded use. So uh two-thirds of the organizations say they have uh strong or very strong impact uh on their organization from the use of AI with a variety of use cases. We actually counted 71 different use cases that people are using AI for. Um it's no longer just content creation now, it's everything from uh sales and SDR co-pilot, localization translation, performing research on the market. Um, I mean, it just the list goes on and on. And it's actually embedded throughout the technology stack as well. So whereas uh a couple of years ago when we went out, there was, you know, maybe people were just using a few LLMs or um just kind of getting uh an early um sense of that. Um right now we're seeing uh it throughout the the entire tech stack. So on the one, you know, sort of the first case, people are using it for you know, claude, chat GPT, Gemini Copilot, et cetera. That's just kind of a given, right? Um and then in addition to that, there it's proliferating throughout their tools that they're using in their tech stack. So the Hubspots of the world, the sales loss of the world, the uh Zoom infos of the world, all have AI capabilities built in. But then we're seeing a third flavor show up, which is AI native use case-specific tools, things like AirOps for content operations, or um clay for data enrichment, or um Z Leaf for decision orchestration. So these, and it's just like um it's really proliferated, proliferated throughout the organization. It's built into people's OKRs, it's built into expectations. It's frankly just how marketing leaders are expecting work to get done today. In fact, we had an interesting story. One of the leaders we talked to said that two or three years, maybe two years ago, if a vendor had come to her and said, uh, we're gonna write a market analysis and we're gonna do, you know, uh, you know, create this deliverable for you. And if they were using AI at the time, she would have thought they were cheating and doing a bad job. But today, if they're not using AI, she feels like they're not doing it right.

SPEAKER_00 4:59

Really fascinating. And you know, from 2024, you mentioned your first dive into this space, this topic. Um, what's changed the most to today and what is changing this today from last week, last month, last year? Things are moving so so quickly.

SPEAKER_01 5:17

It's moving so quickly. Yeah, every couple of months you sort of have to sort of revisit and recreate. Um, so it was interesting. We did the study, you know, about 18 to 24 months ago, and it was very much experimental at the time. So we we found that people were using it in a skunkworks kind of an environment. There were the, you know, sort of the uh the the early adopters within the organizations were going out and pulling in tools and and marketing leaders were sort of playing catch up a little bit, and and and you know, you adoption was kind of proliferating sort of virally from the ground up. And most CEOs and and boards were sort of unaware of it. And today that's completely flipped around. So it's a board level expectation, it's a CEO level expectation, there are departmental-wide initiatives to use this. There's there's actually company-wide initiatives, and within that there are marketing organizational-wide initiatives, and usually there's at least one person on the marketing team who is kind of the AI czar. It could be a chief of staff, it could be a head of marketing operations, and they're the ones who are sort of uh tasked with making sure that the tools are sort of being used, the training is uh is is adopted is everywhere. Um people's OKRs all reflect the use of AI. In fact, we're seeing a lot of people, a lot of organizations where it's just built into the OKRs or the MBOs of the team. They're expected to use AI in different ways and and and uh adopt it and that sort of thing. Um two last year when we when we took did the study in 2024, we asked what uh impact AI is having on your organization. And two-thirds said it was having a moderate or slight impact, and only one third said it was a heavy impact. And today that those numbers have completely reversed. Two-thirds say it's having a heavy impact, a major impact, and only a third say it's having a slight or a moderate impact. So it's definitely adopted. Um, it is interesting though, because leaders are scrambling a little bit because it is kind of like drinking from the fire hose. There is a lot going on, there's a lot of tools out there. Uh, some are keeping on top of it a little bit better than others, some are feeling a little bit more comfortable about it than others, but um, but it's it's definitely here to stay. We we, you know, it's it's definitely not a flash in the pan, Evan.

SPEAKER_00 7:33

Indeed. And it's changed the way everything the way uh I do marketing and my productivity and my ability to proliferate and create uh content. It's it's been amazing. But you know, I'm an army of one. What about an enterprise? You know, they want to understand business impact from AI, whether it's not just productivity, like in my case, but actually improved output or lower cost or reducing headcount, you know, PL stuff. What can you say about that kind of impact?

SPEAKER_01 8:04

Yeah, I mean, that that was, I think, one of the most interesting things to come out of this study. And it was a really interesting thing to dive into with the marketing leaders about. Uh basically, everybody believes that it's having an impact, but it's really challenging to measure those benefits. So uh measurement continues to remain a challenge, getting actual sort of metrics around this. Um, we press them about things like, well, are you reducing headcount? Can you do more with less? Everybody sort of believes they can, they believe that they are, but at the same time, um, they're it's early stage in terms of being able to actually lay off individuals or or grow beyond where they are. So, and and another interesting thing to come out of this is the there's this sort of a bifurcation in terms of the types of companies in our study. So most of the people that we talk to, most of the organizations we talk to, have been around for a long time, decades in some cases, certainly years, and have marketing teams that predated the wide-scale proliferator proliferate proliferation of AI. And then a couple of the companies that we talk to are more recently on the market. And so they've they've sort of formed in the last three years when AI was part of the fabric of the way that things are done. And we call these companies born-in-AI companies. So, one of the interesting things that come out of the study, talking about the benefits, is that the companies that have been around traditionally for a long time are saying, I think I'm seeing 20, 30% headcount benefit. I'm doing the same work today that would have taken me maybe 20% more people otherwise. And um, you know, I'm able to grow more without sort of growing, I'm able to grow my department's function without growing the headcount quite as much. Um, and in fact, we are seeing some companies that are starting to put um uh uh uh agents on their org chart, believe it or not. So it's we're starting to see that, you know, my org chart has some humans and has some agents on it. But these born and AI companies that I talked about earlier, they're starting their marketing organization with AI as part of that core fabric, and they're seeing greatly improved benefit. So while the traditional companies are seeing maybe 20, 30% headcount benefit, the born and AI companies are seeing a hundred percent benefit. In other words, they're able to do the work that they they would have required double their headcount otherwise. Um, and they're just building it in from square one. So they're building agents into the way that they're uh building their content or doing their lead generation, and um, they're just kind of starting from from the beginning. And those companies are seeing the greatest effect.

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SPEAKER_00 11:24

Amazing. Um, yeah, I mean, so I I I clearly uh connect with this messaging. It's AI is

(Cont.) How Tech CMOs Are Embedding AI Across The Marketing Stack

SPEAKER_00 11:31

helping me and my little marketing team immensely. Uh things like video editing, Claude, it can do be a full video editor for content, data analytics, amazing and on and on. But in these enterprises you're talking to, where is AI helping marketing teams the most?

SPEAKER_01 11:48

Yeah, I mean, it's like I said, it's kind of across the board. I mentioned, you know, sort of 71 different use cases that we we covered. I mean, it it definitely content creation is still remains uh kind of maybe the centerpiece of most sort of AI use and adoption today. We all know that, right? Um, and whereas in 2024 it was maybe uh initial creation, today it's also being used for campaign optimization, SEMS uh SEM SEO, uh account-based marketing ABM, things like that, localization translation. So much more sort of broad scale in terms of the proliferation of different types of content. Um, but also things like lead generation and lead scoring, um, message testing. There's a lot of research being done right now, uh, not just on sort of secondary research to sort of understand trends and analysis and stuff like that. But there's even re there's even uh ability to go out and do uh simulated focus groups, sort of, you know, say come back and tell me what these 12 decision makers would have said if I had asked them these kind of um organizations. Um but PR, predictive insights, um analytics, um uh there's just it we as I mentioned, we've counted 71 different use cases um across the organization. It really sort of touches all aspects of marketing.

SPEAKER_00 13:06

Brilliant. So what we're also I think learning with AI is that there's no free lunch. We we went we're going from token maxing to uh tokenomics. And uh many people, including myself, realizing they're blowing through their AI budget and and uh their token uh usage, spending hundreds in my case, more than I wanted in a week. Um one of the other barriers holding teams back uh in addition to economics.

SPEAKER_01 13:38

Yeah, I mean you sort of touched on one of the big ones, right? We're seeing a lot of backlash around that today. But some of the other things that we're sort of seeing is an over-reliance on AI. So leaders are certainly recognizing that if we use AI for that initial sort of content generation, um, it's there's a there's a huge risk that it all sort of sounds the same. And even though a lot of organizations, a lot of marketing leaders are paying at least lip service to the fact that they want to have a human in the loop and they want to make sure that you know they sort of that what comes out of the AI is very consistent with their brand uh voice and that sort of thing, the reality when you sort of scratch a little deeper is that um people are sort of there is a danger of overusing the technology today. And a lot of people who are using it to create content, um, I'm not saying everybody, and definitely not you, Evan, right? But a lot of teams out there are sort of taking what comes out of AI, and if you take a quick scan at it, it looks pretty good, right? Or if it's not your your deep, deep, deep area of expertise, it feels very credible and sounds very credible. So a lot of things are starting to go out now that are not appropriately adequately reviewed, and there are errors sort of going out, and and basically, you know, it's AI slop. You and I have both heard that term, right? But one of the things I thought was most interesting is some of the leaders that we're talking to appreciate and realize not only that they're sort of sending out slop from their organizations, they need to get they need to get their arms around that a little bit more. But this is kind of a system-wide problem, kind of a societal-wide problem. And as more and more AI goes out, I'm sorry, more and more AI content goes out on the internet, then these LLMs are being trained on that AI content. They're sort of retraining themselves. And we've all seen those studies where you can put the the works of Shakespeare into a model and have it recreate those exact words word for word, and then do it again. And by your eighth iteration, it's complete noise. It's complete garbage, right? It has nothing to do with Shakespeare anymore. So the danger is that AI is getting trained on AI, and this has the potential to sort of undermine the very tools that we're using. So that's a big one, and and marketing leaders sort of understand and realize that. Um, the good news is that from your own sort of from any given organization, their own sort of personal um interests are that they have really high quality content to start with. So they're starting to, we're starting to see a pullback in that content generation where that initial hero content, that initial, say, white paper that you're building a campaign around is created kind of end-to-end by humans. And then you can take that and you can atomize it out and you can do localizations and translations or you can verticalize it, right? So those sort of secondary follow-on pieces can be AI generated or AI sort of led, whereas that initial piece is human-led. And then the other thing that I'll mention in terms of the barriers is that it also has the potential to dull the human skill set, right? Leaders are starting to recognize this. So I don't know, I'm I'm old enough, I'm I'm guessing maybe you are too, to remember when we used to drive places without the use of uh the the phone apps, right? Or without and and we use actual maps, right? And we would and we would and and for me at least, once I drove to a place, I'd remember how to get there. And I could do it again from that point forward because I had that mental mop map in my mind. And then when the phone apps showed up with the driving apps, I I can drive to someplace 12 different times. I couldn't tell you how to get there again because I'm just blindly following what the directions are. And it's it's similar with the use of AI, right? So things that sometimes if we if we turn to AI as our first point of contact for whatever task that we're doing, it gives us a good starting point, and that's great. And it makes our cognitive load lighter, and that's great. It's nice for us individually at for any given task. But over time, we sort of lose our ability to create that content or do that task sort of from the ground up, and that's a real danger. And especially with younger people sort of coming in uh into the workforce and and the the junior people starting to come into these organizations, AI is starting to do these jobs. We've all seen and read this, and the study showed that as well. Where you know the people I talk to are seeing this happening, and that really sort of um it runs the risk of sort of hollowing out and undermining those senior people who are gonna sort of come up later. So, some things we need to think about as we use this great tool, and it does make our lives better, but there's some risks, and there's some things we're gonna need to adjust to.

SPEAKER_00 18:20

Wow, such great points. I think what I'm hyper focused, hyper aware of lately is I I know immediately, almost always when I'm reading AI written content. I mean, there's like a few dozen tells that just give it away. And you're seeing this content, and it you you begin to kind of glaze over once you realize it's AI generated. And this is coming from executives uh on posts and LinkedIn articles and other other articles, and um it's becoming off-putting. The same with imagery. I mean, uh, you can create beautiful imagery and graphics and uh without being a graphic designer, but you can immediately tell. In fact, the the social platforms label it as AI generated automatically now. So we it may be that going back to real human writing and and human-generated imagery will be a differentiator now. Uh labeled as such.

SPEAKER_01 19:18

100%, yeah. And the the folks I was talking to are seeing that. That is a different year. I think you're it's an interesting point that you raise about imagery. One of the folks that um one of the executives I spoke with um does print advertising and it's actually consumer-oriented print advertising, and they did experiment one time for one campaign in having some AI-generated in there, and they got such backlash from their market, um, they they pulled back on that. And in fact, what they're seeing is that even when they have real photography, real photo shoots, people are coming back on social media and saying, oh, that looks too good. That's up to the AI generated, you know, nothing, you know, no, no, nothing looks, nothing looks that good. And so they're all they almost have to like put flaws and sort of you know, wrinkles into their imagery because uh people just don't know whether to believe that things, whether something is real or not anymore. It's a it's just it's a system-wide issue that we're gonna have to deal with.

SPEAKER_00 20:18

Um they have to bring back the old Polaroid cameras, you know, they developed as as you printed them and you kind of let them drive whatever that was, and the it was the real photo. Remember those? Those are pretty surprising, interesting findings. Any anything else on the surprise side, the non-intuitive, counterintuitive side of your research?

SPEAKER_01 20:38

I think a couple of things were interesting to us as or to me as we sort of looked at it. So, you know, one is kind of the um emergence of agentic AI, right? So that was that's still early days, and the uh, you know, there you see a lot of buzz, you hear a lot of buzz around that, and a lot of people are talking about it. Um, it's been around for about a year or so now, but when it comes to actually applying applying agents in marketing organizations for specific tasks, they're still figuring it out. So there's a lot of teams that are going through trainings and doing hackathons to figure out how we can introduce agents into what we're doing today. And there's a lot of experimentation, a lot of things are going well, and a lot of things are they're still sort of figuring out. So that's early, early days. That was kind of an interesting to me. Um, one of the things that was also interesting to me was that um generative engine optimization, GEO, is really starting to um come into its prime and how quickly that has actually happened. So almost every organization we spoke with is either experimenting with or has actually started to use GEO to surface its content uh to the LLMs, right? So and in fact, the the companies that are starting to track this now have started to see a fall off in their use of SEM and SEO. So the the traffic that's coming in through uh search engines is starting to dip by 10, 15, 20% in some cases. And they see that all going to LLMs now. So buyers, customers, whether they're consumers or businesses, are starting to do a lot of research about brands and companies and products using the LLMs, bypassing the web entirely and then, or bypassing web search at any rate, entirely, doing a lot of initial sort of research there, and then going and finishing their research on companies' websites. So if you're not really focused on GEO today, then you know you really should sort of jump on that bandwagon. And I'm I'm guessing most of your listeners are at least experimenting. With that, but um, but that's something that's moving very, very rapidly. And then the other thing that's kind of related to that that I thought was really cool, we're we're I I call it machine engine optimization. So one of the things that some of the really um early, early adopters are thinking about is that not only are humans going to be going out and doing research about products and technologies and and and offerings and services and you know, sort of as a buyer, but now they're going to have agents go out and do that research for them, right? So buyers are starting to rely on agents to go out and do this research. So as you optimize your website, as you optimize your GEO, your web presence, your online presence, not only do you have to optimize it for human consumption and human eyes, but you have to start to optimize it now for agentic eyes. And what that exactly that means and exactly how we're gonna go about doing that, nobody seems to really totally know yet. We haven't completely cracked that nut. That's probably one of the things that's gonna be a big topic over the next 12 to 18 months, but that's one of the interesting early things to come out of the study, for me at least.

SPEAKER_00 23:45

Yeah, no, really interesting. And it starts, I think, with long-form content like we're creating now, uh, content that will go out on all the platforms from X to LinkedIn to YouTube and Facebook and beyond, and get indexed and uh transcribed and distributed and all kinds of platforms. Uh, and the fact that we're talking uh with a great degree of expertise and authority will get picked up uh by the LLM. So more of this, I think, is key. Real conversations with real people, really important. Um but so your work was really focused on you know who's who of the tech industry, tech marketing space, blue chip brands, you mentioned NetApp and many others. What about other industries, companies maybe not in in tech or traditional tech? Uh are are the are the tech folks ahead of the curve and others just catching up, or what are some of the lessons there for the rest of us?

SPEAKER_01 24:45

Yeah, I think that's a great question. I think that's a great point. I um we did mostly talk with tech companies, of course. And um, so anecdotally though, but I I do believe it seems, yeah, it seems pretty clear that the tech companies are the ones at the leading edge of this. So we've done a lot of work with other companies and other industries, accountant consulting, and um tech is the one that's kind of at the leading edge, which is not surprising, right? We've seen this with other organizations, other technologies, other sort of waves, the with the cloud computing, you know, whatever it is, uh mobile, you know, et cetera. Um, but yeah, so so the so if you're in tech, you are at that leading edge. Um what I do think, though, is very interesting is um this born in AI that I sort of touched on a little bit earlier, right? So uh while tech seems to be ahead of the curve in general, these born in AI companies that are just showing up in the last couple of years are even further ahead of the curve. And I have a couple more statistics I can share with you. So um I talked a little bit about the productivity claims earlier of the born in AI companies there, you know, seeing 100% to 200% increase in productivity compared to 20, 30% for legacy companies. Um, the born and AI companies have tools sort of proliferated, proliferated throughout their tech stack. They're more likely to use AI native tools as well. Um, they're sort of less likely to rely exclusively on the existing sort of Martex tool tools and the um AI capabilities that come with them. Um, one thing that was very interesting, the board and AI companies are telling us that 72% of their AI use is customer facing as opposed to internally facing, as opposed to legacy companies where that's less than half. So about 45% of legacy companies uh AI use is customer facing. Most of it is internally facing for writing meeting notes or you know, doing internal analysis and things like that. And then one interesting thing as well with the born and AI companies, they don't have any training or adoption strategy at all. They're just expecting that the people they hire, the people already on staff, just know how to do this stuff. This is just in the ether, just just part of the you know, part of the DNA, right, of being a marketer. Whereas the legacy companies are scrambling to catch up and they're training their internal staff and they're putting these OKRs in place and they're telling their teams you need to go out and start to use these tools. And it's true that a lot of a lot of the marketers at some of these legacy companies haven't used them in the past and are not as familiar with them and do need to sort of come up to speed. Um, so those are the companies who are sort of at the bleeding, bleeding edge is these companies that are being founded uh today.

SPEAKER_00 27:27

Interesting. And if you're one of those companies or leaders who feels like they're behind on AI or being left behind, what's next? How do they get up to speed without uh you know creating a uh you know radical transformation project or spending overspending on tools and apps? What's the a good first step?

SPEAKER_01 27:48

Yeah. Um I mean, so for sure, you know, get up to speed on the tools and the training. One of the interesting things is kind of sort of get your arms around this proliferation of tools, right? So we've seen this uh it really sort of explosion. There's a lot of AI capability in your existing tools. There's also a lot of tools that are showing up. And there's just, there's, I mean, hundreds and hundreds of of AI tools out there now. And organizations sort of their heads are swimming a little bit. So I think we're gonna see that sort of, I think we're gonna see that pendulum kind of swing back a little bit. We're gonna see more consolidation of tools within the tool set. We're gonna see more people, the traditional tool vendors, I think, are gonna be the ones who are gonna end up sort of continuing to emerge if they can, you know, adopt AI well well into their, if they can continue their adoption of AI into their platforms, which most of them have, um they're gonna sort of, you know, the ship's gonna sort of write itself a little bit. But some of these new tools will probably um will probably sort of find a place. Um, I mentioned the GEO and the MEO, right? So you definitely need to get on top of uh generative engine adoption and or generative engine optimization and machine engine optimization. Um, if you're not there yet, you need to do that. Um, you know, the skill requirements are going to be different going forward. So in the past, you've had to be good at uh analytics and you know, to get a junior sort of marketing job, um, some of the tools, some of you know, uh maybe content development, creative, right? Now there's a little bit less of an onus on human creativity and a little bit more on the ability to sort of manage and work with these tools and understand what's the difference between what's good and what's not good. And that requires more expertise, that requires more seniority. So again, this is this challenge where uh AI is kind of hollowing out these entry-level jobs. And today, most of the sort of skills that are required in these marketing organizations are the more senior talent, people who can tell the difference between what good looks like and what bad looks like. But we're gonna have this challenge in three to five years' time where as we have fewer junior people sort of working their way up the funnel, um, we may be in a little bit of a crisis where where that having that human skill and that human talent is really gonna matter.

SPEAKER_00 30:06

Right, really well said. Interesting stuff. Just to wrap it up here, tell us a little bit about your work and how you're helping clients lead the charge on these uh transformational uh changes.

SPEAKER_01 30:18

Thanks, Evan. Yeah, we actually do have uh a practice area where we work with marketing organizations to help them adopt AI and sort of use it uh to its optimum within their organization. So would love to sort of, you know, anybody who's feeling a little bit lost, uh needs a little bit of extra help, you know, we'd certainly love to help them with that. And some of the things that we do recommend when we do work with these organizations, we do kind of an end-to-end audit, we take a look at where they're using it, where they're not, where they where there's gaps, where there's you know, sort of uh areas of opportunity, and we sort of work with them on a plan to sort of develop that. But we do recommend that people do embrace AI across the organization. It's it's it's not a flash in the pan, it's not gonna go away. Um, if you're of a certain age, just as I am, you know, you may be an older dog, um kind of you're gonna have to learn these new tricks, or you're gonna have to have other people in your organization who do know how to use this who are gonna help you with that. So do embrace it, you know, sort of understand this is the way that work is done today. Um, you know, we're all gonna sort of use it. Um focus on that AI-driven discovery, that GEO, AEO, that machine engine optimization. That's definitely the wave of the future, and that's going to be very important over the next 12 to 18 months. Organizations that don't have their best foot forward in terms of generative engine optimization will lose opportunity compared to their peers, and you will be at a competitive disadvantage. So that's gonna be a primary focus right now for marketers today. Um, invest beyond just the productivity gain. So uh everybody's sort of thinking about the fact that, okay, I think I can do the same job with fewer people. Yeah, you can, you know, agents are gonna help you do that. But you if you use it well, you can also break into new markets. You can understand your customers' needs better, you can move faster, you can get to market faster with your offerings. So there's other ways where you can use it as a more of a strategic advantage and not simply as a productivity enhancer. Um, so think about the ways that you can sort of use it strategically for your business. I mentioned prioritizing skills and judgment over tools. You know, don't just blindly invest in tools and assume that what you're gonna get out of it is correct or good or better. Um, invest in that human skill and that human talent because that combination of the AI productivity enhancement plus that human talent, that's where one plus one equals three. Um, and then don't overuse the technology. We talked about this a little bit earlier. Don't just automatically assume that what's coming out of AI is a correct or appropriate or the best foot forward. Um, it's going to there's a very good chance it's undifferentiated compared to what your competitors are putting out there. And so really rely on that human as that sort of initial hero sort of piece of content or that work sort of, and then use AI more for the derivative derivatives around that. And that's really the winning formula. And yeah, like I said, get help where you need it. We we're here to help, but there's a lot of other ways that you can sort of get help. Um, you don't have to only rely on internal teams and talent to get you where you need to be.

SPEAKER_00 33:14

Well, such great insight, Tuch, great advice. Thanks for joining, Ed. It's been quite a tour to force of AI and marketing.

SPEAKER_01 33:21

Thank you, Evan. It's been a pleasure.

SPEAKER_00 33:22

Thank you. And thanks everyone for listening, watching, sharing, please, this episode. And be sure to check out our TV show, uh techimpact.tv on Bloomberg Television and Fox Business. Thanks, everyone. Thanks, Ed. Take care, Evan.