[The Marketing AI Show: Episode 6] 10 Key Findings from the State of Marketing AI Report
The Marketing AI Show—the podcast that helps businesses grow smarter by making artificial intelligence approachable and actionable—is back with another episode.
Click here to listen to the first six episodes of the podcast on your favorite podcast app. Keep reading for highlights and video from our latest release.
Episode 6: Special Edition Dissects Key Report Findings
We are entering the age of intelligent automation. What does it mean for marketers? And how will AI impact brands? How will our jobs evolve?
These are just a few of the questions we sought to answer in the 2021 State of Marketing AI Report.We teamed up with Drift in fall 2020 to gain unparalleled insights into the awareness, understanding and adoption of AI throughout the marketing industry.
What we learned is that the industry is on the cusp of digital transformation. In this episode Paul Roetzer, Founder and CEO, Marketing AI Institute, and Mike Kaput, Chief Content Officer, Marketing AI Institute, dive deep into 10 key findings from the newly released research.
Watch the whole interview to hear more about:
- Were there any surprises in the results?
- What does it all mean for the future of the industry?
- What does it mean for your career?
Kaput noted: “It really seems like from the data that people understand that they need to get a handle on artificial intelligence in marketing, but all the supporting data points would seem to imply that they are just scratching the surface.”
Listen to the episode now.
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Read the Full Interview Transcription
Disclaimer: This transcription was written by AI, thanks to Descript.
Paul Roetzer : [00:00:00] Welcome to a special edition of The Marketing AI Show. In this episode, we explore key findings from the 2021 State of Marketing AI Report. Marketing AI Institute, and Drift teamed up in fall 2020 to gain unparalleled insights into the awareness, understanding and adoption of AI throughout the marketing industry.
[00:00:23] Using marketing AI Institute's AI Score for Marketers, which is a Free assessment tool that we created back in 2018. Um, it let marketers go through and answer 13 survey questions and then rate the value of 49 sample use cases more than 400 marketers answered portions of the survey. Uh, and throughout the report, we kind of indicate how many people answered each question and 235 marketers completed all questions and use case ratings.
[00:00:49] So, what did we learn? Were there any surprises in the results and what does it all mean to the industry and to you and your career? Uh, let's have a conversation. So I'm joined today [00:01:00] by Mike Kaput, who is our chief content officer here at Marketing AI Institute. And who has written hundreds of articles about marketing AI over the last five years. Welcome, Mike.
[00:01:10] Mike Kaput: Thanks for having me.
[00:01:12] Paul Roetzer: All right, Mike. So correct me if I'm wrong, our kind of mutual origin story for AI started back in 2014. Um, so what happened was in 2011, I wrote The Marketing Agency Blueprint.
[00:01:25] Um, and then shortly after started kind of my fascination with artificial intelligence, Watson had won on jeopardy. I started trying to figure out, what is this technology? Could it be applied to marketing strategy, budget allocation, um, personalization prediction, like, could it be done? And so I spent a year or two kind of researching it, and then I wrote The Marketing Performance Blueprint in 2014.
[00:01:47] And that's when you stepped in and helped me with some of the research for the AI section of that book, where we started theorizing. What was possible, does that sound correct to you?
[00:01:57] Mike Kaput : Yeah, absolutely. Yeah. I think the book is when you had been looking into AI and related technologies for several years and the book was when we kind of really started collaborating on discussing, researching theorizing.
[00:02:12] Like you said, what this impact, what this technology could do to our business.
[00:02:18] Paul Roetzer: And I think there was a section in the book because at the time Watson was really the only, um, player in the game. There wasn't much AI being invested in and within marketing there might've been some companies starting to do some things, but they weren't talking about it.
[00:02:30] And so we theorize, like what, what happens when Watson comes to marketing? What, if you could build an intelligence engine? What, if you could have all the inputs of everything as a marketer, you were doing all the money. Being spent, the ads being run. The trade shows. You're telling me if everything were all these inputs came in and you had all the historical data, but everything you'd ever done and you could set a goal.
[00:02:51] Could the machine predict what you should do next. That was kinda my baby. That was my vision for like, well, what if AI could do all this? [00:03:00] And so that's kind of what we wrote into the, the second book was this more theory theory, because it wasn't happening at the time. And so, you know, that kind of got you interested, but your background was as a writer, right?
[00:03:10] Like where did your, and maybe like how you kind of got involved with the agency and the Institute as a writing, as a writer by trade.
[00:03:18] Mike Kaput: Yeah, absolutely. So I started my career actually as a journalist, mostly freelancing worked for a few years at a couple of different magazines. Nothing like a war correspondent, but more just kind of general lifestyle magazine and newspaper writing and business writing.
[00:03:38] Um, so. I kind of made the leap to the agency based on the back of my ability to create compelling stories, compelling content, which translated really well into kind of what I'd call kind of like the content marketing revolution happening at the time. And then through working at the agency had the [00:04:00] really strong content foundation and then layered on all sorts of other kind of marketing strategy skills, marketing tech skills became very competent with marketing automation, software like HubSpot, and I think the tech piece plus content is kind of how I ended up getting involved with the Institute. You know, I've been a business reporter before, so I was always interested in new technology trends and reporting on those.
[00:04:27] And it just seemed a natural fit. I had heard of AI, but didn't really know a huge amount about it until you and I started talking about, okay, how can we start combining this kind of technology with the marketing and content we already do and just make the whole thing a lot more effective and efficient.
[00:04:46] Paul Roetzer: And I, again, if I remember correctly, the years start to run together, but so 2014, I write the second book. It comes out sometime, I don't know, fall. I think 2014, 2015, I go on the speaking tour. [00:05:00] So I, you know, I start talking about AI. And so out of, out of the 50,000 word manuscript, AI was maybe a thousand words of it.
[00:05:06] Like it wasn't, this is not a book about AI by, by any means, but there's, there's Easter eggs in there. Like there was the seeds of what I thought could happen in the industry. And so 2015, I did, I think the opening keynote at the MarTech Conference with Scott Brinker. And again, AI was sort of the back-end of the story, but that was, it seemed to capture the attention of some people. So I remember like Chris Penn, I think was there. And Chris like latched onto that because Chris was working on that stuff with IBM at the time, he was starting to kind of move in that direction too. And so then I just, like, that became the thing I would get invited to speak about was AI.
[00:05:44] And so the second book tour, just sort of like diverted into artificial intelligence. And the more I was out talking to people about it, the more I realized, like we were at such an early stage that nobody knew what this stuff was. And so I was debating on like, what should we build a company? Should [00:06:00] we build a software product? Bring this intelligence engine to life and, you know, kind of back and forth, nothing happened at an agency to run. And then I think it was, you came into my office during an office hours, sometime in early 2016, it was like, what are we going to do with that AI thing? Like that was kind of fun to research.
[00:06:17] Seems like a really big deal. Are we going to do anything with it? And, uh, you know, I think from there, it kind of like, I was like, yeah, you know, I, I just got back from this crazy talk and this opportunity was emerging. And so we're just kind of like trying to figure all this out and then I'm out cutting my grass one day.
[00:06:31] I was like, you know what, we're just going to, like, we just need to build an Institute, we just start a blog and start writing about this and we'll figure it out. So that was what we did. You and I started writing about AI sometime in late 2016 under the domain Marketing AI Institute. And that was, and we started tracking vendors, right.
[00:06:47] I mean, that's pretty much how it started and the deal was if other people care, like we do find this fascinating and maybe there's a business in it some somewhere somehow. Right. All right. So that's kind of how we got here [00:07:00] so that we start reading all the reports. So McKinsey, PWC, Deloitte, starting in those years, like everybody's putting out these reports saying this is going to change the world.
[00:07:09] It's the new electricity. Like everything is going to be powered by AI. And here we are in the marketing industry. We're like, why isn't anybody talking about it? Then this doesn't make any sense. And I go out and give talks to rooms of 500 people and. My perception is like, nobody knows what it is that this is the first time they're ever hearing about it.
[00:07:27] Or if they've heard about it, they couldn't tell you what it is. They couldn't give you a definition. And so, you know, I think early on, we just looked at as like, people have no clue. Like there isn't even demand for the knowledge because the topic is so abstract. And so we would read these reports and like, I would just, every time a new one come out, I would absorb it and be like, okay, This is great, but they're saying like it's already scaling and businesses and why aren't we seeing that?
[00:07:51] Like why aren't marketers even piloting it? And so when we created the Institute, one of the first visions was to create this tool called AI Score. And the idea [00:08:00] was to make AI more approachable to people by showing them a bunch of specific use cases and just saying, Hey, if you could intelligently automate this thing, if you could take, you know, a task, you usually do that's human powered and use machines to help you do it faster, which is the whole idea of intelligent automation.
[00:08:18] It's automation, plus AI, not just human powered automation, like, would that be valuable to you and what would be the most valuable use cases? And so for years we've been collecting that data. So we launched that. I think it was in 2018. Mike, is that sound right to you? And so we'd, you know, going into last year, we, I think we'd had like eight or 900 people had taken AI score and so had all this interesting proprietary data on what use cases, people valued. And then we just got talking with Drift, which is one of our big corporate partners at, at marketing Institute and Mark Kilens over at Drift who, you know, Mark and I go back years together and he's had a fascination with AI as well. Um, And we got talking about like, well, what we should [00:09:00] do a report on this.
[00:09:01] We should find out where we're really at, because all these awesome reports from all the big analyst firms and consulting firms, they don't really drill into where are we in marketing and as a marketing manager, as a VP of marketing as a CMO, or even as just a, someone who's just getting started in your career as a student, There just, wasn't a place to turn and say, where, where are we?
[00:09:20] And so that was the idea behind the State of Marketing. AI is like with drift, could we come together and find out where we're really at? Um, and so that's what we did. So, you know, again, Mike, how many articles do you think you've written? 500, 600,
[00:09:37] Mike Kaput: probably 500 at this point.
[00:09:39] Paul Roetzer: Yeah. And the articles are, you know, we do a lot about, um, use cases.
[00:09:43] We do a lot about specific categories of marketing. Like some of the most popular might be like what social media content marketing.
[00:09:50] Mike Kaput: Yeah. AI for social media, AI for advertising content marketing, these kinds of broad categories that people have. Both roles and formal job titles around people [00:10:00] are really, really interested in how they can start thinking about their own discipline and how AI impacts it.
[00:10:07] Paul Roetzer: Yeah. And that's our approach all along is how do we make AI approachable and accessible? Um, uh, you know, make it more understandable and make it actionable. That'd be like, he's like, let's not talk at a high level about the geeky, highly technical stuff about the different machine learning models and how to build them.
[00:10:23] It's like, no, we're talking about how do you find smarter technology to be better at your job? It's PR pretty much what it comes down to. And so it is a lot of demystifying AI. That's basically been our mission. I think we've probably written seven or 800 articles total on the Institute. I've probably done a hundred to 120 webinars and keynotes on the topic.
[00:10:42] So it's just like, We felt like we had a pretty good idea of where the industry really was because we've talked to so many people we've profiled over a hundred of these vendors. We ask them all the same nine questions. How do you use AI? What's the opportunity? You know, what's the limitations, what are, what are the barriers to entry for people if they buy AI [00:11:00] products like trying to get this really clear picture.
[00:11:03] But again, it's like this sort of subjective viewpoint from our. Uh, work in the area, our experience, and we wanted to go outside of that. And so that's really what the report became. And so in fall of 2020, we did the research as I kind of said in the lead in here. Um, and what we want to do today is just talk about some of the key findings.
[00:11:22] You can download the full report at state of marketing, ai.com. Um, Well, we're going to do today is go through kind of the 10 key findings and just Mike and I kind of riff on it, like give, give some context to what we're seeing, if, if it seems to align with what we're hearing in the industry, um, and go from there.
[00:11:39] Sound good, Mike.
[00:11:40] Mike Kaput: Sounds great.
[00:11:41]Paul Roetzer: All right. Um, so upfront, as I mentioned, this idea of intelligent automation. So the report talks about this whole idea that we're entering this age of intelligent automation. And so it is important to, again, revisit the idea that marketing today that all of us have come up with is human powered.
[00:11:57] You write the rules, you, you figure out when to send the email. You. Figure out what the subject line is going to be. You figure out the CTS, um, you figure out the workflows, like you write all the rules. Some software developer created a piece of software that enables you to do your job, but you have to actually figure how to use the software and it doesn't get any better unless you make it better unless you go learn.
[00:12:19] So intelligent automation is this idea of taking these repetitive tasks. Often data-driven repetitive tasks and using machines. To help you do them better. And those machines get smarter because they learn as new data emerges. And so in essence, what intelligent automation does is it gives you a superpower.
[00:12:36] It gives you the ability to do things at a superhuman level. And so to me, it's just still crazy that marketers aren't. Proactively trying to find that, to understand it, it is a competitive advantage. Um, so that's at a high level. And I think the key takeaway when Mike and I kind of stepped back again, 13 survey questions, 49 use cases, and then a bunch of profile data on people that you can kind of cross [00:13:00] reference and find correlations in.
[00:13:01]We try to find, like, what is the big story here? What is the main narrative? And what we settled on is that marketers see an intelligent, automated future in marketing AI, but understanding and adoption are slow to take hold that, that it seems like maybe they're a little further along than I thought they were.
[00:13:20] Um, and Mike, I don't, you, you can agree to disagree, but like, I didn't think that they actually had these levels of understanding, but the data tells us that maybe do. Um, but it's just not advancing. And so that was the key takeaway. Right. Mike, do you have any other thoughts on that?
[00:13:36] Mike Kaput: Yeah, I think that I would agree a hundred percent with that. It really seems like from the data that people understand that they need to get a handle on artificial intelligence in marketing, but all the supporting data points would seem to imply, and we'll get into all of these, that they are just scratching the surface and need quite a bit of assistance and guidance both from, you know, perhaps internally, but also externally from vendors, people like Marketing AI Institute educators.
[00:14:09] Paul Roetzer: All right. So let's, let's just jump in. So again, we've got 10 findings for this podcast. We're just going to kind of talk through each of these, add a little context and you can again, grab the report whenever you want and kind of dive in yourself. So the first finding the majority of marketers know AI is very important or critical to their success this year. Now, the question we asked here was how important is AI to the success of your marketing over the next 12 months? So again, we're, we're trying to get a gauge. Not only do they, do they understand, but do they actually think it really matters? And in this case, um, it, it said that the majority are 52% said it was very important or critically important.
[00:14:48] So 37% said very important and another 15% said critically important. Okay. I, I don't. I mean, there wasn't really anything on that one that I found surprising. Um, [00:15:00] did anything jump out at you, Mike? I'm not a huge amount. I will say that I thought with this and this we'll get into the data. We're about to look at.
[00:15:09] Um, I was a little surprised because I wanted to immediately say, but then why aren't you doing anything? Yeah, I agree. I mean, definitely there was every question is like, man, I could run 10 pivot tables off of this. Like there's so many correlations. I want to find like, well, who's saying. What, and is the CMOs saying this?
[00:15:26] Um, yeah, and I just looking at the charts. So, uh, only 4% said not important at all that I guess that's good, but you probably wouldn't have gone all the way through this survey, if you feel that way. Um, 10% said they weren't sure. And then 34% said somewhat important. So my guess is when we do this again in 12 months, that's going to dramatically shift.
[00:15:48] I would think 70 to 80% would identify very, to critically important and far fewer be on the other end of the spec. Yeah. And I'll be honest. I would have probably expected. To [00:16:00] see more people saying, they're not sure about the impact. And so you've got almost 80, 85 plus percent here that are saying that at the very least it's going to be important, you know, in somewhat important or higher to their marketing in the next year.
[00:16:15] So that's a pretty clear question. I mean, I think it does show a really interesting trajectory for where we're going. All right. So the next one, um, so what we're trying to do with this. So the second finding is marketers believe widespread intelligent automation of the industry is inevitable in the next five years.
[00:16:33] So we tried to get creative with the questions to get truly at are people using it? Like what, what is the adoption level and where do they think it's going to go? And the idea again is to. This is like a benchmark study and then to see where this goes. So we, we asked this one in two ways. So the first was, there was a question that said, what percentage of marketing tasks that your team performs are intelligently automated to some degree [00:17:00] today.
[00:17:00] And then we said specifically, what that means is AI is applied to improve the efficiency and or performance of the task. So this would require the user to know that aI is in there somehow. so there is a, you know, understanding that, that, that is assumed that they have some idea that AI is built into it.
[00:17:18] Um, and that they have some knowledge of, you know, how much it is today. So again, what percentage of tasks today are intelligently automated to some degree? The answer is more than 70%, percent of marketers have less than a quarter of all their tasks intelligent automated to some degree today. 18% said they have not intelligently automated any tasks at all.
[00:17:43] Um, So I'll, I'll, I'll do the second part of this and we'll kind of come back and unpack this. So then the second question was the exact same format. So what percentage of marketing tasks that your team performs do you believe will be intelligent, automated to some degree in the next five years? [00:18:00] So again, we're trying to get at this, like, where are you at today?
[00:18:03] What do you think is about to happen? And this becomes a real critical question to the overall finding of. They get it, like they know it's coming. They might not know exactly what it is or how it's going to work, but they know it's coming. And so to that question around the next five years, that same majority, 77% believe that more than a quarter of all their marketing tasks will be intelligently automated to some degree in five years and 40%.
[00:18:29] Believe that more than half of all of their tasks. Well, so again, that's a lot of numbers, but let's step back and say, what does that mean? It means this month take all the things you do. And in the next five years, assume half of them a machine will be doing for you in some capacity. That's crazy. Like, and to think you might not be actually.
[00:18:51]Seeking tools or seeking understanding when 77% of you think that more than half of what you do is going to be telecheck [00:19:00] automated. So, I mean, Mike, what did, what were your thoughts when you kind of start this data coming through?
[00:19:05] Mike Kaput: Yeah, honestly, this one was a huge question for me to see these results, because I think the previous thing we just discussed about how important is AI going to be? That's a good solid leading in question, but that's still a little high level and this one brings it down to earth and says, okay, within a constrained period of time, tell me how many tasks you think are going to be automated. And the fact that in five years, people think of large, a large majority of people think that over a quarter of marketing tasks are going to be automated is just, I was pretty flabbergasted by us just because like, that's where I thought it was going. But to see that so many people are onboard and understand, this is where the future is going. I think of like, take this finding, get out of marketing and sales for a second. Yeah. Think about if we [00:20:00] went into a factory or any other, law firm. Or any other type of business. And we looked around, so there's a few hundred people in an office. And we said, wow, almost 80% of the people here think that more than a quarter of the tasks everyone is busy doing right now are going to be done by machines. You would be like in five years, within five years, this has seemed like in two decades, you would be writing articles tomorrow about the massive transformation, whatever that business or industry would be, what, what would be happening there.
[00:20:35] Paul Roetzer: So I agree. And I, I mean, so we, we said the vast majority of marketers are just getting started. Meaning like most of them aren't intelligent. I made that many things, um, But they know it's coming. And so again, like you would think adoption would be further along, but there would be more urgency to your point when you really understand what this means.
[00:20:58] Like what marketing team that [00:21:00] you know of is preparing for this, or, or like guiding their team of what their future is. If they think that half of their jobs is going to be done by machine, what do they think is going to happen? They get the other half off. Like, do they need to up-skill re-skill find a whole different role.
[00:21:14] Like. If I'm a market, I have a hundred questions just from this data point. So yeah, I, I, I thought that was a fascinating part of it.
[00:21:23] Mike Kaput: Yeah. And I think just one other point there, it's really interesting too, for people who are just starting to come into the industry, right. Or perhaps going to school for it, and that's a whole other.
[00:21:33] Conversation to have, but if you're anyone involved in trying to figure out what skills are going to be needed for the future, I mean, you figure what a degree, at least a traditional degree these days would take four years or what happens when you enter school today and you come out four years later, have you learned skills that are the non-automated wines or, I mean, there's just so many questions I have about the future of the industry from this data point.
[00:22:01] Paul Roetzer: We didn’t get into the university side and higher education within this report. But obviously, you know, you and I have a shared interest in the higher education and where it goes. And I can tell you, again, some of this is just, we've talked to a lot of deans. I've spent time consulting with some, some business schools. They're not ready. Like there, there isn't an intro to AI course that I've found like at a liberal arts college, that's just lets people learn about the basics. Like they're just not ready and they're going to be putting out students who are going to be so ill-prepared for four years from now.
[00:22:34] So I do think that that's a. Another story for another time, probably. Yeah. All right. The third key finding marketing marketers are seeking to understand AI and pilots smarter solutions. So we ask questions about AI and you. So we did ask questions specific to you as a marketer and your understanding and where you're at in your career.
[00:22:55] But then there was an AI and your organization section, and it was trying to get into [00:23:00] where is your team and where's your marketing team and where is your organization at large? And so to do this, we actually created this sort of five stages of marketing AI transformation. And this came from some consulting work that we were doing a couple of years ago, we were working with some big companies and trying to help them understand it's not just about piloting a bunch of smarter tools.
[00:23:20] You don't just go buy five AI tools and intelligently automate a bunch of stuff. It's going to fundamentally change everything within your marketing organization, how you build strategy, how you hire, what you focus pro dev on, what those people are going to do. And when they do have free time opened up, how are you going to reallocate that time?
[00:23:39] It's like, it's a fundamental shift in the way marketing is done, and nobody is thinking about that. And so we created these sort of fives stages. And these may evolve like this is like, we wanted to kind of put it out there within this survey to start gauging it. But, I'll just kind of give you context of what those five stages are.
[00:23:55] Now. Keep in mind, you may be in multiple of these stages simultaneously. This isn't a [00:24:00] chronological. You go a to B to C to D. It is like you might be at multiple stages. So. The question is which stage of marketing I transformation best describes your marketing team? Choose all that apply. So the first is researching, you're becoming aware of what AI is and why it has the potential to transform marketing talent, technology and strategy.
[00:24:21] The second stage is understanding your learning how AI works and exploring use cases and technologies. The third is piloting, prioritizing, and starting to run a limited number of quick-win pilot projects with narrowly defined use cases. The fourth is humanizing seamlessly, integrating AI or integrating AI in human capabilities and reinvesting the time and money saved from intelligent automation to listening, relationship, building creativity, culture, and communities, and the other is scaling, achieving wide scale adoption of AI.
[00:24:54] While consistently increasing efficiency and performance. So, uh, the actual orders [00:25:00] researching, understanding, piloting, scaling, and humanizing, we think of humanizing as kind of the last one. So again, um, and I know that's a lot to unpack and we'll come back and talk about these, but I wanted to give a little bit upfront context around the question that was asked here.
[00:25:13] What we found is most are in the researching phase. So 65% said that they are at the stage where they're becoming aware of AI. A majority also said they were in the understanding phase. They were actively exploring use cases in technologies. And then to my surprise, more than a third said, 34%, said they entered the piloting phase where they're actually prioritizing and starting to run a limited number of quick Lin pilot projects. So again, 65% of the researching phase, just starting to try and figure it out. 55% are moving into starting to really understand this and starting, looking at ways to apply it through use cases and technologies. And then roughly a third are starting to actually run some pilot projects.
[00:25:56] Did anything jump out to you there, Mike?
[00:25:59] Mike Kaput: Yeah, similar [00:26:00] to you. I was surprised so many people are in the piloting phase, but I think conversely, it doesn't surprise me that more people are in the researching and understanding phase, but that does jump out to me as a way to start thinking about how vendors may need to start accelerating how they help people through those phases in my mind, just because given the last two points we've discussed of how important it is to begin deploying the technology. In my mind, I'm kind of like, okay, I think it's time we need to, we need to hustle through research and understanding if we're going to get to AI, being a critical part of your marketing in the next 12 months.
[00:26:42] And especially if you expect all of this automation to happen in the next five years.
[00:26:47] Paul Roetzer: Yeah. And I, I, you know, for the vendors that are listening, this is a tough spot. I mean, there's a lot of vendors we talked to have some really. Good technology. I mean, truly building smarter solutions and they just don't know how to talk about it to [00:27:00] marketers because a lot of the people they try and sell to have no idea what it is. It's like they might feature machine learning or talk about their natural language processing capabilities or talk about some technical feature. And from every vendor I talked to they're like the market. Doesn't understand that stuff. Like they just want to talk about outcomes. And my feeling along is that that's, that's good.
[00:27:18] Like they should, you should focus on how you make their job better, improve their probability of achieving their goals. But when I'm looking at five content intelligence tools as a marketer, as a buyer, At the end of the day, I should care that one of them is smarter than the other. And I should know what that means.
[00:27:35] And so I think that as the researching understanding becomes a higher majority, hopefully vendors can start talking at a higher level to these buyers because right now I don't think the buyers are ready for the more advanced conversations around what really makes an AI powered product better. All right.
[00:27:52] The next one, some are seeing an impact from their marketing AI investments specifically in revenue acceleration. [00:28:00] So again, it's, I think it's always helpful to hear the question and some of the choices. So the question here was what outcomes is your marketing team achieving with AI today? So again, you're assuming that the people answering this are probably the ones in the piloting or scaling phases where they're actually using it or the ones who said they're intelligently automating a percentage of their tasks already. So you're, you're kind of making that assumption that these are people who are actively doing it.
[00:28:24] So there was, Oh, about 10 choices here. Um, and I'll just kind of go through in order. Well, let me give you the key finding first. So for marketers who are applying AI, accelerating revenue at 41% and getting more actionable insights from marketing data at 40% were the two most common outcomes that they're achieving across all marketers surveyed most are 89% said their marketing team's highest priority includes accelerating revenue.
[00:28:51] So that didn't surprise us there. Um, And only about 8% adopted the reduced costs. So again, the question is, what outcomes is your team achieving [00:29:00] today? The other choices here were creating personalized consumer experiences at scale, which at 38% reducing time spent on repetitive data-driven tasks, um, generating greater ROI on campaigns.
[00:29:12] Driving costs down, unlocking greater value from MarTech stack. 29% said none of the above. Like they didn't, you know, they weren't getting any value right now, which again, I actually thought that would be higher. Um, based on how many people weren't really doing what they're, um, piloting or scaling it, predicting consumer needs and behaviors with greater accuracy, increasing qualified pipeline and shortening the sales cycle.
[00:29:35] We know a ton of salespeople taking it. So it doesn't surprise me that qualified pipeline and shorter sales cycle rated lowly or low. Um, But that was, and we had 321, people answered that question. So it's a nice sample size of, of the respondents. So I don't know anything, jump out to you there, Mike.
[00:29:52] Mike Kaput: Yeah, I think it just kind of confirms what we're already seeing in the last year or so maybe longer in the marketing industry [00:30:00] of just revenue acceleration, being such a priority.
[00:30:03] I mean, it sounds obvious to say that, but I would argue that it's only in the last year or two people are really. Talking more about that specific term. And I think, you know, unfortunately the pandemic only makes that trend even more important. Given how many traditional channels for revenue generation, lead generation have kind of been curtailed.
[00:30:26] So that doesn't surprise me. It's great to see. I like it. I think getting more actionable insights from marketing data jumped out to me as decently high, but also not surprising. I mean, I think that this is maybe some of the explanation for why people are kind of behind the curve a little bit is that people are still struggling. We see this in the client services side of our business. All the time, people are still struggling to get value from the data they've had for years, the traditionally generated data. And that data is not becoming [00:31:00] smaller. They're getting more and more of it every day. Yeah. So I think this is pretty conclusive in my mind that AI is one, this is one huge area where you can actually start getting insights from the data you've been trying to get insights from before even AI started becoming commercially available.
[00:31:18] Paul Roetzer: Right. Yeah, I agree. And I, you know, I know Drift is big on our, our sponsor of the study is big on accelerating revenue, but I think the key here is like, again, our whole point with the Institute, it's not to go buy a bunch of AI tools. Let's go buy smarter technology that actually helps you achieve your goals better.
[00:31:36] And everybody wants to accelerate revenue. So it seems really logical, but I think that's important kind of a North star for people as you start moving in and looking for AI technology. You're not looking for AI technology. You're looking for smarter solutions. You're if you're buying a marketing automation platform or an email marketing platform or a social media platform, there are companies building smarter ones that will drive costs down and accelerate your revenue and make your [00:32:00] team better.
[00:32:01] And you have to be buying the smarter technology like that. That's the whole point of all of this is to go find better tech. That's going to make you better at your job and help you grow your company smarter. All right. Number five, half of marketers are still at the beginner stage of understanding AI terminology and capabilities.
[00:32:18] So the question here was. How would you classify your understanding of AI terminology and capabilities? Um, so it says the site, some of the data points that show AI understanding and adoption are on the rise. 50% of marketers classify their understanding as beginner and another 37% identify as intermediate.
[00:32:37] So that's 87% beginner intermediate. I would argue that if we then provided a litmus test of what intermediate means. The majority of that 37% would actually beginners. And if a simple litmus test is like, give me a really simple definition of AI machine learning and deep learning, what are those three things?
[00:32:56] Are they the same? Like if you just ask that basic question, [00:33:00] there is no way in my mind that 37% of marketers could do that. I have said again, having done more than a hundred of these talks and talked with thousands of people. My guess is it's 2% that could actually say, well, yeah, here's what AI is. And machine learning is this.
[00:33:17] And here's a real, simple way to think about it. Um, without any technical terms and without Googling it, like just off the top of their head confidently, explain to their C-suite sitting in a boardroom. Yeah. Here's what it is. And here's why it matters to marketing. If more than 2% of marketers could do that, I would personally be shocked.
[00:33:34] I, I don't want you Mike, but you've talked a lot of the same people. Like I just don't think people understand it. I, I would agree. And, you know, maybe, uh, thankfully they are educating themselves a bit on those kind of core terms, but to your point, yeah. If we considered intermediate selling this technology to stakeholders and actually understanding, connecting the dots, so to speak between okay.
[00:33:58] Mike Kaput: What the technology is and [00:34:00] what it can do and what the opportunity is, I would agree 2% might even be a little hot.
[00:34:05]Paul Roetzer: It took me five years to be able to give that confidently, say the definition. And I used to have this like fear factor that I would have some machine learning engineer in the crowd as I'm up on stage, trying to educate marketers on what AI and machine learning and deep learning are.
[00:34:19] I would in those early years, just wait for the machine learning person to come up and be like, you have no idea what you're talking about because we focus so heavily on trying to simplify, trying to come up with really simple definitions. Like AI is making machines smart. They don't know anything. They have to be taught how to do human-like things like that's a really simple definition.
[00:34:39] And then you can unpack and say, what does it mean to be smart means it can learn. It means it can like do these things. Like it took me years to get enough confidence to stand on stage and say that's what it is. And then if a machine learning engineer, can't be like, no, you're wrong. You're doing the technical definition.
[00:34:55] And you're forgetting that the average human doesn't know what you're saying. We're saying the same thing. [00:35:00] I'm just saying in a way that actually makes sense to somebody. And so like, I, I just, I don't think we're there. And I think the faster we get there as an industry, the faster we can accelerate all this learning and adoption, because I just feel that's the barrier that, that in addition to what the data is telling us here, like, I feel like understanding just isn't where it needs to be in the industry.
[00:35:19] Mike Kaput: I would agree.
[00:35:20] Paul Roetzer: All right. And then, so part of that is, if you don't really understand it, like then how are you going to buy it? And so the, the sixth key finding is marketers lack confidence when evaluating AI powered marketing technology. So the question here was how would you rank your confidence evaluating AI powered marketing technology?
[00:35:40] Um, So when asked to rank it 40% chose medium, 24% chose, low 5% said no. Um, so I mean, the way we look at as simply, but th they just don't get it, like, again, put a marketer in a room with email marketing platform. That's saying they use AI to intelligently [00:36:00] automate subject writing and CTA button selection and send time optimization.
[00:36:04] All these things. And ask that marketer, what does that mean? What, what do they mean they're using AI to do that? How, how would they be doing that? Again, I two, 1% too bad. I don't know who could actually comfortably do that. Um, so to me, it's just, it's such a critical takeaway is we, we have to level up understanding, and we're not saying we all have to become machine learning geeks.
[00:36:25] I'm saying like one Oh one, two Oh one, like just a base level of what it is a competency and a confidence that you can talk to a vendor and understand what they're saying.
[00:36:38] Mike Kaput: Yeah, I would agree. And I do think that this is this data point is extremely important to kind of evaluate this lack of confidence.
[00:36:47] And also the fact that I can tell you just anecdotally from spending four plus years of answering questions from folks, you know, about AI tools and what they can do, there are a [00:37:00] lot of people that. You know, for whatever reason, asked very confident questions about AI technology and say, Oh, okay. So tell me how it can do whatever.
[00:37:10] And they're just the wrong questions too. So there's that whole gap there of, you may not even know, you're asking the wrong questions either. Yeah. And so we, we won't get into it now, but we created a marketer to machine scale. That's trying to help marketers visualize the different stages of intelligent automation, because it's not like you buy an, a product AI product and it just does everything for you.
[00:37:30] Paul Roetzer: There's no magic switch. What you're trying to do is get to like from a zero, meaning all human all the time to a level one, which is mostly human with some machine assistance. That's what most of this is going to be. You're just finding tools that do some piece of your job or your task in a smarter way.
[00:37:46] That drives efficiency for you. But again, most marketers don't know to think that way of like what stage of automation really is this and how much time and money is that actually going to save me? Um, okay. So number seven, this goes [00:38:00] back to those five stages of transformation question about where is your organization at?
[00:38:04] And so this key finding was few marketers are successfully scaling marketing in their organizations. Only 17%. In fact said they were scaling at the scaling phase. Which means wide-scale adoption of it and consistently producing results that were well beyond pilots. We did our three, four or five pilots, and it is all AI all the time within our marketing team, you know, it's infused into everything.
[00:38:26] Every problem we look at, we say, is there a smarter way to solve it? Any piece of technology we buy, we say, is there a smarter solution, smarter technology to buy? You are truly thinking about how AI can drive success of your organization. And again, only 17%. We're at that phase. And that I, I personally thought that was high.
[00:38:45] I wouldn't have guessed that I actually would have guessed that would have been the piloting phase, like 17% to me seems possible. But again, I mean, it is what it is. Um, I want to talk to those people. I want to [00:39:00] follow up with them and find out what they're doing. And I, you know, I think that's the next phase of this is really drilling into these people who are leading the way because w we ha we struggled to find those case studies.
[00:39:09] Mike and I have been looking for years to find brands were doing this and who are willing to talk about it. And it's hard. I mean, we, we had the marketing AI conference in 2019. It was one of the hardest things I did was trying to find brand marketers, CMOs VPs, who could come in and tell their story to our audience of how they're using AI.
[00:39:27] It, that they're unicorns right now. Like they're just hard to find. Well, I think that also speaks to. A larger point and you and I discussed this even earlier this morning, there is a few tweets recently from Mark Cuban talking about how AI companies that are essentially first movers or early adopters.
[00:39:48] Mike Kaput: They're able to develop this competitive advantage that isn't just necessarily temporary, it gets better and better and compounds over time. So they get an out-front by moving first, but then [00:40:00] move faster and faster to the point where it's quite hard to catch up. And I think you can start seeing some of that reflected in these kinds of data points as, yeah, this is a very, a relatively small percentage of people, but I guess as these will be the same people year in and year out, I keep saying that are moving into that scaling phase humanizing phase.
[00:40:21] And just really building.Almost an unassailable lead over other companies.
[00:40:27] Paul Roetzer: Yeah. And on the humanizing one 19%, they said they were at the phase where they're actually thinking about the implications of AI and finding ways to make their company more human as a result of it. Now that was a surprising one to me again, it's encouraging.
[00:40:39] I mean, I'm, um, I'm very encouraged by that. Now. I would love to talk to those people because, um, that's the story that isn't written yet is like, what, what happens? What is the fallout? What is the opportunity when intelligent automation. Takes over the industry and it, again, we were under the assumption for the last year or so that 80% of everything we do will be [00:41:00] intelligently automated to some degree in the next three to five years.
[00:41:02] So again, I own an agency, I own the marketing Institute. I am actively building the agency under the assumption that at least 80% of what we do. We'll be intelligently automated to some degree we're not moving fast enough. Like I see it coming, but we're not moving fast enough. And we're not even at the humanizing phase, like, what does that mean to our talent?
[00:41:20] What happens? Do we transition roles? Do we upskill people? Like how does that look? We've started training. Like we have an internal AI Academy in the pro program and we obviously have our AI Academy for marketers that we built for the general public to take courses. So we're moving, but we haven't figured out.
[00:41:39] What does this all actually mean? So I'm encouraged that there were 19% that said they're heading in that direction. Yep. Number eight. Um, I was kind of surprised by this one. So fear is not really a factor when it comes to barriers to adopting AI in marketing. Um, now just read this one says there's a common belief that fear of AI in the unknown, uh, [00:42:00] presents the workforce is an obstacle that must be overcome to achieve widespread adoption.
[00:42:04] Our research does not support this idea. In fact, the majority, uh, 56% believe AI will create more jobs than it eliminates over the next decade. Um, and when asked specifically about barriers to adoption only 16% chose fear of AI as a contributing factor. Now, again, in that, in that question. So again, what is, which of the following are our barriers to adoption?
[00:42:28] Um, there was 16 choices, so lack of education and training. By far, um, that the top. And we'll come back to that one in a minute. But when we go down the list, the bottom ones were fear of AI, uh, with 16% mistrust of AI at 15%, and then unrealistic expectations, 19% lack of governance at the bottom was 14%.
[00:42:51] Um, so yeah. Again, fear of it. And mistrust of it were very, very lowly rated and having done all the talks I've [00:43:00] done, it's almost inevitable that the first question is, is it going to take our jobs? Like my perception is that people are afraid of it. And so I again, was encouraged that maybe that's not the case, maybe at a widespread level, it doesn't really need to do with being afraid of it.
[00:43:14] It is abstract. Like, I think it's hard for people to understand. But it doesn't mean that they have this scifi perception of what it is. And that's, again, going into this study, I was under the assumption that there is this perception that it's what you see in the movies and it's scary and it's going to destroy us and take our jobs.
[00:43:31] Like, I don't know, it might be a negative way to look at it, but that's kind of what I thought had, did you have the same feeling going in?
[00:43:38] Mike Kaput: Yeah, I thought there were a number of reasons that people would rate fear of AI, like a lot higher. And I think even if. There's plenty of people are afraid of it. I thought because of kind of the Saifai implications and the hype around mat, which I don't think has really gone away too much.
[00:43:54] I mean, you still can read an article a week about things like that. So that surprised me [00:44:00] from that aspect and to your point, the employment part of it too, because that question comes up all the time is how is it going to impact my career? I wasn't going to, is it going to take my job, my role, is it gonna, you know, make my position or my business obsolete.
[00:44:13] So from that perspective to your plan, I'm encouraged here. Maybe people are moving past the fear if they had it in the first place, in meaningful numbers, and they're starting to find PR they realized based on our other data, this is here, it's real. And I anticipate in the next five years, it's going to have this effect.
[00:44:34] So. Hopefully they're being more proactive rather than afraid it would sound like. Yeah.
[00:44:40] Paul Roetzer: And I do think that, you know, we spend so much time trying to teach use cases and just make it super tangible. Like this is what it does. It's not taking your job. It's doing this, this and this. So it's like, it's been a big focus of ours is trying to make AI, not the thing you see in the movie.
[00:44:54] It's just this smarter tech that helps you do your job better that, you know, at this tactical use case level. [00:45:00] And then when you stack all those tactical use cases together, Having superpowers and being a better marketer. So yeah, I hope that that continues to be the case. That fear is just almost like off, off the list at some point.
[00:45:13] Um, okay. So number nine, though, going back to this, you know, what are the barriers? This is by far the clearest finding of the study, um, is it is the lack of education and training that is holding marketers and the industry back from adoption. And when we asked about the barriers marketers gave the resounding answer of all, it is the lack of education training as reported by 70% of respondents.
[00:45:36] Uh, to further this point when asked if their organization has any AI focused education training, only 14% said, yes, The other two top barriers were lack of awareness of AI at 46%, which is still quite a bit, I mean, you think, and then lack of resources also at 46%, but again, the Delta there's like 46% lack of awareness in the second spot, 70% lack of education and training.
[00:46:00] [00:46:00] So it goes back to the, you know, how we started this, that. Marketers see the intelligent, automated future. They get it. They, they see 40% of them think more than half of what they do is gonna be intelligently automated in the next few years, but they just don't know what to do about it. They don't have the training if you're a young professional and you're just coming out of school, you didn't learn any of this.
[00:46:21] This may be the first time you ever heard about artificial intelligence and marketing and. If you're a marketing professional, even if you've, you know, VPs CML, like there's a decent chance. You haven't done anything with this yet. And so, so, you know, I, I make sense. I was shocked by it. I mean, I, I would have never guessed any response would have been that high.
[00:46:40] Um, but I don't know. I mean, it was again to take a step back and look at the full narrative. It's like, wow, like that, that's fascinating that, that, that ends up being the answer. Yeah.
[00:46:52]Mike Kaput: Yeah. My, uh, my jaw dropped when I saw this number and once they kind of finally went through all the data, just because I knew lack of education [00:47:00] was a in training was a problem.
[00:47:01] I didn't expect it to be this high and coupled with the fact that so few people have any AI focused education and training at their organization, honestly, seems a little crazy to me because. I think of just all the important skills that, you know, we develop tracks for here at PR 20/20 and Marketing AI Institute.
[00:47:24] And I'm like, it would be insane to me to be considering, say a future role in the next year or two at an organization that does not have something even basic in place to help you navigate this change because. It seems like the question of a marketing career in the next five years is how to figure this out from an individual level in terms of, you know, I think about it, you think about it.
[00:47:51] Paul Roetzer: So like if you're a VP of marketing or a COO and you're interviewing for a role in a company, And you say, well, what what's, what's the [00:48:00] marketing organizations roadmap with AI, and if they just stare at you, they have no ears. That's a major problem. It's an opportunity for sure. Like you can be the one who can drive it, but if you're interviewing at an enterprise that doesn't have some point of view on AI in marketing and sales and some starting point of a roadmap, That's a major concern for me.
[00:48:23] And I know there are lots of them because I mean, not, not name-dropping here, but 18 months ago, I talked to a fortune 10 company, one of the biggest companies in the world, and they were going to pilot AI for the first time in marketing. And the way they did it was they found a lady in the organization who had innovate innovation in her title.
[00:48:44] And they said, could you figure this out? And she found the marketing Institute and then she called me and she said, I've been charged at this massive organization with piloting AI and marketing. I don't know where to start. I found your website. I was reading through use cases. How do I even do this? So I then did a [00:49:00] consulting call with like 10 executives from this company.
[00:49:01] He's like, well, here's what you need to think about it. 18 months ago. Top 10 organization in the world. So that's where we're at. And that was my perception is like, well, they're not doing this. And there was other companies we've consulted that were in the same boat. Then there's no way that the adoption is as widespread as some of these big reports are telling us.
[00:49:21] Mike Kaput: And I always just try to even think about this in the context of other industries. And like you would be out of your mind if you were going into, or no, I guess I'm not, I don't know everything about like programming or manufacturing, but those are much more technical and forward thinking jobs than they were five years ago.
[00:49:43] You would never walk into a programming job and someone's like, we're using, you know, we're sitting you saying like COBOL or something, like, come on. Like you would be out of your mind. You'd be like, what am I doing here? So. You don't have to be at an organization. You're trying to interview with on that says [00:50:00] we've got it all figured out, but just that complete lack to your point is really worrying to me.
[00:50:06] I think of it as an individual, that would be a huge career risk for me or what the title was, what the pay was, whatever I would be like. This is a big blind spot, and I really do need to think of, and related if you work for a marketing software company that doesn't have an AI roadmap. Get out now they're gonna be obsolete.
[00:50:25] Paul Roetzer: Like, that's the thing I've been saying for years. Like if you're in a marketing tech company and again, email social automation, CRM, whatever it is. There better be a point of view from on high of what you're doing with AI and how you're going to infuse it into everything you do as a software company in the future.
[00:50:44] Because if you're not infusing it and making it seamless within the software for your end users, don't have a plan to do that in the very near future. You will be obsoleted. Like it's not hard to build smarter tools if you have the right team in place and the right vision [00:51:00] for it. And that's, what's happening to the VC Mondays fund VC money is funding all of these startups that are coming at this and say, well, how do we just build it smarter from the ground up?
[00:51:09] How do we take down the big established software companies by just building a smarter tool? They have all this legacy human powered automation. Let's just build it from the ground up powered by machine learning and let's make it smarter. And so I just, I mean, I feel like the next five years in the marketing tech landscape, although 7,000 companies, if they don't have a roadmap for AI next 12 months, they won't be on that list in three to five years.
[00:51:31] Like there's just no way. Yep. All right. And that takes us to our 10th and final finding. And I'll just, I'll just read this one, cause this is kind of easier than summarizing. So the future is a marketer plus machine in the future is now. So the great art irony of marketing automation is that it's manual marketers write all the rules.
[00:51:50] They build the plans, produce the creative. Um, run the promotions, personalize the experiences and analyze the performance. Traditional marketing is all human all the time, [00:52:00] but the landscape has changed. Leading marketers know that in order to deliver personalization and experiences, modern buyers expect marketing must become smarter.
[00:52:09] It must become marketer plus machine a marketers do not believe AI will replace them. Rather. They see the potential to augment their knowledge and capabilities. Through the intelligent automation of data, different repetitive tasks. We have entered the age of intelligent automation. The time now for marketers is now for marketers to seek.
[00:52:28] The knowledge and resources to understand pilot and scale AI, the opportunities are endless for marketers with the will and vision to transform the industry and their careers. And I think that just summarize it. We've been, I did a talk three years ago, like marketer plus machine it's, it's kind of what we've assumed that we are entering this stage of intelligent automation and it's going to, it's going to happen really, really fast because if you look at other industries, We're 10 years behind some of these industries.
[00:52:57] There's no new AI technologies showing up in [00:53:00] AI that hasn't been done in other industries for a decade. AI isn't new, it's like 70 years old, the application of the way we're seeing it today. And what it's capable of is evolved. But AI, isn't a new idea, but it is new in marketing, but we've seen it take down.
[00:53:17] These other industries completely transformed the way they're done. And it is inevitable that it will happen in marketing and sales and people just aren't ready. And I think that's my biggest takeaway from all of this. From the whole reason we built the Institute, you have to take the next step. You have to go find.
[00:53:32] The next piece of information to like advance your career. So, uh, any reflections from you on just overall or that last finding in particular?
[00:53:40] Mike Kaput: Yeah. I, I mean, I love the simplicity of marketer plus machine, because if you believe that to be true and you say I'm a marketer, it immediately fills in the blank on the other side of the equation for you and you say, Oh shoot, I don't really know anything about the machine part.
[00:53:56] Okay. There you go. That's your beginning path. Like, you [00:54:00] know, you know, the marketing piece of this and that's great and you're clearly good at it. If you're, you know, in a role today and you're thinking about this, I had an organization think about the machine piece.
[00:54:11] Paul Roetzer: Yep. I think, and, and I, you know, just kind of rolling into the final thoughts for me, you know, the big takeaway is just be curious, explore it.
[00:54:19] You know, I did a series of answering the I, and that's how I would end. I'm just like be curious, explore. I like just, if it, if this podcast or the last thing you read or a webinar, tentative just sparks that little interest. Th this is going to transform the industry. Like nothing we've ever seen, maybe going back to the internet would be the closest equivalent we could look at.
[00:54:37] And that is not overstating that I promise you. I'm not overstating the impact. This is going to have. And, and I just encourage you. If, if you are growth minded in your career, if you want to be a next gen marketer, if you want to kind of be what the future of the industry is, if you want to help create the future of that industry, go read the next book, go listen to the next podcast, go take the next course, like just do [00:55:00] the next thing, because I promise you, if you keep down that path, you will, it will make sense to you.
[00:55:05] You will see. The opportunity as it emerges in the coming months and years that some of your peers are going to miss. What about you, Mike? What's your big kind of takeaway?
[00:55:15] Mike Kaput: Very, very related. I would say that along the lines of your own individual career, take the next step. And also this might sound counterintuitive.
[00:55:26] Don't overthink it. It's one step at a time. If you look at this and say, Oh my God, I need to transform my career. That's great. You don't have to go get a degree in data science. If you want to go for it, machine learning, go for it. I'm not going to stop you, but it's a green field space, like to the point Paul made about.
[00:55:46]The innovation officer at a fortune 10 that just got drafted to do this. Literally your one book or one little article that you write yourself, just trying to kind of put your notes down and understand this, Oh, away from that kind of next step [00:56:00] opportunity. It doesn't mean you're going to get tapped to be the AI person at some huge organization, but every place is going to need these skills.
[00:56:07] And I think all too often, it's just a human bit of human nature. We all think we need much more. Training validation certification. Those are all really important. You need to go down that path, but you can start now to moving in the right direction and you'd be surprised even you might be ahead of the curve just by joining our AI Academy or just by downloading our beginner's guide.
[00:56:33] You can be ahead of much of the pack by taking small steps.
[00:56:37] Paul Roetzer: One of the most encouraging things for me and exciting is when I do talks, um, when we're able to be together with other humans in the conference is, um, when someone connects the dots and they come up afterwards and they're like, Hey, do you think there'll be a career path for.
[00:56:53] This like a marketing AI ops role that would do X, Y, and Z. And it's like, yeah, I love it. You should [00:57:00] write that job description and take it to your boss now and say, what if I started moving into this role? And I think that's what it's going to take, like to create these career paths, they're going to be for job titles.
[00:57:10] We don't even think of right now. They're going to be for roles we don't even think of right now. And the more that. We have widespread understanding of AI in the industry. I think the faster the innovation will come, not only in technology, but, but in the, in the jobs, in the careers, like we will create these whole new roles that just don't exist today.
[00:57:28] And that's exciting to me to like, see what it'll look like in three years, five years, how the titles will change, how the job descriptions will change, how the questions that are asked of you in an interview or the questions you ask of the interviewer. Like that's exciting. And I think. That's where we're at is people we're at the beginning stages.
[00:57:44] You're not behind you. Haven't missed out. We are in the very, very early adoption phase of. Where we're going to go in an industry. And I think that's incredibly exciting for all of us. All right. So that's it. That's our 10 key findings, uh, special, thank [00:58:00] you again to Drift for. Uh, who's an incredible corporate partner of marketing Institute and the sponsor of this report, and they've been an incredible team to work with, and they're doing some really exciting things with AI.
[00:58:11] They've got lots of. Um, information coming out soon, they've got lots of products and, uh, they're one of those. That's just looking at ways to make everything. They build smarter, looking at ways to seamlessly integrate AI. So you're not buying AI, you're buying smarter tools to do the thing you already do, or to achieve revenue acceleration, wherever those goals are.
[00:58:29] And that's what you need to find. You, you need to find organizations like drift that are just. Very focused on building smarter solutions. So, uh, again, you can download the full 2021 State of Marketing AI Report at www . state of marketing AI ai.com. This has been a special edition of the Marketing AI Show.
[00:58:47] Mike, thanks for being a part of it. Always cool chat.
[00:58:51] Mike Kaput: Likewise.
[00:58:52] Paul Roetzer: We don’t get to do it as often now that we're not in person all the time, but, um, yeah, we'll do it again soon and thanks everybody for joining us, listening and watching. Until next time. See you soon.
About Sandie Young
Sandie Young started at the agency during the summer of 2012, with experience in magazine journalism and a passion for content marketing. Sandie is a graduate of Ohio University, with a Bachelor of Science from the E.W. Scripps School of Journalism. Full bio.