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"The only thing propping up Martech budgets right now is AI." — Juan
AI adoption pressure has become one of the defining pain points in marketing technology, and the numbers make the case starkly. In this Office Hours episode, Jacqueline and Juan dig into the $1.4 billion-to-$1.48-trillion explosion in AI spending from 2023 to 2025, the Gartner prediction that at least 30% of gen AI projects would be abandoned post-POC, and the uncomfortable reality driving it all: executives are demanding AI strategies from Martech teams that are still fighting foundational data and stack issues. This is the fifth in a six-part pain point series, and it may be the most urgent.
The conversation covers three interlocking dynamics: the "virus" of AI hype spreading from boardrooms to vendor positioning, the peril-versus-promise tension forcing every executive to pick a side, and new enterprise research showing that companies without a dedicated AI budget face a 60% decrease in Martech investment versus a 65% increase for those who have one. They also walk through a role-play scenario, offering practical language for Martech leaders when asked, "What's your AI strategy?" and why pushing back is often the most valuable thing you can do.
Timestamps
00:41 — Pain point five: AI adoption pressure without clear value realization
02:35 — The "I Love You" virus and the Y2K parallel — why AI hype rhymes with tech history
06:07 — The 100x spending surge and why 30% of gen AI POCs are abandoned
09:54 — AI theater in Martech: when every vendor renames itself an "agentic intelligence platform"
13:10 — Peril vs. promise: LLMs as the first marketing channel that talks back, and AI as cloud cover for layoffs
19:14 — The budget data shock: companies without an AI budget face a 60% decrease in Martech investment
22:03 — The Trojan Horse strategy: using AI budget to fix your broken stack
23:06 — Role-play: how to push back when an executive demands an "agentic AI strategy in 30 days"
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Brought to you by Hightouch, the leading composable CDP and decisioning platform trusted by brands like Domino's, Chime, and Aritzia. 90% of customers have a real use case live within their first week, delivering world-class personalization at scale. Learn more at hightouch.com/msom.
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Creators and Guests
What is Making Sense of Martech?
Unfiltered takes on the biggest shifts in marketing technology. We spotlight what matters, who's leading (or lagging), and what's next. In Martech, clarity is power — and we're here to deliver it.
00;00;04;27 - 00;00;08;01
Speaker 1
Welcome to the Making Sense of MarTech podcast. I'm Jaclyn Friedman.
00;00;08;04 - 00;00;09;22
Speaker 2
And I'm one, and those are and.
00;00;09;22 - 00;00;20;27
Speaker 1
This is office hours. And we cut through the noise and discuss the latest and greatest in the martech landscape. So we are reaching the fifth pinpoint out of six. What is it? One.
00;00;21;00 - 00;00;41;27
Speaker 2
So this is one of our favorite topics to discuss right now. Mostly because it's the season for it. Everyone's talking about this topic, which is pressure to adopt AI solutions in your marketing technology stack without a clear understanding of the value realization. Obviously, everyone is is adopting AI. Every company on the planet Earth is using AI to some degree at this point.
00;00;41;27 - 00;01;01;20
Speaker 2
Some of these major AI platforms have billions of users. There is a real challenge here, among our members and subscribers around this problem of what do you do with AI in the tech stack? But most importantly, how do you respond to executives and business leaders and teams that are saying what your AI strategy, how are you putting AI into the business?
00;01;01;23 - 00;01;09;13
Speaker 2
How's the marketing team using AI today? And without having that real sense of ROI or a direction in terms of where the value can actually come from?
00;01;09;16 - 00;01;37;09
Speaker 1
Yeah, it's, definitely something that's plaguing many a teams and or quote unquote, temporarily replacing teams until they realize it's not going to work. And so they have to come back. But I love this topic in particular, because every preceding pain point builds to this without each and every single one of those pain points being resolved. This one becomes one of the biggest issues because it scales real quick and it just means you're problem scale with it too.
00;01;37;12 - 00;01;45;20
Speaker 1
So to start us off, I know when you are prepared to take us back in time, where are we going to end with?
00;01;45;23 - 00;02;04;20
Speaker 2
Yep. So I'm going to take you back to the ten year old one Mendoza. Back in year 2000. Year 2000 was a really interesting time in tech, if you remember. There was a lot of hype and a lot of speculation around the Y2K internet bug or the challenge around the internet, all the internet computers moving to the year 2000.
00;02;04;21 - 00;02;24;11
Speaker 2
No one really knew if that would actually cause a massive upheaval and disruption in the world economy. There was a season where there was a lot of uncertainty around technology. Around that time that was just off the back of the 1998 sort of bust in the tech, community as well, where the stock market absolutely crashed and a lot of companies went, went and closed at that time.
00;02;24;12 - 00;02;32;20
Speaker 2
It sounds pretty familiar at this stage, doesn't it? I mean, we're kind of in our own little Y2K era with AI. Is AI going to destroy the world? You know, as all these things.
00;02;32;20 - 00;02;35;04
Speaker 1
Like history rhymes or something?
00;02;35;06 - 00;02;57;17
Speaker 2
Absolutely. You know, even we had, Claude, we've even just this week had AI anthropic announced that they've built a model that's so dangerous, it may destroy the entire internet. So then they're holding it back, right? There's this hyperbole and this hype and this fear mongering is at extreme levels. But in the center of that, this program called I Love You now, jacks, I'm not saying that I love you.
00;02;57;17 - 00;03;28;21
Speaker 2
You're a good friend and, you're a great colleague, but saying that I love you, I'm saying there's an app that was called I Love You. The computer virus that basically contaminated hundreds of millions of computers cause $10 billion in damage. It was made by a hacker in the Philippines that exploited a weakness within Microsoft Outlook. So back in those days, when you had outlook booted up and maybe you own your old Sony computer or your own, you know, HP, for example, outlook wouldn't show you the file extension when someone sent you a file in an email.
00;03;28;21 - 00;03;44;00
Speaker 2
So you receive an email, it wouldn't actually show you what type of file it was, if it was a PDF or whatever. So this hacker very easily created an app that when you literally said, hey, I wrote a love letter for you, you would receive the love letter. And then not thinking about it, people would download the love letter to read it.
00;03;44;03 - 00;03;59;09
Speaker 2
They download it and it would be a computer virus that would download a whole bunch of malicious crap to the computer, basically brick their laptop or their PC. But then it would also automatically send the same email out with the same attachment to everyone in their outlook address group. You know.
00;03;59;09 - 00;04;09;11
Speaker 1
It's funny that, even 26 years ago, outlook was a problem. It's never been one that's been in space.
00;04;09;14 - 00;04;31;03
Speaker 2
It's all probabilities. Go back to outlook. Absolutely. Yeah. I mean, yeah, there's there's been a lot of challenges of outlook, but that's one of the big ones that caused this massive, virus outage. A lot of companies got hurt by it. Billions and billions of dollars in damages cost. We're not dealing with a computer virus with a lens or an AI, but we are dealing with a different kind of virus.
00;04;31;10 - 00;05;01;19
Speaker 2
You know what? Maybe Elon Musk would call a mind virus, where there's been this expectation over the past, literally since 2023. I was a something that was interesting and curious, but very much isolated to the domain of academia. You know, a lot of, companies were looking at a lot of trying AI, but since 2023, there's been an expectation that I can solve so many problems, and unlock this whole new world of value, but also is extremely risky, very dangerous.
00;05;01;19 - 00;05;17;16
Speaker 2
And there's a fear, I think, among a lot of companies, that AI is going to substantially change that entire business model. And so that's the mind virus that's uploaded into literally every executive boardroom right now. Some of our partners that are in that, that some of the leading platforms that we, we ask them, hey, how's business been?
00;05;17;17 - 00;05;34;09
Speaker 2
They say, yeah, you know, you guys made pitch to the head of martech or the CMO. We put you on a pitch to the board. So literally every public company is inviting these AI businesses to talk directly to the board. That's how existential it is for most companies. And that's why I say it's a bit of a mind virus.
00;05;34;09 - 00;05;55;17
Speaker 2
It's, you know, we've it's a everyone gets the idea now that there's AI out there that it can be useful, that it's super advanced, you know, but then it's creating all these, this fear and then this opportunism that's happening in the marketplace, which is the negative consequences of such a viral product, such as ChatGPT hitting the market roughly through two and a half years ago.
00;05;55;19 - 00;06;07;16
Speaker 2
So, you know, there's that's kind of the Iloveyou virus for 20, the 2020s, basically. But Jackson, you want to talk about some of the numbers because some of these numbers are absolutely shocking. In terms of AI adoption over the past three years.
00;06;07;17 - 00;06;32;22
Speaker 1
Yeah, it really is, because I don't think anyone's really taking a step back to recognize what's changed. And when we say when just changed, it's such a crazy number. So in AI spending exploded to 1.4 billion. That is a lot of money in 2023. Not to mention today, however, that is pennies on the dollar compared to what was done in 2025.
00;06;32;22 - 00;07;06;11
Speaker 1
And it was 1.48 trillion. That's a 100 x difference in the span of two years. But really it's one year because visualizing this scale, it's it's we've entered the trough of disillusionment without a doubt. And it's also the singular largest hype cycle that's ever existed in the technology history of tracking. And it's interesting. At the end of last year, Gartner predicted at least 30% of gen AI projects were going to be abandoned after the POC because there was poor data quality sounds familiar?
00;07;06;12 - 00;07;29;26
Speaker 1
Unclear value risk controls. It cost it a lot. And let's just say every company I know who has considered one of these types of projects, they failed within one year, and it was the vendor who came to the table saying, yes, we didn't bring the value. So I'm not surprised. I'm surprised the number is only 30%. But to that end, I think we've discussed it.
00;07;29;26 - 00;07;50;24
Speaker 1
But really the sentiment that's struggling here is executives are just they feel like they have no choice. They're being told to grow at all costs. They've got shareholders, they're hitting up against macroeconomics. They're trying to figure out how to multiply. So it's not just like fear of missing out FOMO, but it's also just the commercial reality that's dictated by the stock market and investors.
00;07;50;27 - 00;07;57;00
Speaker 1
And obviously this causes a lot of problems. Where do we begin?
00;07;57;02 - 00;08;19;14
Speaker 2
Well, I want to begin with a quote from one of our members here at the MarTech Weekly, because this just keeps coming up time and time again. The amount of conversations I think we've had on the analyst side, where we sit down with a with a brand, a customer, a large enterprise and they'll say, hey, like our executive want us to deploy this AI chat bot on the customer experience side, but we don't have the data set up for that.
00;08;19;14 - 00;08;41;09
Speaker 2
Well, data AI in fact is a mess. We can't connect it. It's all over the place. You know, we're not operationally set up to build something like that. We have no risk framework to manage it in case something goes wrong. And there's a lot of this sort of, like, how do we respond to this? Because the House isn't in order, and yet the executives want to add more things onto a house that has not great foundations.
00;08;41;11 - 00;09;13;21
Speaker 2
You know, so here's here's a quote, for one of the, folks that responded to our survey, they said the biggest martech related challenge for us the next 12 months is managing the organizational change required to keep pace with rapidly evolving technology, particularly the growing expectations around AI. The pace of change driven by AI is rising expectations around automation, personalization, analytics, content generation, ensuring we adopt new technologies is a way that is in a way that is sustainable and delivers real value, rather than simply adding complexity is our biggest challenge.
00;09;13;23 - 00;09;36;12
Speaker 2
So that's the big crux here is executives have a dream. They ask the marketing technology team, the product team, the experience team to go, what are you guys doing? And then it's not good enough at the moment to say, hey, we're building our foundations, or hey, we're doing play cleansing our data, or hey, you know, we're, we're we're ripping out a platform that's not AI for something else that isn't AI because we really need it.
00;09;36;15 - 00;09;54;28
Speaker 2
You know, that doesn't fly right now. You know, even I look at AI in the grand scheme of all the vendors that that are out there in the martech landscape, you know, there's 15,000 every single vendor that was pre LMS, like pre 2023, their whole positioning is going to AI. They're not a CMS. They're an AI driven CMS.
00;09;55;00 - 00;09;59;16
Speaker 2
They're not an analytics package. They're a genetic customer intelligence platform.
00;09;59;21 - 00;10;08;00
Speaker 1
You know what I'm so sick of seeing Agent like an AI everywhere. It's it doesn't mean anything if it's used everywhere.
00;10;08;01 - 00;10;27;20
Speaker 2
We've seen some longstanding, very successful vendors change their whole name to involve the word I. Right. Or the acronym AI. You know, we're seeing this across the board, and vendors are reacting to this in one way because really good luck getting any VC money without having AI right now. It's the only thing that VCs care about. But also they're responding to that.
00;10;27;20 - 00;10;42;20
Speaker 2
They're pandering also to executives that are like, oh, you're a CDP. Oh no, no, you're not a CDP or you're a genetic customer data infrastructure. All. Okay. So that's going to help us with our story here about embedding AI technologies. And so there's this.
00;10;42;20 - 00;10;56;06
Speaker 1
Further dilutes the the naming and the categorization of martech and just continues and proliferates that issue where folks don't know what category you're talking about because they're made up and they keep remaking them.
00;10;56;09 - 00;11;19;15
Speaker 2
Absolutely. And it's just following this, following the hype and the opportunity. And look for any vendor listening that is like, okay, go for it. Like it. There's there's obviously going to be opportunities for AI experimenting and trying things. So I don't think my criticizing that. But criticizing this sort of AI theater that is happening where the executives want to present something to a shareholder or to their board when they're actually doing something with AI.
00;11;19;15 - 00;11;43;11
Speaker 2
The vendors want to do the same thing, and then who's stuck actually trying to figure this stuff out? Well, it's the people we know we love dearly is the heads of martech. It's a heads of digital to GM of technology transformation. It's these people that have to pick this up and go, right now, let's move all of the rest of our roadmap out of the way for a minute so we can prioritize this one thing that the executive wants without any clear understanding, that's going to create value for us.
00;11;43;18 - 00;12;04;14
Speaker 2
And then every vendor is also pitching to us. Hey, bolt on to this AI solution, adhere to this. And the pressure just ratchets up and up and up. And I can see why people really, really struggle because the pressure's coming from all sides. There's all this AI theater going on and it can really, really derail, what can be very, very valuable programs of work that don't include AI right now.
00;12;04;15 - 00;12;22;01
Speaker 2
So, you know, that's I think that's sort of where this pressure is coming from. But as you say, Jack, executives are feeling the pressure. They have to respond to this because, you know, we call it a bit of a cash grab at this point. But, you know, there's executive pressure is real. And it's it's good to sort of understand why they're reacting to the AI market the way that they are, for sure.
00;12;22;05 - 00;12;44;22
Speaker 1
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00;12;44;22 - 00;13;10;00
Speaker 1
See what high touch can do for you at High Touch. RT.com firms om and now back to office hours to the point of cash grab. Because of all of this irrational pressure, it's it's becoming completely unsustainable and it's it's creating a dilemma on two different components. It's a peril versus a promise. And so as it relates to payroll, it's AI is the first channel that talks back.
00;13;10;00 - 00;13;31;16
Speaker 1
It's threatening to displace traditional customer experiences, role creation, you name it. But the promise is also the irresistible allure of productivity gains and trimming the fat reducing workforces, as opposed to having a solid business plan and hiring strategy. And on top of that, it's as if you're building on sand.
00;13;31;19 - 00;13;58;06
Speaker 2
If you look at the executives, I think from our tech leaders, first thing they should really do is get a sense from the the leadership, whether or not they're dealing with risks. So the the peril of AI, you know, so this idea that for the first time, if you think about it, the first time, there's a marketing channel out there now that's driving substantial traffic to websites and apps and, you know, and influencing customer journeys and experiences and transactions.
00;13;58;09 - 00;14;16;08
Speaker 2
It's the first channel that actually talks back the LMS. I mean, there's so many other things in AI happening, but just think about just one area, LMS is the first channel actually talks back. And it's a very interesting sort of idea to say, well, okay, in this new world, but this new consumer channel, how do we react to that?
00;14;16;10 - 00;14;32;11
Speaker 2
It could actually totally displace all of the marketing work and all the investment in marketing up to this point. It could literally change that. We could be sitting in a future and not to add to the hype, but you know, we could see a future where the majority of transactions happen on an LM chatbot. It's on an A website.
00;14;32;11 - 00;14;53;26
Speaker 2
So on an app anymore, it's on an, an aggregator like Amazon. So for a lot of retailers, especially for media companies right now, retailers, even finance companies, banks, things like that, health care is also a massive issue here as well, because lemons are not, you know, not more interesting, accurate. So health care is under pressure a little bit as well because of customers receiving information that's not from a healthcare professional.
00;14;53;29 - 00;14;55;20
Speaker 2
I think one of the biggest use cases actually.
00;14;55;21 - 00;14;57;03
Speaker 1
Definitely don't do that. Okay.
00;14;57;05 - 00;15;03;11
Speaker 2
But, I think one of the biggest use cases, I think it's like the 1 or 2 biggest use case for JJ is actually therapy. You know, it.
00;15;03;11 - 00;15;03;19
Speaker 1
Is.
00;15;03;24 - 00;15;04;12
Speaker 2
Talk therapy.
00;15;04;12 - 00;15;06;21
Speaker 1
Which is it's not a good starting point.
00;15;06;23 - 00;15;33;19
Speaker 2
Yeah. I mean, I think impacts on industry. There's massive multi-billion dollar industries that sell counseling services, mental health products, you know, medication around mental health. You know so they're really industry is getting getting feeling the fear of total displacement. And yeah, it can actually impact almost every industry. And so that's like the peril, right? If you're an executive in one of these large companies, you have to think about, oh man, it's just going to totally change how we generate revenue in the future.
00;15;33;21 - 00;15;57;12
Speaker 2
Does a customer experience change dramatically? You know, there's a risks. There's a massive risks you have to deal with just to survive as a business. But then the promise, you know, is it's, you know, we kind of call it the irresistible allure of productivity gain, and the ability to, you know, we saw famously with Klarna, like all of most of this stuff, I need to hire them back, you know, say I can replace our entire customer, customer experience, customer service stack.
00;15;57;14 - 00;16;20;27
Speaker 2
You know, you have the big tech giants laying people off. We had, block recently, you know, lay off a lot of folks because of the, quote unquote, productivity gains of using AI to replace employees. Heck, we even see some HR platforms now trading. Hey, I agents as employees, you know, we have you know, so so there's this promise of, I can make us really lean, really efficient.
00;16;21;02 - 00;16;36;11
Speaker 2
We can take out a lot of stuff that we don't need. In fact, I would say a lot of, executive thinking about AI as cloud cover for layoffs, you know, because I lay off, without a doubt. Yes. Because you're you're not seeing your revenue goals. You're not saving a profitability. That's a bad story for investors, of course.
00;16;36;17 - 00;16;55;27
Speaker 2
But if you say we're letting people go because I was replacing them, that's a that's for investors. That's a positive story because it's saying that the customer, the company is becoming more more efficient. And so, there's a promise that there's a promise for commercial gain in new customer experiences, driving better conversions, you know, so there is like I think executives also are reacting to the promise.
00;16;55;27 - 00;17;21;18
Speaker 2
And in most cases in a boardroom, there's going to be discussion of both areas. But for the later you need to figure out what the tilt is, is like, okay, is it in peril or is it promise? You know, is this like a really positive thing where a company can actually drive a lot more growth with these tools, or is every executive responding to feel, you know, so getting to the sand bit, building on sand, you know, I kind of mentioned this earlier, like building, you know, a house without a foundation.
00;17;21;20 - 00;17;44;23
Speaker 2
Building on the sand is a parable, which is, you know, if you build your house on the sand, the waves will come, the sand will erode, and then your house falls down. And one of the dangers it's particularly right now. And martech leaders need to thread the needle here really carefully, is that if you're building on sense aka your data is not in a really good shape, your marketing processes are not in good shape.
00;17;44;25 - 00;18;05;25
Speaker 2
You know, you don't have clarity of the ROI of your previous marketing technology investments. If you do not have that, adding AI will only accelerate those problems. It won't solve them. Correct. And I think that's big part of this. I love you mind virus is AI can solve everything that we haven't been able to solve before. And I don't necessarily think that's real or true.
00;18;05;27 - 00;18;07;27
Speaker 1
But yeah, I think it's a pipe dream.
00;18;07;29 - 00;18;29;28
Speaker 2
Absolutely. And so we'll talk about how you can respond in a minute. When an executive asks what's your AI strategy? We'll talk about that and help give you some words and some ways to think about how to respond. But for now, taking stock. If your stack is absolutely humming, you know, we talk to brands all the time that also have amazing they've shifted to a composable architecture and it's working really well.
00;18;30;02 - 00;18;42;16
Speaker 2
They've got clarity around the ROI from all their campaigns in the stack. You know, they've they've got those things. They're like, yes, we're ready for more. Now that's a position you want to be in, not in a position of responding to hype and then adding even more things into our broken stack.
00;18;42;17 - 00;19;14;06
Speaker 1
Yep. And we're seeing this also come across with the members of the MarTech weekly as a sneak peek of some upcoming data from Keanu and the team, AI budgets are driving martech investment. As we've been discussing. However, it's interesting to see the correlation. If you do not have an AI budget, there's a 60% decrease chance of having your martech budget maintain and stay, and only 20% had that increase.
00;19;14;06 - 00;19;49;24
Speaker 1
However, if you have a dedicated AI budget, only 5% of those companies are reducing their budgets versus 65% or increasing. So it's almost to your advantage to leverage AI, even if it's just in name, because otherwise you're at a loss of your budget to not even just maintain status quo, but actually rebuild or re implement in ensure hygiene everything you can imagine with your existing platforms, which is ultimately a lot cheaper than buying new platforms.
00;19;49;27 - 00;19;59;06
Speaker 1
But if you're having to decrease your budget with what you have, you're already in a bad position to be able to clean things up and organize. Anything else you want to add there?
00;19;59;08 - 00;20;22;17
Speaker 2
Yeah, I think it's interesting. This like the stat that, you know, there's it's almost a mirror image of like if your company doesn't have an AI budget, you're facing a 60% decrease in Ma tech investing next year. If a company does have a dedicated AI budget, then you're going to have a 65% increase in your martech stack. And, and and I had a research Qian who said, so this is some early stats from our enterprise martech research.
00;20;22;17 - 00;20;45;22
Speaker 2
And basically, can you tell our head of research, on stage at my table for Melbourne, he said that the only thing that's propping up budgets for martech right now is AI. And it's really shocking, you know, if you think about it again, building on sand, you know, like, can you get a business case for just a customer data platform adjusting guys, your platform, those things are still absolutely needed, but you're more likely to get the budget you need, the things that you want.
00;20;45;22 - 00;20;55;19
Speaker 2
If you replace the word CDP, CMS custom, get your platform with something like I Agenti you know, it's just the way the world works, I guess, is that everyone wants to.
00;20;55;22 - 00;20;57;08
Speaker 1
Be double edged sword.
00;20;57;10 - 00;21;17;01
Speaker 2
Yeah. It's very it's very strange, but it's just shocking that polarity between no budgets is the decrease for companies that don't have an ad budget. They're seeing a massive decrease in their martech investment, and then they're seeing a big increase for those who use the words AI. And so so the illustration that we have is that, okay, your executive has put a big pot of money in the middle of your business.
00;21;17;03 - 00;21;38;18
Speaker 2
And this executive says, she says, okay, if you want extra budget this year, you have to say two magic letters. I if you give me that and you give me a business case that uses AI somewhere, then you get access to another 5 million, 10 million, $20 million. This year. Of course, every team, including heads of martech, are going to say those words, right?
00;21;38;18 - 00;22;03;21
Speaker 2
They're going to say, no, we're not. We don't need to. Guys, your platform. We need an identity customer experience management platform. We don't need personalization. We need AI decisioning. You know, and so it's a cash grab. And that's what's driving a lot of martech investment right now. And that's why the vendors are responding with a lot of AI terminology and verbiage, with their content and with their positioning is because the pots of money that are being put in the middle of the business, we've literally had customers.
00;22;03;21 - 00;22;26;00
Speaker 2
And this is kind of the, that we were talking about this before the episode started, Jacqueline, about this idea of a Trojan horse, you know, and, call it an energetic AI readiness project. Get $3 million in funding and use all that money to droopy database, you know, like clean up your data that's messy, or build the integrations that you need or unify your customer profile.
00;22;26;02 - 00;22;34;13
Speaker 2
Like there's a bit of this, like, you know, smoke and mirrors and a Trojan horse to go, hey, maybe you can use the AI budget to actually fix your stack.
00;22;34;16 - 00;22;49;24
Speaker 1
Exactly. And then you could actually implement the AI, and all of a sudden everyone is happy. But obviously if we're not in the the field of wanting to deceive. However, if you need a Trojan horse, it's a really good option.
00;22;49;26 - 00;23;06;19
Speaker 2
Yes. Don't deceive. However, there is a very good argument here to say that you need this budget to be ready and to set yourself up for success, and a smart executive would understand that. You know, just adding more technology will create more problems, not solve them. But, Jacqueline, I want to do a bit of a role play with you now.
00;23;06;19 - 00;23;21;04
Speaker 2
I'm going to be the executive, and I want you to kind of respond to some of the pressure I'm going to put on, okay? Because I would love to give the audience a bit of a sense of what you how you can respond to some of the pressure that's coming at you, from executives to adopt AI. Okay.
00;23;21;04 - 00;23;40;28
Speaker 2
So you ready? So I'm an executive and let's call our company, let's call it Friedman Enterprises, LLC. Okay. Friedman. Okay. So I'm the CEO and you're the head of marketing technology. We're in a boardroom, and I just came out of a meeting with the board, and I'm going to ask Jacqueline, you know, the board agrees that, we really need that agenda guy.
00;23;40;29 - 00;23;53;22
Speaker 2
Customer experience strategy. We need that, like, in the next 30 days, because we want to present it at our next investigating. Jacqueline, how where are you at with it? Are you adopting AI? What's going on? You know, tell me more.
00;23;53;24 - 00;24;17;27
Speaker 1
Yeah. The consultant in me is like, so what exists already? What are the variables that we've really done? Let's pretend we've got some of those things. We know kind of the lay of the land. We've been in the role for a while. Identify the top 5 to 10 pain points. Use cases that have been a struggle that could be further enabled with a platform of any sort, and then see if they have AI.
00;24;17;29 - 00;24;45;11
Speaker 1
So if you're looking to increase the data pipeline and integrations into your existing platforms, do you need to reverse CTA or do you want to keep having engineers versus with a reverse ETL platform, they might have some AI components or some genetic components, and all of a sudden you kind of killed two birds with one stone. And so it's really knowing what you need and actually what tools will solve it.
00;24;45;13 - 00;25;02;28
Speaker 1
And then what once it's solved, could you do with AI on top of it? But it's a very truthfully hard thing to be like, yeah, I can figure this whole thing out in 30 days because there's no actual experts as early stage. There's no actual expert on all of it.
00;25;03;00 - 00;25;25;03
Speaker 2
So, okay, you're answering that question, where's our agenda guy? Customer experience strategy. You're answering with, hey, well, what's going on in our stack right now? We need to understand that first. You're not saying how high, right? When I say jump, you say, oh, yeah, I'll get your strategy in 30 days. You're saying that. But I think the pushback is right, because as a marketing technology laid up, you represent the customer.
00;25;25;06 - 00;25;53;02
Speaker 2
At the end of the day, it's not fluffy customer experience. What is this persona, one that's not your job as a martech leader? Your job is what does a customer need? What does a business need? Customer commercial and what are the processes data, training requirements that we need to put in place to be successful? So going back to an executive saying would you identify customer experience strategy, responding with we have a customer experience strategy.
00;25;53;05 - 00;26;16;11
Speaker 2
And we've identified three key areas where I can be experimented with, experimented, not implemented for great success in ROI experiment. You know, and actually saying we found three proof of concept and one long term initiative. And that's based on the analysis that we've done, the market research we've done, and the insight and the conviction from our team that this is what will serve the customer really well.
00;26;16;13 - 00;26;34;11
Speaker 2
And this is what's going to drive us a true commercial outcome. Now, if you said that to an executive, you know, there we go. Makes sense. Logical. That's what they'll say if you say how high and go yep I'll get you the agenda guy. Customer exchange strategy in 30 days. What will happen is that you'll lose respect because you'll just be taking orders from executives, not pushing back.
00;26;34;11 - 00;26;55;02
Speaker 2
When the second thing will happen is that you will then create a lot of pressure and expectations with your team down below. So the campaign people, the data people, the analytics, all those folks that need your leadership to steer the ship, they're going to feel the pressure just as much as you will. And so if you don't have those things in place, paint that picture and go, hey, we do have a framework.
00;26;55;06 - 00;27;12;18
Speaker 2
If you don't have a framework, come and talk to us about it to around your customer experience and how you actually manage martech around that. But if you have those things in place, you can say, hey, we can start looking at AI. Maybe in 2028. Reason for that is we want to get these three major capability unlocks done first before we even consider it.
00;27;12;20 - 00;27;24;25
Speaker 2
If you go back to an executive in the news, they probably won't want to hear. However, you can say that with confidence and steer the ship because just saying how high when someone tells you to jump is never a good idea.
00;27;25;02 - 00;27;45;23
Speaker 1
Correct? And also, I like to think about this. If the questions being asked, if you removed the word AI or agent like what the ask still matter, and if the original ask is hey, how can we make x, y and z AI? It's like, okay, do we even have the first part of the sentence? Do we have everything else?
00;27;45;23 - 00;27;53;21
Speaker 1
Is it still a priority? Otherwise? And that's the real difference between, you know, adding some icing to a cake and having a good cake.
00;27;53;23 - 00;27;56;17
Speaker 2
Yeah, absolutely.
00;27;56;19 - 00;27;58;01
Speaker 1
You need the cake first.
00;27;58;03 - 00;28;19;19
Speaker 2
I like there are opportunities where I can be implemented it like low hanging fruit, low high value, low effort. In fact, we released a really great research project called, AI Agents in Enterprise, with conjunction with Treasure Data, looking at what are the most valuable like least effort that use cases. And there's plenty out there data governance is a really interesting one.
00;28;19;21 - 00;28;39;05
Speaker 2
You know, like chat with your data analytics type agents, agents around content processes could be very easily implemented as a POC because content often doesn't have all this, like heavy integration in dependencies. You can put that straight in a lot of the vendors folks work with today say, for example, Adobe, they have their own AI studio that is just for content.
00;28;39;05 - 00;28;56;09
Speaker 2
So there's ways that you can experiment and try. And you know, it's kind of managing the now and the not yet. So like the now of okay, let's try some things that only really make sense and that are low effort. And then we expect a good ROI that says the not yet, which is yeah, this is a three year transformation pace.
00;28;56;09 - 00;28;59;01
Speaker 2
You know, like this is going to take us forever to get there.
00;28;59;01 - 00;29;01;22
Speaker 1
Yeah. It's a bigger ask than you think. Yes. Yeah.
00;29;01;28 - 00;29;27;03
Speaker 2
And with every with with almost every magic and mutation for years and years being in this industry, whenever a vendor comes to implement something, they're always like, could we implement it? What's the highest ROI, lowest effort thing we can do to get confidence straightaway? Literally every single martech program starts like late. Like this. You have the POC, the experiment that gets everyone excited, but then everyone knows that this.
00;29;27;03 - 00;29;51;11
Speaker 2
That's great. We're starting them, but we're building for a much bigger, much harder, long term future, you know, and we're building for that. And so it's like the same with AI balancing the now versus non yet. Absolutely. You need to do that. However it's all couched back in you representing the customer and the capability. Once you understand that then you can go back to your executives with a strategy which is considered and disciplined.
00;29;51;11 - 00;30;15;27
Speaker 2
But if you can do us all a favor, stop saying how high when your executive say jump, push back, push back, push back as much as you possibly can. You are the bulwark of sanity. You're balancing the need for transformational leaps with the commercial needs of today as well, you know? So that's kind of I think our advice in total is you have a fantastic opportunity to push back as a marketing technology leader.
00;30;16;00 - 00;30;43;08
Speaker 1
Yeah. And I think everyone comes to a point in their career where they recognize actually sometimes the pushback is exactly what's needed, and it's actually what the executive prefers. It's not always the case. Obviously depends on the person. Be mindful. But you don't want yes, men or women in these situations. You want to actually apply what you know to what is emerging and what's coming up.
00;30;43;11 - 00;31;00;29
Speaker 1
And this is your opportunity to really use it to your advantage. And you know, why not use it to your advantage to get your data in order? So you could actually do all the things you've been wanting to do as well. And maybe I could help somewhere along the way. But it can be a further downstream project too.
00;31;01;04 - 00;31;24;08
Speaker 2
Oh yes, well, that's dealing with AI pressure. Hopefully you got some value out of this episode. You know, the main thing to consider is your company responding to risk or opportunity, promise or peril. And when you get finally when someone comes to you and asks you what is your AI strategy? Your job is to go back and say, we have not done the analysis and we're not ready for that, or we already.
00;31;24;08 - 00;31;45;02
Speaker 2
And here are the three things. And here's exactly why they make sense for our business right now. It sounds simple, very hard to do in practice, but we'll leave you with that thought as we close out this episode of Making Sense of MarTech, please check out the remaining episodes that we have as well around the big challenges. We've covered everything from data, orchestration, ROI, realization, and everything in between.
00;31;45;02 - 00;31;51;16
Speaker 2
It's been a really wonderful journey listening and responding to a lot of the challenges enterprise marketing technology leaders are facing today.
00;31;51;18 - 00;31;57;00
Speaker 1
Yes, and we've got one more in this series with personalization, and you'll hear it next week.
00;31;57;00 - 00;32;12;16
Speaker 2
If you want to stay in touch with us and learn more, you can go to our YouTube page like and follow there. We'd love to see you subscribe and add to the comments and conversation. We can also follow us on LinkedIn page Making Sense MarTech podcast. And then also, catch us in all of your podcast, streaming as well.
00;32;12;16 - 00;32;17;05
Speaker 2
Apple, Spotify and the rest of them would love to see you there. But for now, stay curious.