In this special edition episode of The Artificial Intelligence Show, we are jumping into the 2024 State of Marketing AI Report. Join us as we recap the top ten key findings from our comprehensive report.
With insights collected from almost 1,800 respondents between March and July 2024, this fourth-annual report offers a detailed look at the role of AI in marketing and business today.
We started this tradition with Drift back in 2021, and it has become an essential resource for marketing professionals looking to understand AI’s impact on their field.
Tune in to hear about significant trends, shifts in AI adoption, and key findings found in the 2024 State of Marketing AI Report. We also answer questions submitted by our webinar attendees, providing additional insights and clarifications on the report’s findings.
Whether you’re an AI enthusiast or a marketing professional intent on staying ahead of the curve, this episode is packed with information to help you navigate the evolving landscape of AI in marketing.
Listen now and stay informed with the latest trends and insights from the 2024 State of Marketing AI Report.
Listen Now
Watch the Video
Timestamps
00:00:00 — Introduction
00:07:02 — Methodology of the Report
00:09:49 — Demographics of the Report
00:18:46 — Key Findings of the Report
00:55:14 — Q&A
Links Referenced in the Show
- 2024 State of Marketing AI Report
- Introducing the 2024 Piloting AI and Scaling AI Courses; AI Mastery Membership Program; and AI Literacy for All
- State of Marketing AI – 2024 Report Findings Webinar
- Intro to AI for Marketers
- 5 Essential Steps to Scaling AI in Your Organization Webinar
- Piloting AI Course Series
- Scaling AI Course Series
- AI Mastery Membership
- MAICON
This week’s episode is brought to you by MAICON, our 5th annual Marketing AI Conference, happening in Cleveland, Sept. 10 – 12. Early bird pricing ends Friday. If you’re thinking about registering, now is the best time. The code POD200 saves $200 on all pass types.
For more information on MAICON and to register for this year’s conference, visit www.MAICON.ai.
Read the Transcription
Disclaimer: This transcription was written by AI, thanks to Descript, and has not been edited for content.
[00:00:00] Paul Roetzer: There are things I’m very worried about for the future in AI. And then there’s things that I think are just amazing and unparalleled in the possibilities we’ve had before. And so I think. We need to live in both of those realities that there are fears that we have to address and we have to, think about regularly but there’s these amazing things that it’s going to open up the possibilities for, and we can’t lose sight of that and become, restricted by our fears and not take advantage of the opportunities ahead
[00:00:25] Paul Roetzer: Welcome to the Artificial Intelligence Show, the podcast that helps your business grow smarter by making AI approachable and actionable. My name is Paul Roetzer. I’m the founder and CEO of Marketing AI Institute, and I’m your host. Each week, I’m joined by my co host. and Marketing AI Institute Chief Content Officer, Mike Kaput, as we break down all the AI news that matters and give you insights and perspectives that you can use to advance your company and your career.
[00:00:55] Paul Roetzer: Join us as we accelerate AI literacy for [00:01:00] all.
[00:01:03] Paul Roetzer: Welcome to episode 109 of the Artificial Intelligence Show. I’m your host, Paul Roetzer, along with my co host, Mike Kaput. This is a special episode. we actually didn’t even announce we were going to do this one. This is sort of like a surprise drop. we are recording this on Wednesday, August 7, but this is actually based on a state of marketing AI industry report that we released on July 25th.
[00:01:28] Paul Roetzer: And so that report was introduced, during a webinar. So Mike and I held a webinar that had nearly 2, 500 people registered for it. And then we released the report that day.
[00:01:39] Paul Roetzer: Which we’ll talk more about and explain, but it’s stateofmarketingai. com. You can go grab the report yourself. when we did the webinar, Mike and I went through the 10 key findings from the report after doing analysis of over almost 1, 800 survey respondents.
[00:01:54] Paul Roetzer: Um, but when we did that webinar, there was dozens of questions from attendees that we did not [00:02:00] get to. And so I think on the webinar, I said, maybe we’ll do a special edition and we’ll answer some of these questions. Well, that’s, That’s what we’re doing. So Mike and I talked about it and we said, all right, let’s just go ahead and record this thing.
[00:02:10] Paul Roetzer: And so we were again, recording this on Wednesday, August 7th. and this is going to be not our standard weekly format. This is going to be Mike and I going through these 10 key findings. And then we’re going to do, I don’t know, about 10, 12, 15 questions, that are sort of a summary of , the.
[00:02:27] Paul Roetzer: questions we got from attendees. Mike went through the dozens that we didn’t have time to answer and he kind of curated a list of those questions that we’re going to go through today and try and do a mostly in rapid fire format. There may be a couple we expand on a little bit, but that’s the format today.
[00:02:41] Paul Roetzer: So again, episode 109 is sort of a surprise special episode being dropped. We’re going to go through the findings of the state of marketing AI report. And so I’m going to give a quick overview of, our MAICON event, which is sort of the, today’s episode is brought to us by MAICON and then Mike’s going to dive into the report for us.[00:03:00]
[00:03:00] Paul Roetzer: So again, Marketing AI Conference. If you’re a regular listener to this show, we’ve been talking a lot about this. It’s our fifth annual Marketing AI Conference happening in Cleveland, September 10th to the 12th. We’ve got about five weeks to go before the event. There is 69 total sessions. So there’s. 10 main stage sessions, 40 plus breakouts, 16 demos, there’s mindfulness sessions, there’s lunch labs.
[00:03:24] Paul Roetzer: So, it’s just an incredible event that’s going to bring together, marketing practitioners and leaders to really explore the future of marketing. To, you know, not only get practical guidance in the applied AI track, but to, you know, But to think more strategically in the strategic AI track, thinking about talent, tech, budgets, resources, strategies, performance.
[00:03:43] Paul Roetzer: So if you’re ready to really go all in on AI, not only this year, but in your planning for 2025, you can’t miss MAICON. So it’s MAICON. AI.
[00:03:55] Paul Roetzer: You
[00:03:55] Paul Roetzer: can use promo code POD200, that’s POD200 to [00:04:00] save 200 off all past types. And you can go and get registered today to join us there. We’re expecting probably in the range of about 1, 500 attendees.
[00:04:10] Paul Roetzer: I’m not sure where we’re going to land, but
[00:04:11] Paul Roetzer: that’s what we’re expecting. um,
[00:04:12] Paul Roetzer: definitely more than a thousand attendees will be coming to Cleveland, and we would love to have you there. So again, it’s MAICON. AI to learn more and get registered today. Mike and I will both be there doing multiple presentations and running pre conference workshops.
[00:04:27] Paul Roetzer: So we would love to see you in person.
[00:04:28] Mike Kaput: All right, Paul. So like you mentioned, we’re going to dive in first to the kind of key findings and takeaways from the 2024 State of Marketing AI Report. Again, that’s at stateofmarketingai.
[00:04:44] Mike Kaput: com. So I’m going to tee up kind of what this report is, what it’s all about. Paul. We’re going to kind of go into some of the methodology, demographics, where the respondents came from, and then we’re going to dive into all the key findings and all the really juicy data we [00:05:00] got this year. So, first up, this is actually the fourth annual State of Marketing AI report we’ve done.
[00:05:07] Mike Kaput: We started doing this way back in 2021. With Drift, a conversational AI leading company, as our partner, every single year so far. So we’re super grateful to Drift for their continued support of the report. And this year,
[00:05:26] Mike Kaput: We collected responses
[00:05:27] Mike Kaput: to 25 different questions about AI and its role in marketing and business.
[00:05:33] Mike Kaput: We also asked a few questions about demographics of the survey takers, and we did all this through a survey that was put in the field from about March through July of 2024. The report itself came out July 25th, 2024. The respondents were not required to answer all the questions in order to submit There are survey responses, but we did have 1, 784 respondents complete at [00:06:00] least some of the survey, so almost 1, 800 respondents, with the vast, vast majority, about 73%, completing the entire survey.
[00:06:09] Mike Kaput: So we got some really, really good data out of the respondents this year, and that’s Just about twice as many respondents as we had in 2023. So we really expanded the sample size this year. Now, every survey, report, research, you know, has its own kind of eschewed to who is answering the question. So our survey was primarily promoted via the Marketing AI Institute website, our newsletter podcast, our webinars.
[00:06:35] Mike Kaput: So it’s definitely possible that the respondents, the answers, are going to show a predisposition to AI content and information. you would anticipate this audience may have higher awareness and adoption levels of AI than the broader industry just because they’ve been following our education typically and are really forward on the bleeding edge of artificial intelligence.
[00:06:59] Mike Kaput: [00:07:00] education, and understanding.
[00:07:02] Methodology
[00:07:02] Mike Kaput: So, Paul, I actually want to turn this last bit about the methodology here over to you because there is an important note here about the increase or decrease in percentages that we talk about and we’re going to kind of cover as part of
[00:07:16] Mike Kaput: reporting on the data here.
[00:07:18] Paul Roetzer: Yeah, you know, we, we made the choice this year to include this note up front because I think it’s such a point of confusion for not just marketers. I see this across, you know, business leaders. I see it across researchers. Like, it’s just a very common thing. So when we talk about increases in percentage, so say going from 40 percent to 44%.
[00:07:42] Paul Roetzer: That is not a 4 percent increase. So that is the common misconception I see.and honestly, like an error we see in a lot of data, especially when it’s created by marketers who don’t do this stuff for a living. So an increase from 40, from 40 percent to 44%.[00:08:00]
[00:08:00] Paul Roetzer: is
[00:08:00] Paul Roetzer: an increase of four percentage points, but it’s actually an increase of 10%.
[00:08:06] Paul Roetzer: So it’s when we talk about percentage points versus percent or percentage, it’s important to remember this distinction. And it’s also just a good reminder that if you are involved in doing research reports or just reporting on analytics and marketing or business performance, that you understand the distinction between percentage points.
[00:08:28] Paul Roetzer: and percentages. It’s very, very critical. And we will highlight in a couple areas why this becomes so essential. And again, if you’ve made this mistake, it’s okay. It’s it’s like a really common mistake. But like, let’s as an industry fix this moving forward. I told the story in the webinar that there was this Um, rather large marketing software company that, that we, worked with for years and their business intelligence dashboards, their analytics dashboards were [00:09:00] misrepresenting this exact issue.
[00:09:02] Paul Roetzer: They were considering percentage point increases to be percentage changes. And so their dashboards they were providing to tens of thousands of customers were wrong. And when I called them out on it, they didn’t fix it because they thought people were used to seeing
[00:09:18] Paul Roetzer: the
[00:09:18] Paul Roetzer: data the way it was being presented.
[00:09:20] Paul Roetzer: I said, well, that’s fine, but it’s wrong. And so again, like this isn’t, if you’ve had this issue yourself or weren’t even aware this was a thing, it’s okay. There’s a bunch of MIT people that, you know, have this wrong in software. So it’s, it’s a common thing. Let’s just resolve it. And so Mike and I will make a point of calling out the distinction as we go through this and you’ll note it.
[00:09:44] Paul Roetzer: If you download the report and read it, you’ll see this exact thing called out there.
[00:09:49] Demographics
[00:09:49] Mike Kaput: So. Before we get into all the key takeaways, let’s talk a little bit about who are these respondents. So, like I said, we asked about some [00:10:00] demographics to get a better sense of who these people are. So, this year, 64 percent of our respondents actually identified their roles as some type of director level or above role.
[00:10:13] Mike Kaput: Now, this includes titles like directors, VPs, etc. CEOs, or presidents. CMOs, and then we had an other C suite category that we also offered as an option. So that’s actually a few percentage points higher than it was last year, Paul. I think it was about 61 percent last year were director level and above.
[00:10:34] Paul Roetzer: Yeah, and that’s good. I mean, it’s definitely a concentrated effort we’ve been making at the Institute. So we have about 75, 000 contacts, subscribers, whatever you want to call them. People have opted in to the Institute through different vehicles. And so we’ve made a concentrated effort to continue to bring in more and more marketing leaders to make sure that that, Perspective is being represented not only in our research, but that those are the people that are being involved and engaged within the content we’re [00:11:00] creating, the events we’re running, the courses we’re building.
[00:11:02] Paul Roetzer: So that’s good to see that that is, you know, continuing to grow year over year. very
[00:11:17] Mike Kaput: could select
[00:11:18] Mike Kaput: more than one. So they could just tell us, here’s all the areas I’m involved in. It’s not necessarily what’s in their job title or their main role, but of those, 82 percent of respondents, the highest percentage, said they’re involved, or in some way, in content marketing. Now, that’s followed by social media marketing, where 69 of people said they’re involved in that in some way.
[00:11:40] Mike Kaput: Other top areas include email marketing, which is 67%. Analytics, which is 62%, and Advertising, which is also 62%. And again, because you can, com, you can pick multiple answers, you could have picked all of those, or some combo of those as well.
[00:11:57] Paul Roetzer: Yeah, and this is pretty [00:12:00] common, in terms of the top response. Content marketing has always been at the top now, four straight years. It was 83 percent last year, so a very slight change. And I think that mainly is a testament to content marketing being a very broad area. You know, podcasting, blogging would certainly fit under there, and most people are involved in doing those couple things.
[00:12:19] Paul Roetzer: Cheers. and when you start expanding it into like video and other ways where content
[00:12:23] Paul Roetzer: is created
[00:12:23] Paul Roetzer: or promoted, it’s kind of a catch all for a lot of marketing today. So it’s not surprising to me that that continues to be at the top of the list.
[00:12:32] Mike Kaput: So we also offered quite a few common industries that people may work in and of the answers we offered, the respondents most commonly identified as the category of marketing professional services. So we split out professional services into professional services marketing, Professional Services Other.
[00:12:52] Mike Kaput: So 29 percent of those surveyed were in professional services marketing. Now there are other common [00:13:00] industries that were represented here. These included software, they included professional services other, education, healthcare, and manufacturing, among others.
[00:13:10] Paul Roetzer: And again, this has remained pretty steady, stating the obvious, maybe, is that professional services marketing is most likely marketing agencies and consultants, and we’ve always had a very strong audience there. again, context,
[00:13:24] Paul Roetzer: if people aren’t familiar, I owned a marketing agency, PR 2020, for 16 years, sold it in 2021. But we were HubSpot’s first agency back in 2007, and my first book was the Marketing Agency Blueprint, and that’s sold 18 to 20, 000 copies worldwide. So we have always had a very strong marketing agency presence and following, so it’s not really a surprise that the Institute audience has a strong agency following as well.
[00:13:51] Mike Kaput: So we also asked if a respondent’s company was Business to Business, B2B, or Business to Consumer, [00:14:00] B2C.
[00:14:00] Mike Kaput: 51 percent said that they are exclusively in B2B, 37 percent said they are in both B2B and B2C, and 10 percent said they are exclusively B2C. So, given how that kind of overlaps, 88 percent either work exclusively or partially in B2B, while 47 percent work exclusively or partially in B2C.
[00:14:26] Paul Roetzer: Yeah, not much change here either, just a two percentage point shift. So exclusively B2B was 53 percent in 2023, so that went down to 51%. And then both, those numbers just basically moved over to the both category, . So it’s a, it’s a nice balance. I mean, it is, it does seem predominantly B2B when you say, you know, 88% involved in B2B.
[00:14:49] Paul Roetzer: Um, but when the reality is you, you still have a large component that are heavily B2C as well. So it does present a, a balanced mix of perspectives.
[00:14:57] Mike Kaput: So when it came to [00:15:00] the revenue of the companies that these people work at, the majority, 51 of respondents said they work at companies with 10 million or more in revenue. That is a very large jump from 2023 when just 42 percent said the same.
[00:15:16] Mike Kaput: thing.
[00:15:16] Paul Roetzer: Yeah, and kind of likethedirector level and above, this has been a concentrated effort. of ours is, you know, to, to reach more of that larger enterprise audience and to get a better understanding of their perspectives, their needs, the challenges they’re facing, and a lot of the private, speaking engagements and workshops that Mike and I do is actually to this larger enterprise audience.
[00:15:41] Paul Roetzer: And since ChatGPT, the demand has skyrocketed in that space. So this does align not only with the demand we’re seeing from these bigger companies to understand and adopt AI,
[00:15:50] Paul Roetzer: um, but that they’re taking a much greater interest in
[00:15:54] Paul Roetzer: in the institute and our education and training and events and content. So again, it’s [00:16:00] encouraging for me because this has been an effort we’ve been making, and I think it’s just representative of the fact that Companies of all sizes, especially these big companies, are now trying to figure out what the play is here and what they can do about AI.
[00:16:12] Mike Kaput: So sort of in line with that, we also asked about, number of employees and the majority, 53%, said they work at organizations with 50 or more employees.
[00:16:23] Mike Kaput: And that’s a 5 percentage point increase from 2023.
[00:16:27] Paul Roetzer: Yeah, and the good news here, this does obviously parallel pretty closely the revenue increase numbers, but what this means is because we’ve almost doubled the number of respondents this year to close to 1, 800, we’re now getting to the point where we can run meaningful segments and look at small business responses, look at large enterprise responses, And so as we keep moving forward with this annual research, it’s encouraging to us because we’re going to get much better at being able to drill into specific industries or specific segments or specific sizes.
[00:16:56] Paul Roetzer: And so that’ll help us really get a, again, a clearer picture of what’s going on [00:17:00] that we can then share with our community.
[00:17:02] Mike Kaput: And so one last bit of demographic data here. This actually is not listed in the report and wasn’t covered on the webinar. We ended up pulling it after, the webinar itself where we actually went in and looked at kind of the IP, um, listing of the contacts who had given us their contact information to fill out the survey.
[00:17:24] Mike Kaput: And in that way, we were able to figure out how does this break down roughly geographically. Now, not every single survey respondent gave us, their contact info in order to get their IP address, but it’s the vast, vast majority that did. So this is highly representative of where the respondents come from.
[00:17:42] Mike Kaput: And we had about 72 percent We’re In the
[00:17:46] Mike Kaput: U. S., about 5
[00:17:47] Mike Kaput: percent in Canada, 5 percent in the United Kingdom, 2 percent in Australia, and then 1 percent each from Germany, Spain, India, Italy, Netherlands, France, Mexico, New Zealand, [00:18:00] and South Africa.
[00:18:02] Paul Roetzer: Yep. And again, like kind of along the lines I would expect. we do ask this data for like our marketing ad conference. and I think we ask it for our virtual summits. So we actually get into exactly what country people are in. In this case, we don’t ask it on the form, but I think this is pretty representative of, you know, what our.
[00:18:22] Paul Roetzer: Uh, but what our understanding of our audience would be, you know, it’s a big presence, obviously, in the U. S. and then, I mean, but we had, uh, you may remember it, Mike, I think the AI for B2B Marketers Summit, we had 92 countries registered, I believe. It was all 50 states and 92 countries. So, you know, our reach is certainly global.
[00:18:41] Paul Roetzer: It is just, you know, dominantly within the U. S. in terms of our audience breakdown.
[00:18:46] Key Findings
[00:18:46] Mike Kaput: for sure. All right, so we’re going to dive now into kind of the key findings that we pulled out of the report. Now everything we go through here, I want to note, is not everything that’s in the report. These are kind of the [00:19:00] major takeaways, the major stories we’re seeing. There’s a ton of other data that’s not Fully or directly covered in here. So I definitely encourage you still, if you’re listening to this, to go check out the report itself too.
[00:19:11] Paul Roetzer: And the report obviously has visuals to go along with all of this, so whether you want to download it now and follow along, or after the fact, you can, you can kind of like visualize everything we’re talking about as well.
[00:19:22] Mike Kaput: Yeah. So that’s a great note. If you want to take a second to pause and go to stateofmarketingai. com, grab your report and follow along as we go. Now’s the time to do it.
[00:19:33] Mike Kaput: All right. so, first up, one of the big key findings is that AI adoption and understanding are on the rise. So, we had 99 percent of respondents say that they’re personally using AI in some fashion, and the level of AI usage appears to be rising significantly.
[00:19:52] Mike Kaput: We have 36 percent of respondents say that AI is now infused into their daily workflows. We asked this question last year [00:20:00] as well, and we are up 7 percentage points from people who said the same thing last year. There was a significant jump in people who said they, quote, couldn’t live without AI. That was one of the, options.
[00:20:12] Mike Kaput: It went from 6 percent in 2023 to 15 percent last year. today. That’s a huge jump. This is also accompanied by a drop in the percentage of people who said they are simply experimenting this year. That was just 26 percent of people last year. 45 percent said they were simply experimenting. This kind of indicates it seems that marketers and business leaders are expanding their use of AI in their work year to year. 61 percent of respondents said they now have an intermediate level understanding of AI. That’s up 54 percent from last year. 16 percent said they have an advanced understanding, which is up from 11 percent last year. And, predictably, this is accompanied by a drop in the number of people who classify themselves as beginners in their [00:21:00] AI understanding.
[00:21:01] Mike Kaput: We went from 35 percent last year to 23 percent this year. this year. So Paul, what did you kind of make of some of the swings here in terms of overall adoption and understanding?
[00:21:13] Paul Roetzer: Yeah, this first one is maybe the most stark example of the importance of percentage points versus percentage
[00:21:20] Paul Roetzer: increase. So, the people who said they couldn’t live without it. So again, the question is how would you best describe your personal use of AI tools? The options are couldn’t live without it, infused into my daily workflow, experimenting, use AI periodically, don’t use AI at all.
[00:21:36] Paul Roetzer: And so the people who said couldn’t live without it went from 6%. to 15 percent as Mike said. Now that’s nine percentage points, but that’s 150 percent change. So we’re talking about 150 percent increase in the number of people who said they can’t live without it. So that tells you like how instrumental AI is becoming to people’s personal and professional [00:22:00] lives.
[00:22:00] Paul Roetzer: The other thing to keep in mind is on this, the shift in Moving from like beginner to intermediate to advanced. While it’s, again, it’s encouraging to see the people who would identify themselves as being intermediate when asked how they classify their understanding of AI terminology and capabilities, there is still a very, very large percentage of people who don’t really fully understand what it is, who maybe have anxiety about it, have fears about it.
[00:22:24] Paul Roetzer: We see it every month when we do our Intro to AI for Marketers class. That class still draws like 1, 000 to 1, 200 people.
[00:22:32] Paul Roetzer: Every four weeks, and we don’t even advertise it, I don’t think, anymore. It used to be that we had to run ads to get people to come to us three years ago when I first started doing it.
[00:22:41] Paul Roetzer: So I’ve been teaching this class since, I think it was November of 2021, we did the first one, and I’ve been doing it every week live since then. We have, the 40th edition of that class is actually, I think it’s like August 15th, that’s coming up next week. And so we’ve got over 25, 000 people. go through that class, [00:23:00] and the demand is actually increasing.
[00:23:02] Paul Roetzer: So what that tells me is a very strong data point. That a lot of people are still just trying to figure out the fundamentals. They still actually just need that entry level education and support. So if you’re someone who has raced ahead and you’re, you know, you’ve got 20 different pilot projects going on and you have 17 different AI platforms and you feel like you’re just immersed in this.
[00:23:23] Paul Roetzer: Don’t, don’t leave the other people behind. There’s a lot of people in your company, a lot of people in your peer groups who haven’t figured this out yet. And I think it takes a collective effort for all of us to realize that and to make sure we’re continuing to make it approachable and actionable for the large part of our community and our peer group and our industry who just need the fundamentals still.
[00:23:45] Mike Kaput: So another big takeaway here is that the majority of marketing teams appear to now be piloting or scaling AI. So we ask every year, like what stage of AI transformation best describes your marketing team? You can pick from [00:24:00] understanding, piloting, or scaling with descriptions of kind of how we define each of those and the majority now say they are either piloting or scaling which is a pretty significant difference from last year so 51 percent said they were either piloting or scaling AI compared to 42 Combined last year.
[00:24:22] Mike Kaput: Additionally, we are seeing confidence in purchasing AI technology rising. We ask, how would you rank your confidence in evaluating AI powered marketing tech? You can select none, low, medium, high, very high. And we are seeing that 48% percent Of Of respondents rate their confidence in evaluating AI powered marketing tech at a medium level.
[00:24:44] Mike Kaput: This is a slight rise over 2023. Fewer people this year also rated themselves as low confidence. Only 16 percent said they were low versus 21 percent last year. And slightly more rated their confidence as high or [00:25:00] very high. It was 35 percent in one of those two groups this year. 32 percent in 2023. So Paul, did that kind of track as well with what you were kind of seeing and hearing in the market?
[00:25:13] Paul Roetzer: Yeah, and again, I think this is an important reminder in the inherent bias in any research. And so as Mike called out up front, the people responding to our research, while it is a solid sample size of nearly 1800 people. They are largely people who already follow our podcast, like listen to the podcast or are active in the Marketing Institute community.
[00:25:37] Paul Roetzer: So these are people who have been proactive in seeking AI knowledge and understanding and likely, using it, you know, again, with 15 percent are saying they can’t live without it. So what that means is when our data shows 49 percent at the understanding stage, 41 percent at the piloting stage, those numbers are probably, the understanding numbers in piloting, are [00:26:00] probably, lower than what you would, Expect, or, or the piloting of one at least would be more advanced than what you would expect.
[00:26:08] Paul Roetzer: So a lot of companies I would expect are actually more at the understanding phase. So our, what our piloting and scaling numbers are probably skewed higher than what the rest of the industry at large would be. And when we go in and talk with these organizations, especially these bigger enterprises, we are seeing.
[00:26:26] Paul Roetzer: The understanding and piloting being the most common thing. And I’m honestly like understanding is still the dominant. So the scaling of like, if you’ve got this all figured out, they’ve got AI councils and roadmaps policies, and they’re doing internal education and training, that’s very, very rare right now.
[00:26:44] Paul Roetzer: Um, I,Ican’t get into like the companies we do our private engagements for, but I can tell you there are companies on that list that I have done the Intro to AI class for privately, where we’re talking about 300 [00:27:00] marketers from a major enterprise where I go in and teach the fundamentals, and some of the companies we have done that for would be shocking to people.
[00:27:07] Paul Roetzer: So we’re talking about leading tech companies, major enterprises that you assume have this figured out, And a lot of times, they are bringing us in to do the fundamental education. So, our experience, which is pretty broad in terms of dozens of these engagements, is that they are trying to help their whole team understand it.
[00:27:29] Paul Roetzer: And they’re trying to prioritize pilot projects. There are very few enterprises we talk to who are actually at the stage where they’re ready to scale it now. So that’s, again, if your organization is at that early stage, and it’s very siloed, the understanding of this stuff, and people are kind of afraid of it.
[00:27:46] Paul Roetzer: That, that is the more common, position right now that we see in the market. So that’s an opportunity for you. Like, don’t feel like you’ve been left behind, feel that there’s an opportunity ahead to really more aggressively pursue piloting and [00:28:00] scaling.
[00:28:00] Mike Kaput: So we also found that saving time. Using AI is the number one outcome desired by far by respondents.
[00:28:11] Mike Kaput: So we ask, what are the primary outcomes that your organization is interested in achieving with AI? Choose all that apply, and we provide a number of preset responses, one of which is reduced time spent on repetitive Data driven tasks. This was the most cited by far, with 80 percent of respondents choosing this as at least one of the outcomes that they chose.
[00:28:37] Mike Kaput: Now, the next most common response was get more actionable insights from marketing data, but that was kind of a distant second. That was 64 percent of respondents cited. That one. So Paul, what did you take away from the saving time, reducing time on repetitive data driven tasks being such a clear winner
[00:28:57] Mike Kaput: here?
[00:28:57] Paul Roetzer: It’s the most obvious outcome and the [00:29:00] most logical place for people to start, so it makes perfect sense that, again, this year it would be number one. And I think we give 11 options and none of the above, so, you know, there’s a fair amount of choices and this is, you know, Far and away the number one choice.
[00:29:14] Paul Roetzer: So what we see is the best way to start with pilot projects is this repetitive data driven task approach. Like what are the things we already do in our job, our job description, what campaigns are we running? What are the things we can just infuse AI into right away? And so I do think that a lot of organizations for the next year or so are going to continue to focus on this as their integration with AI.
[00:29:34] Paul Roetzer: They’re going to try and help different team members across different departments find those obvious use cases where they save.
[00:29:42] Paul Roetzer: They’re more efficient, they’re more productive. It’s the logical place to start because the ROI is easy to assess.
[00:29:48] Paul Roetzer: I think the organizations that become the leaders in the infusion of AI, that become AI forward, as we would call it, they’re going to look for ways for AI to accelerate revenue, creativity, and innovation. [00:30:00] And so if you’re in an organization that’s still at this kind of early pilot phase where you’re trying to find use cases for efficiency and productivity, that’s okay.
[00:30:08] Paul Roetzer: But what we want to start doing moving into 2025 is really thinking bigger picture about how it can help us accelerate the growth and success of the company overall.
[00:30:19] Mike Kaput: So this year, we also found that ChatGPT is the most popular AI platform that is licensed in organizations. So we asked a new question this year, asking if respondents were being provided with licenses to use it. Any of the popular AI tools out there, we ChatGPT, a Team or Enterprise License, Copilot for Microsoft 365, or Gemini for Google Workspace, given how prominent those three are being adopted by companies.
[00:30:48] Mike Kaput: There’s also a None of the Above option. So, the majority, 55%, said their organization, Provided them with a license to ChatGPT Team or Enterprise. [00:31:00] 31 percent said they were provided with a co pilot license. And 17 percent said they had a Gemini for Google Workspace license. Now, significantly about 29 percent said that their organization did not provide a license to any of the three options that we gave them.
[00:31:17] Mike Kaput: Um, what’s really cool is this year we also asked respondents to write in. their favorite AI tool or platform. So this isn’t necessarily when they have a license to through work, but just what is their favorite tool to be using. Um, we had more than 590 people directly cite ChatGPT, overwhelmingly the most popular answer, 37 percent of respondents. The second most common response was actually the AI powered search engine, Perplexity. With over 184 direct mentions, which was 12 percent of respondents. Now, respondents also wrote in a bunch of other tools like Claude, Google [00:32:00] Canva, Drift, Descript, Grammarly, and tons of others. So, these were at far lower rates than ChatGPT
[00:32:08] Mike Kaput: and Perplexity, but still interesting, Paul, to see kind of the diversity of tools people are using.
[00:32:14] Paul Roetzer: I was really excited to see this data come through because these were new questions this year and so once we got the results in, ChatGPT was higher than I would have predicted. I would, I would have guessed ChatGPT was going to be the leading choice here. in terms of platforms that organizations have a license for, but I wouldn’t have expected 55 percent of respondents to say that their company provides licenses to ChatGPT.
[00:32:38] Paul Roetzer: That’s pretty
[00:32:38] Paul Roetzer: wild. What we have seen time and time again with larger enterprises that have co pilot licenses is definitely more common. So I would have expected co pilot to be more popular than Gemini, which it is almost two to one. Um,
[00:32:53] Paul Roetzer: the,
[00:32:54] Paul Roetzer: What’s happening a lot, and we talked about this on episode 105 with the Chevron example of 20, [00:33:00] 000 co pilot licenses, what we keep hearing is, yeah, we have co pilot licenses, but we don’t have access to it, or if we do have access to it, especially in the marketing department, they haven’t been taught how to use it.
[00:33:13] Paul Roetzer: They just turn it on and say, okay, you now have Copilot. And then people are left to figure out for themselves, well, what would I do with it? And then, you know, when you question, well, what’s the value of a Copilot license or a ChatGPT or a Gemini license, and you’re asking people who haven’t been trained how to actually use it or helped to figure out what use cases they should be applying it to other than email and help me write my document, you get a lot of just, eh, like, what’s the value of these AI platforms?
[00:33:40] Paul Roetzer: It’s like, I don’t know. It’s okay. Like, it’s fun to use it to write my emails or it helps me be more efficient in my inbox, whatever. And it’s like, that is just not what we’re here for. And I think episode 108 this week, we talked about that new Microsoft
[00:33:53] Paul Roetzer: study
[00:33:54] Paul Roetzer: on this exact issue, where they went and like assessed themselves the value of Copilot and it wasn’t obvious because [00:34:00] They weren’t teaching people the use cases to
[00:34:01] Paul Roetzer: pursue. So
[00:34:02] Paul Roetzer: this to me is a huge opportunity for everyone is to, you know, really think about that education and training, which we’ll talk more about in the upcoming findings. but yeah, I think this data was really cool and I’m excited to look at this as we move forward. I could see Anthropic Claude probably being added to this list next year.
[00:34:19] Paul Roetzer: It wasn’t really, they didn’t even have an offering. I don’t think when we first put the survey in the field this year, that was a pretty new thing. So yeah, this was a, this was a cool finding. The moment is
[00:34:29] Mike Kaput: So like we said at the beginning, this is the fourth annual state of marketing AI report.
[00:34:34] Mike Kaput: And every single year we find In one of our key findings, that lack of AI education and training is still a massive barrier to AI adoption. This year, unfortunately, is no different. We asked the question, which of the following do you consider barriers to the adoption of AI in your marketing? Choose all that apply.
[00:34:55] Mike Kaput: And there’s about a dozen different options of possible barriers that you can choose as well [00:35:00] as none of the above. 67 percent of respondents said that a lack of education and training was their top barrier to AI adoption in their marketing. And this number actually rose slightly this year. It was 64 percent last year.
[00:35:17] Mike Kaput: So that was kind of a little, surprising. We also asked outright. Does your organization offer any AI focused education and training for the marketing team? Collectively, 75 percent either said no, that was 47 percent said straight up, no we don’t have any. 24 percent say it’s in development. 4 percent said they’re not sure if it exists.
[00:35:40] Mike Kaput: So either they don’t have it is being produced, but they don’t have access to it, or they don’t know it exists. That’s three fourths of all respondents essentially have no access to formal AI education or training. Now, while these numbers improved a bit from last year,
[00:35:57] Mike Kaput: Paul, I would say that’s [00:36:00] still pretty concerning.
[00:36:01] Mike Kaput: Would you agree?
[00:36:03] Paul Roetzer: I remember the first time we did this survey four years ago, and that lack of education and training came back so far and away, the number one barrier. And I wouldn’t say I was surprised by it back then, but the size of the difference was somewhat surprising to me that it was so, people were so aware that that was the major issue they were having.
[00:36:22] Paul Roetzer: And so, you know, it just continues to be the number one problem. And then it like, when it started growing again this year, like I think in our early days, it was in the 70 percent and then it was like, okay, no, we’re making progress. And then this year it starts jumping back up. And so again, this is like, yeah, why are you saying like, we focus so much on this idea of accelerating AI literacy because all this other stuff like piloting and scaling and building AI consoles and roadmaps, like none of that matters or is even possible to do right.
[00:36:49] Paul Roetzer: Until we have AI literacy, and it’s not siloed among a few leaders, it’s actually democratized across teams. And so this data just reinforces it, and [00:37:00] yeah, while we’re seeing an improvement in the AI education and training being offered to people, it’s still only 26 percent of respondents that say their company provides it.
[00:37:09] Paul Roetzer: And that is a shockingly low number. Given the outsized impact AI is having and will have on business and the future of work. So this to me is where we have such an obvious area of room for improvement and such an accessible way to do it. Like you can start this tomorrow, like put the frameworks of an internal academy in place, like Put some basic curriculum together.
[00:37:36] Paul Roetzer: Have someone, you know, your whole team take a certification course together. there’s just ways to do this really fast. This doesn’t take a year of fighting through bureaucracies within your company. It’s saying, Hey, as a marketing team, let’s create our own internal marketing AI program, and let’s listen to this podcast, read this book, take this course together, like, just do something and then build a more formal program.
[00:37:59] Paul Roetzer: So [00:38:00] our Scaling AI course series that we launched in June, I have an entire course dedicated to how to build an academy within your organization. Sample, learning inventory, sample, Personalized learning journeys for marketing managers. Like it’s all in there. So that’s like a really fast way to accelerate.
[00:38:16] Paul Roetzer: If you want to go figure out how to build your own Academy, check out that scaling AI series. It’s just scalingai. com if I remember correctly.
[00:38:23] Mike Kaput: That’s correct. so we also asked this year again about like, what kinds of maybe AI policies do you have in place? And we found that 34 percent only of companies say that they have generative AI policies.
[00:38:39] Mike Kaput: However. That’s up a whopping 55 percent over 2023. So we had asked the question, does your organization have generative AI policies which guide the use of AI generated text, images, video, audio, and or code? 34 percent said yes, 8 percent said they were not sure. [00:39:00] We also asked a related question about AI ethics policies.
[00:39:03] Mike Kaput: Does your organization have an AI ethics policy and or responsible AI principles, either public facing or for internal use? Now, 36 percent said that they did, which is still overall low, but that is a jump of 15 percentage points. from 21 percent last year. So, Paul, there has been some good movement here, it seems, on this particular benchmark.
[00:39:30] Paul Roetzer: On the Gen AI policies, it is really solid progress. The majority still do not have them. I mean, we’re still talking about 58 percent no, 8 percent not sure. So that’s 64 percent who probably don’t have them. But it is, again, it’s year over year, we are seeing improvements. So that is great. I will do a note of caution here.
[00:39:49] Paul Roetzer: Having them and actually training your teams on them are two very different things. So we have definitely sat in meetings where they’ve said, yeah, we have them. And then we say, okay, how has the team been [00:40:00] trained on these policies? And you get crickets. So I would just encourage people, if you have them or if they’re in development, make sure there’s also a rollout plan and a, and a, and a
[00:40:11] Paul Roetzer: and a plan
[00:40:12] Paul Roetzer: To reinforce those policies throughout the year to remind people because we see policies as freedom.
[00:40:18] Paul Roetzer: We see as giving people guardrails to responsibly adopt and apply AI. And so you want to make sure you’re reinforcing that throughout the year and encouraging them to use this technology in a responsible way. The AI ethics one. Obviously a huge jump, but I think, you know, it’s, it becomes more and more critical moving forward that, that these help guide us because it seems very apparent as we talk a lot about on the podcast, laws and regulations aren’t going to keep up.
[00:40:47] Paul Roetzer: This is going to be about having a moral compass, having guidance internally that provides guidance. your people with an understanding of what are the right ways to use these technologies and how to remain human centered in your approach to [00:41:00] AI. And these AI ethics or Responsible AI principles are fundamental to that.
[00:41:04] Paul Roetzer: As a reminder, we have a Responsible AI Manifesto that is available under Creative Commons for you to take and remix however you want. It has 12 standard principles that we use internally at the Institute and that we created and shared publicly. And we’ll put the link in the show notes. But if you don’t have any in your organization, take those and use it as a starting point.
[00:41:25] Paul Roetzer: They are available there. And I think you’d even download a Word document of them from our website.
[00:41:29] Mike Kaput: So we also
[00:41:32] Mike Kaput: found this year that the vast majority of companies lack AI councils and roadmaps. We first up asked, does your organization have an AI council charged with developing policies and practices and considering the impact of AI?
[00:41:47] Mike Kaput: on the company. Just 29 percent said that they did have one, however it was interesting when you look at the cohort of companies with 1 billion plus in revenue, there are many many more [00:42:00] said they had an AI council, 54 percent of that specific cohort said they had one.
[00:42:05] Paul Roetzer: uh,
[00:42:06] Mike Kaput: also asked, does your marketing team have an AI roadmap or strategy that prioritizes AI use cases and projects for the next one to two years?
[00:42:15] Mike Kaput: Now, only 19 percent of respondents said that they did. However, again, 1 billion, Plus firms outperformed here with 26 percent saying they had a roadmap or strategy. Now, Paul, still, regardless of which cohort we look at, this still seems pretty low.
[00:42:34] Paul Roetzer: And again, new questions this year, so I was really excited about this data. the AI Council, you know, we’re, we’re at 29 percent yes. What we’re seeing here is, um,
[00:42:45] Paul Roetzer: Um, some large organizations have an overall AI council, and what we often encourage is if, like, maybe you don’t have a voice in that AI council.
[00:42:54] Paul Roetzer: I have done talks for very large enterprises where the marketing department isn’t [00:43:00] represented. On the larger AI council. They don’t even have a member on the council. So they’re just sitting back waiting to be told what’s going on within the organization. So one, if you have a larger AI council, that’s more broadly for the organization, make sure the marketing department has a voice in that, or if you’re not in marketing and you listen to our podcasts and you’re, you’re intrigued by all this, make sure your department has a voice in that council.
[00:43:24] Paul Roetzer: The alternative here is, raise your hand and start a Marketing AI Council, or a Sales AI Council, or a Customer Service AI Council, whatever it may be. there’s no reason you can’t follow this same process internally, create a charter, involve members, get them, you know, engaged in the process. And then figure out what the role of that council is.
[00:43:43] Paul Roetzer: So I would just encourage people like a council is a great way to put a formal structure in place to keep up with on the latest news and information and figure out what it means to you and your organization. And then in terms of the roadmaps, you know, obviously only 19 percent said, said yes. And this is what I was saying.
[00:43:59] Paul Roetzer: Like, I think.[00:44:00]
[00:44:00] Paul Roetzer: Most
[00:44:01] Paul Roetzer: organizations are still just trying to figure out the first few pilot projects to prove the value of this stuff, and they haven’t really figured out the one to two year plan of the next 10 they’re going to do, and then how they’re going to scale it from there. So, I think that this is a real opportunity for everyone listening is to, you know, figure it out.
[00:44:18] Paul Roetzer: Make it an effort maybe over the remainder of 2024 to put an actual AI roadmap in place going into 2025 that prioritizes use cases, problem statements, AI projects that you’re going to focus on in the coming year.
[00:44:33] Mike Kaput: So we have a few more key findings here before we get into some of the questions that people had asked. Um, one other one that I found really interesting is that nearly half of our respondents this year believe that AI will eliminate more jobs than it creates in the next Three years. So we asked, what do you, what do you believe the net effect of AI will be on marketing jobs over the next three years?
[00:44:57] Mike Kaput: More jobs will be created. More jobs will be [00:45:00] eliminated. I don’t know, or AI won’t have a meaningful impact on jobs. 47 percent said that AI would eliminate more jobs than it creates in the next three years. That’s
[00:45:11] Mike Kaput: a seven percentage point jump from 2023. And the number of people who thought that more jobs would be created rather than eliminated fell by 5 percentage points.
[00:45:22] Mike Kaput: It was just 31 percent of respondents this year. Now we also asked about how people saw AI automating their work today and in the near future. So we asked two related questions and then merged the data. So first, what percentage of marketing tasks that your team performs are intelligently automated to some degree today?
[00:45:46] Mike Kaput: And then we said what percentage of marketing tasks that your team performs do you believe will be intelligently automated to some degree in the next three years? years. Now, when you look at the answers to this, a whopping 78 [00:46:00] percent believe that more than a quarter of their marketing tasks will be automated by AI to some degree in the next three years.
[00:46:08] Mike Kaput: 45 percent of respondents expected more than half of their tasks to be automated in the same time frame. So this is pretty interesting to me, Paul, both for the sentiment and also people seem to be quite clear eyed about AI’s potential for automation, yet when paired with the lack of strategy, education, counsels, it’s kind of a worrying picture we’re starting to see in this aspect.
[00:46:32] Paul Roetzer: Yeah, I think some reality is starting to set in that there’s a reasonable chance that AI is going to cause disruption to jobs in the near term. And so we talk a lot about this on the podcast, episode 106. We went pretty extensive on this. in course eight of the scaling AI series, I mentioned, I created a whole course on how to do AI impact assessments, which is basically taking a job and trying to project one to two years out the [00:47:00] impact AI will have on it.
[00:47:00] Paul Roetzer: How many tasks make up that job? Which of those tasks will be AI assisted to some degree in the next one to two years? What does that mean in terms of time savings and redistribution of resources? So I just feel like we need to be talking more about taking a more intentional and scientific approach to assessing where AI is going to impact us and then being proactive in preparing for that.
[00:47:22] Paul Roetzer: And so I think that’s really important. I do think this more jobs will be eliminated by AI response is going to jump again next year.
[00:47:29] Paul Roetzer: I think again, the reality is going to start to set in, that, that is a likely scenario for the near term. And then in terms of the automation of tasks, it is very stark when you look at that visual in the report to see how people feel now versus three years from now.
[00:47:45] Paul Roetzer: And I do think people are still underestimating it. I do think that there’s a reasonable scenario where 90 to 90, I don’t know, 99 percent of our tasks that we do will have AI infused to some degree. Again, this does not [00:48:00] mean AI does the task for
[00:48:01] Paul Roetzer: us, but I
[00:48:02] Paul Roetzer: have a really hard time envisioning a world three years from now in marketing and more broadly in business where AI isn’t assisting in some degree, whether it’s 5 percent of the work, 10 percent of the task, whatever it is.
[00:48:15] Paul Roetzer: Uh, I think it’s a very likely scenario that it’s, it’s way higher than what people currently assume it to be.
[00:48:22] Mike Kaput: So interestingly, kind of in tandem with that, we also found that overall sentiment about AI’s impact is Positive, though many have some concerns about near term negatives. So we asked, how do you feel personally about AI and its impact, the impact it’s having on marketing, business, and society? 68 percent said they had it. Are the top positive personal feelings.
[00:48:46]
[00:48:47] Mike Kaput: 14 percent said they were neutral. 14 percent said they also did not, were not sure how they felt about it. And 4 percent said They had negative feelings.
[00:48:57] Mike Kaput: So those numbers are actually really, really, really close [00:49:00] to last year. So there’s not like any real big sentiment change here. But what is cool is that we did this year,
[00:49:08] Mike Kaput: Ask some new questions that were open ended. First, what are you most excited about when it comes to AI? So we actually have the ability now to kind of get some more qualitative data around What people are saying and thinking related to AI.
[00:49:21] Mike Kaput: And a lot of the things people were excited about, the most popular answers kind of revolved around AI’s ability to make work more efficient and productive, to foster innovation and creativity, and also to practically be applied to automation and business growth. We had some people saying things like, quote, I’m excited about the sheer ability and ease to complete tasks.
[00:49:43] Mike Kaput: I’m excited more time for creativity and critical thinking, and I’m excited about expanded possibilities to grow existing businesses and jumpstart new ones. Now, that didn’t mean respondents weren’t also concerned about some things. We also asked an open ended, write in question this [00:50:00] year about what concerns you the most about AI.
[00:50:02] Mike Kaput: And topping this list were concerns about the lack of resources and knowledge to take advantage of AI. Especially a big, big concern is the speed of change and innovation.
[00:50:14] Mike Kaput: Many respondents, said they just don’t have the tools or time to adequately keep up. They’re worried they could fall behind.
[00:50:21] Mike Kaput: They’re worried about misuse
[00:50:22] Mike Kaput: and abuse of
[00:50:23] Mike Kaput: AI and privacy and security. Many other concerns here, but a lot of them fell into these categories. So some people said things like, quote, I’m concerned that the company I work for will fall behind because they are afraid of AI. I’m afraid of deepfakes, copyright infringement.
[00:50:40] Mike Kaput: I’m worried about data privacy. So, Paul, I thought that was some really interesting, like, rich layering in qualitative, you know, insights into what people are really have top of mind. I can’t say any of it surprises me, but it’s interesting to hear it directly from people.
[00:50:55] Paul Roetzer: Yeah, I love this section of the report. It is the first time we’ve done these open ended [00:51:00] questions. And so I was really anxious to see what people say. And there’s dozens of these responses, including included in the report. As you go to pages 31 to 33, and it’s got dozens of these responses that people gave on concerns and what they’re excited about and I think people will see a lot of themselves in these responses.
[00:51:16] Paul Roetzer: Like, there’s a lot of them I was going through, I was like, yeah, I feel that. And yep, I’m excited about that. And And I think it’s just this balance. And people always ask me what worries me most or what am I most excited about?and honestly, I bounce between these stages. Like I I’m just right in the middle.
[00:51:31] Paul Roetzer: Like I’m, there are things I’m very worried about, for the the future in AI. And then there’s things that I think are just amazing and unparalleled in the possibilities we’ve had before. And so I think. We need to live in both of those realities that there are fears that we have to address and we have to, you know, think about regularly regularlyand be proactive in pursuing solutions to, but there’s these amazing things that it’s going to open up the possibilities for, and we can’t lose sight of that and become, you know, restricted by our fears [00:52:00] and not take advantage of the opportunities ahead.
[00:52:03] Mike Kaput: All right, so in one second, Paul, we’re going to dive into kind of rapid fire going through questions that people asked during the webinar. the webinar where we revealed these findings.
[00:52:13] Mike Kaput: But kind of to wrap this all up, our last takeaway here was really that Looking at all this data, it is kind of clear that we stand at a bit of a crossroads. Like, we’re seeing from this data that we just talked about that marketers and business leaders do seem to be largely all in on AI.
[00:52:33] Mike Kaput: They’re using it more than ever, they’re adopting it at unprecedented rates, they’re viewing it positively.
[00:52:39] Mike Kaput: But, as they integrate it into their work, They’re now seeing some of the potential you mentioned for it to disrupt business and employment. On some, one hand, many people find this exciting because it can offer new ways to improve productivity and performance. On the other, They’re starting to see that AI might automate [00:53:00] significant amounts of work and maybe impact jobs.
[00:53:03] Mike Kaput: Now, are they prepared for this? That’s kind of the big question. Like on a personal level, maybe they’re increasingly using tools and infusing them into their work, but Paul, maybe as a final thought here, it really does seem to come back to that lack of preparedness at the company level. So even if people are trying to run ahead on their own, they’re lacking a lot of the support and infrastructure that is going to really help them with a sense of urgency get prepared for a business environment that’s being rapidly disrupted by AI.
[00:53:36] Paul Roetzer: Yeah, I do think that that is a really key point here is that the research continues to show that individually, people want to pursue this. They see this lack of education kind of holding them back. They don’t have policies and roadmaps from their organizations, but they see the opportunity. They see intelligent automation.
[00:53:56] Paul Roetzer: On the frontier, it’s coming. They see, the impact it’s [00:54:00] going to have on jobs, and they’re just not getting the support from the organizational level to put the things in place to prepare them, to reskill, to upskill, to have plans and visions for where it goes. And that Again, we can look at this as a negative, or we can look at this and say, think of the opportunity we all have, that you individually listening to this, that you have, to raise your hand and be a leader in this space.
[00:54:22] Paul Roetzer: You know, if you’ve spent the last 50 minutes with us listening to this, you obviously care about this topic, and you know, maybe it concerns you, maybe it excites you, maybe it’s a mix of the two,
[00:54:33] Paul Roetzer: But you’re, you’re putting in the time to learn about it. And there aren’t that many people in your organization doing that.
[00:54:40] Paul Roetzer: There probably aren’t even that many people in your industry doing that. So you have this incredible opportunity ahead in your career to take this kind of knowledge and figure out what it means in your organization. And that’s why we say we’ve arrived at this crossroads.and you as a listener have sort of arrived at this crossroads as well.
[00:54:57] Paul Roetzer: The technology is enabling all of these things. [00:55:00] But most organizations don’t know what to do with it. And so that’s the opportunity for all of us ahead is to figure that outand help drive not only literacy within organizations, but responsible adoption and transformation.
[00:55:14] Q&A
[00:55:14] Mike Kaput: All right, Paul, let’s dive into some rapid fire question and answer.
[00:55:18] Mike Kaput: Session. We got a ton of different questions during the webinar where we talked through these findings. Some of them are about specifically the findings. Some are kind of just follow ons to what some of the data seems to imply or bigger topics that the data talks about a little bit. So I’m going to just jump right in here, and start throwing some questions at you.
[00:55:38] Paul Roetzer: Sounds good.
[00:55:39] Mike Kaput: Alright, So first up, someone asked, what was the biggest surprise to you from the findings?
[00:55:45] Paul Roetzer: Yeah, I mean,Ikind of think about some of the new data because, you know, the education and training, I wouldn’t say it surprises me, like it is, it just keeps showing up at the top and I keep expecting there to be more improvement [00:56:00] and
[00:56:00] Paul Roetzer: it’s not happening, but it’s not a surprise. It’ll be a surprise when it does get resolved, I think.
[00:56:04] Paul Roetzer: Um, I think I go back to the ChatGPT, that 55 percent number of Almost 1800 people we surveyed that 55 percent have, company sponsored licenses to ChatGPT. Like that’s a, that’s a big number. I don’t know, was there anything that jumped out at you, Mike, that you spent way more time analyzing all these findings than me, um, anything jump out at you as you were doing it?
[00:56:26] Mike Kaput: Yeah, I would say that jumped out at me for sure. I also thought it was actually kind of interesting that the second most popular or favorite write in tool was Perplexity. Not because I’m surprised that that tool’s amazing. And we talk it up quite a bit. Among the Institute audience. But I’m like, Oh man, maybe this whole search landscape is going to change even faster than we think if that’s the second most after I kind of expected, honestly, it to be another foundation model or like Claude or something.
[00:56:55] Mike Kaput: So
[00:56:55] Paul Roetzer: Yeah, that’s a good point. Yeah.
[00:56:57] Mike Kaput: all right,
[00:56:58] Mike Kaput: next up, this is a [00:57:00] big question. I’m not saying we can answer every aspect of it, but what is your three to five year view on how AI is going to be adopted?
[00:57:09] Paul Roetzer: I’ve been pretty, consistent on this messaging that, you know, when I do my keynotes, I’ll often leave with a slide that I, you know, under the assumption at least 80 percent of what we do will be AI assisted to some degree in the next one to two years. I said earlier, I feel like. In three years, that could be 90 to 99%.
[00:57:28] Paul Roetzer: Um, I just feel like there won’t be knowledge work done without AI and there really won’t be software we use to do our jobs that doesn’t have AI infused into it. So I feel like three to five years out. You don’t even have to go looking for the AI. It’s just going to be present in everything, whether that’s we’re interfacing through voice technology more commonly, or generative AI is baked into every piece of software we use in some capacity, it’s analyzing our data, it’s writing our emails.
[00:57:59] Paul Roetzer: Like, [00:58:00] I just feel like it’s just going to be. Everywhere, three to five years from now, just an underlying operating system for all knowledge work, basically.
[00:58:08] Mike Kaput: So, someone asked, small or medium sized businesses, SMBs, seem to find the adoption of AI more challenging. And so, how do you see them making it easier? And also, do you even agree with that sentiment? at the beginning
[00:58:23] Mike Kaput: of it.
[00:58:23] Paul Roetzer: Yeah, I don’t, I don’t know that that’s a universal. I could certainly see how people feel that way if, if it is true in your business or your industry, I think it probably goes back to an AI literacy and competency issue where smaller businesses, if you’ve got five, seven, 10, 20 people. Maybe it’s just less likely someone has figured this out and is bringing this knowledge and capability into your company.
[00:58:46] Paul Roetzer: Whereas if you’re in a bigger company, mid market to large enterprise, you’ve got a CIO, a CTO, you maybe have, you know, chief legal counsel, you have heads of procurement, like, There’s just way more people whose [00:59:00] responsibility is going to touch figuring this out. so yeah,Iwould say it’s probably reasonable, but at the same time, a lot of SMBs are the most innovative with their application of AI because they don’t have
[00:59:13] Paul Roetzer: the layers of legal or procurement or, IT to get through to adopt something.
[00:59:20] Paul Roetzer: It’s like, It’s like our company, Mike, we have seven people and I’m the CEO. And if I was like, Hey, I love this tool. Like, I think there’s tons of value. Or if Mike sees something, he says, I think we shall be using this. Like, cool. Like let’s take a 30 minute demo with the team on the weekly call and let’s go.
[00:59:34] Paul Roetzer: So we’re just able to move way faster and innovate and we’re willing to take more risks. And so I think that the SMB thing could go both ways based on that.
[00:59:44] Mike Kaput: So obviously from the findings, there’s this big need for education and training, but like what should education and training consist of?
[00:59:54] Paul Roetzer: Like any, great approach to education, training, professional development, it has to be a mix of [01:00:00] content and experiences. So
[01:00:01] Paul Roetzer: you need to figure out how to tailor learning experiences, learning journeys to individuals or to, you know, individual roles within the company. Figure out how AI is going to play a role in what they do, and then how they learn best, and it might be a mix of both.
[01:00:15] Paul Roetzer: Podcasts, books, online courses, in person events, demonstrate like tech demos, experiments run, cohorts within your company. Like you got to figure out the pieces, but don’t just do one thing because not everybody learns the same way. so I think you just got to take a personalized approach to education and training.
[01:00:36] Mike Kaput: So kind of a follow on to that, I’m really interested in the answer for this. we see this Challenge all the time, like how do you quote unquote sell the need for education and training of AI in marketing or in business within an organization?
[01:00:50] Mike Kaput: I mean, we had that comment in some of the things that you’re, you’re worried about with AI. My company’s afraid of AI, so I’m worried we’re going to fall behind. Like, how do you [01:01:00] do this
[01:01:01] Paul Roetzer: this probably the same way I do the AI technology itself. You have to sell it using terms and business metrics that matter to the people who make the decisions to allow it to happen. So what I mean by that is if you’re in an organization and you’re following along and you want to build that internal AI academy and you’re really excited about this and no one else in your company is, and you don’t have the power to do it yourself.
[01:01:25] Paul Roetzer: You got to go get a sponsor internally. You got to go get an executive who does have the power to make something happen. And you have to work with them to figure out what is the messaging needed to get this kind of support. Do we have to showcase studies? Do we run some pilot projects that we benchmark performance before and after 50 hours last month with this one pilot project for 30 per month of a tech.
[01:01:52] Paul Roetzer: We can carry this out across marketing, sales, service. You, you have to understand what’s going to move leadership. And oftentimes it’s [01:02:00] going to be business performance. And the best way to do that is to run these pilot projects yourself and prove it out and then show how, if we scale it can impact the business.
[01:02:10] Paul Roetzer: So then, well, how do we do that? We got to start with teaching people. We have to start with literacy. So you have to create the need for the literacy and often that isn’t a direct thing. You have to figure out the indirect way. Make them realize it’s what’s needed. all
[01:02:25] Mike Kaput: So this next one is clearly asked by someone who is a consultant, service provider, maybe an agency, self employed person, like what about those people?
[01:02:35] Mike Kaput: Many of the companies I’m contracted with don’t have guidelines for AI. And there have been lawsuits against using AI for creative work in some ways. like, are there any tips for navigating trying to be a service provider of some sort
[01:02:49] Mike Kaput: and use AI to increase performance productivity when the companies themselves may not know how it’s supposed to be used.
[01:02:57] Paul Roetzer: Yeah. so, I mean, the generative [01:03:00] AI guidelines are obviously very critical. Um, we do recommend always to develop those in partnership with legal, whether it’s an outside legal counsel, IP attorneys, or internal legal counsel, whatever it may be. Um,
[01:03:15] Paul Roetzer: but again, like if. If they don’t have the guidelines, you kind of have to show them why they need them.
[01:03:22] Paul Roetzer: And if it’s a company that doesn’t even allow access to generative AI platforms, then you’ve got a couple other obstacles ahead of you before they’re going to take the step of building these generative AI policies. And so, you know, you just got to consider each organization unique. in terms of the lawsuits against using AI for creative work.
[01:03:42] Paul Roetzer: That’s not going away. Like, that’s a very, dynamic and messy environment where all of these AI model companies are going to get sued or are already being sued. Companies have to make kind of their own choices around whether or not they’re comfortable using [01:04:00] technology that they know may have stolen copyrighted material,
[01:04:03] Paul Roetzer: a. k. a. absolutely took copyrighted material. It just may end up being that it was legal to have done it.and and, and those are, again, there’s no right or wrong answer here. I have seen people, you know, comment on my, my posts on LinkedIn who’ve said they’ve just chosen not to use it. And I respect that. I think you’re making, in those environments, like you’re making a choice that likely becomes a competitive disadvantage becauseIjust don’t see the business world slowing down their adoption of generative AI because of these legal concerns.
[01:04:33] Paul Roetzer: I think everyone’s just going to kind of accept there is risk inherent in doing this and that there may have been some questionable methods to how these models were trained. But it is what it is. And at some point in the not too distant future, it will just be an accepted norm that that’s how it was done.
[01:04:48] Paul Roetzer: And maybe they find ways to compensate the creators. Maybe they don’t, but I just don’t see us going backwards.
[01:04:53] Mike Kaput: So when companies are actually trying to adopt AI for marketing, should they be [01:05:00] trying to do it piece by piece, doing proof of concepts and experimenting or developing fully integrated plans before diving in?
[01:05:08] Paul Roetzer: I don’t know how you do a fully integrated plan without the piloting phase. I’m just, you know, such a huge believer in experimentation and having lots of experiments going, lots of pilot projects going, and then, you know, some of them aren’t going to work. Some of them are, and you’re going to keep learning.
[01:05:24] Paul Roetzer: So, I think I would take the, you know, experimentation approach, and then I’d be working on that plan, but that plan itself needs to be dynamic as new models come out, as new laws and regulations, you know, move forward. So even a plan itself isn’t going to be a static 12 month plan. I would encourage very heavily, like, even once you’ve got that AI roadmap, there’s like quarterly reviews of that roadmap to, you know, assess it based on things as they evolve.
[01:05:52] Mike Kaput: So someone asked, said a previous employer of mine was heavily involved in what they’re calling, quote, AI washing. The practice of [01:06:00] heavily exaggerating the role of AI or its capabilities in a product or service. I’ve heard the same from others. Is this a new trend?
[01:06:08] Paul Roetzer: It is not a
[01:06:09] Paul Roetzer: new trend. I can very vividly recall being at a major marketing industry conference back in like 2018 or 19. And keep in mind, like, I started the Marketing Institute in 2016. So we’ve been in this game for a little while. And back in 2016 17, Mike and I spent a lot of time trying to find actual AI vendors doing legitimate AI tech.
[01:06:31] Paul Roetzer: And we had to deal with this all the time. It was like, what exactly are they doing? And so at this conference, I go past this one company that we knew not to be doing much with AI at the time. And they had changed their name, not technically, but like on their booth. They added AI to the end of their name and I walked past and thought, you just, you’re not doing anything with AI.
[01:06:53] Paul Roetzer: Like, what are you doing? And so they had decided, so I remember another, I won’t mention the software company, but they [01:07:00] actually ran focus groups to figure out if adding AI to, this is before ChatGPT, adding AI. in the description of their products would increase conversion rates with leads, and their data showed that it was like a 21 percent increase in conversion if they put AI in the messaging for
[01:07:19] Paul Roetzer: the product, even though it didn’t really have it.
[01:07:22] Paul Roetzer: It was using like natural language processing, which technically is a form of AI, but it’s a little bit of a stretch to say that you are an AI company or have an AI product if it’s using that. Microsoft Word’s been using that for 20 years. So, No, this is not new at all, but you do have to be very conscious of it and get good at assessing these vendors forthereal value they’re going to create for you.
[01:07:45] Mike Kaput: And we’re probably seeing, I would say, maybe a new iteration of this right after ChatGPT, It’s like, okay, everyone can say they have this brand new AI product when it’s really just got kind of like an API call, which is not [01:08:00] inherently a bad thing, but it’s sometimes oversold It’s like, Hey, we have this.
[01:08:05] Mike Kaput: Crazy AI engine. It’s like, well, okay. We have ChatGPT.
[01:08:08] Paul Roetzer: Can’t tell you how many times mike and I have been on calls where we say, so is this built on ChatGPT? Like, is
[01:08:15] Paul Roetzer: this built on OpenAI’s Yeah. Yeah. Because they’re presenting it as though they have their own model and it’s like, well, whose model are you actually using? And then it’s like, oh yeah, yeah, it’s OpenAI.
[01:08:25] Paul Roetzer: It’s like, again, it’s not a bad thing, but like, let’s just be transparent here. You didn’t build a model. Like, so yeah.
[01:08:34] Mike Kaput: So we had talked about kind of what these barriers are for, to adoption. Like, what are you seeing, I guess, anecdotally or personally as the biggest barriers for like CEOs?
[01:08:45] Mike Kaput: Like, what are they, if someone asks, what are they waiting for when it comes to AI?
[01:08:49] Paul Roetzer: I think, you know, I spent a lot of time with CEOs and presidents at different sized companies. And It’s often hard for those people [01:09:00] to become like the domain expert on a topic like this. It’s not their full time job. They got a lot of other things going on. And so the CEOs and presidents often rely on whomever it is in their organization.
[01:09:12] Paul Roetzer: They think should solve this. Big companies, it’s probably the CIO. If it’s outward facing products, it’s the CTO. they’re probably looking at IT and legal for guidance. It’s like. And they may not be the subject matter expert on this. And so that’s the challenge is that sometimes they’re not even maybe picking the right people.
[01:09:31] Paul Roetzer: So CIO is a naturaland a lot of times it can work out really well, but if the CIO then silos AI innovation within that department and doesn’t decentralize it to allow for innovation to come from.
[01:09:47] Paul Roetzer: other departments and areas, for example, not even inviting the CMO to be on an AI council, then the CEO and the presidents are kind of stuck with maybe not getting the best guidance and not [01:10:00] accelerating what’s possible internally.
[01:10:01] Paul Roetzer: And so, unfortunately, like the CEO and presidents need to set some time aside to develop some confidence.
[01:10:09] Paul Roetzer: In their understanding of this topic beyond just peripheral.
[01:10:13] Paul Roetzer: And I think that’s a key. So again, it goes back to literacy. It’s like, they, they have to have this knowledge. And I’ve done these talks where I’ll be in front of
[01:10:20] Paul Roetzer: 300 CEOs and you do this almost like intro to AI level talk. And you can just see their, their minds light up and this like, Oh my gosh, I get it now.
[01:10:32] Paul Roetzer: And then they’ll come up afterwards and say, okay, what do we do? I want to do that roadmap you talked about. I want to create an AI council because now they understand the importance and they can start to connect the dots. And I think they, you can do that in a 30 to 60 minute session. I’m not saying CEO has got to go spend.
[01:10:46] Paul Roetzer: 10 hours a month doing this. I’m just saying, get the right people in front of you to give you the right knowledge, so that you can then do what you do, be the leader of the strategy and the vision.
[01:10:55] Mike Kaput: All right, two final questions here, and then we are done. [01:11:00] wrapped up here. What advice would you give to a marketing student who has recently graduated and wants to pursue a career in marketing AI?
[01:11:08] Mike Kaput: And honestly, you could probably expand that advice to a traditional marketer that’s trying to break into or evolve their career.
[01:11:15] Paul Roetzer: Experiment a ton in your personal domain. So, you know, go use ChatGPT for everything. Go experiment with image generation, video generation. Like, get the experience that you can talk about in interviews. And then find the companies who actually are piloting and or scaling this stuff. You know, if you want to spend your career doing this, which I do think is the right call.
[01:11:36] Paul Roetzer: You want to be in environments that, support. innovation and they support experimentation and they are at least in the development of having a longer term plan for how AI is going to play a role in their products and services and operations.
[01:11:52] Paul Roetzer: You do not want to get into a company in a very conservative industry that doesn’t allow access to these tools and may not for [01:12:00] another year or two until all this is figured out.
[01:12:02] Paul Roetzer: That is going to set you back in your career. So if. If you want to be at the leading edge of this stuff, you’ve got to, you’ve got to match yourself with an organization that enables that to be possible.
[01:12:12] Mike Kaput: Alright, final question for today. One of the barriers as I’m leading AI implementation across my organization is I can’t find a good source for AI tools across departments. I have a pretty good idea of what’s out there for marketing, but I’m not sure where to find tools for other departments like HR, operations, finance, etc.
[01:12:33] Mike Kaput: How do you do your initial search for tools for specific use cases?
[01:12:38] Paul Roetzer: So, I mean, the way we do it is, I mean, we use CB Insights. We use CrunchBase, our two kind of tools we use to assess these technologies. but a lot of it, honestly, is just us staying in the loop on who’s getting funding and who they’re getting the funding from. So, you know, you have these standard venture capitalists and angel investors who have a [01:13:00] history of being pretty good judges of technology across different industries.
[01:13:04] Paul Roetzer: And you pay attention to which organizations they’re talking about. Now, if I was actually doing a project though, where I needed to find an HR software that does X, Y, or Z, and I’m proactively seeking that knowledge. I’m probably going to go through a lot of the same channels I would historically go through, you know, a G2 crowd where I go and look at who’s the leader in the space.
[01:13:24] Paul Roetzer: You’re going to probably look at the, you know, the, analyst reports from Forrester and Gartner, like, you’re going to go through these assessments, but at the end of the day, you, you actually, ideally, you want Demo the technology. You want to test it for yourself.
[01:13:37] Mike Kaput: Mhm.
[01:13:39] Paul Roetzer: our AI vendor assessment, we can put a link in the show notes.
[01:13:41] Paul Roetzer: We have a free template you can download that we featured in our marketing artificial intelligence book that helps people assess these technologies and whether or not they have viable AI capabilities, but the starting point for me, honestly, is often your existing tech stack. So if you’re in accounting or [01:14:00] HR operations, finance, whatever it is, Go to the companies you already have relationships with, already have contracts with, already through procurement and legal, and find out what AI capabilities they have or that they have on their roadmap in the near future.
[01:14:13] Paul Roetzer: Because they’re all building AI into their products, and many times that’s going to be the safer bet because, a lot of these startups are going to be gone in 12 months. They’ll get acquihired, they’re going to not find a product market fit, and they’ll run out of money. Um,
[01:14:29] Paul Roetzer: so unfortunately, while there’s tons of innovation in the startup world, a lot of the safe bets are to work with your existing vendors who are building AI capabilities in.
[01:14:37] Mike Kaput: All right, Paul, that was awesome. Thank you for walking through the key findings from the State of Marketing AI Report 2024 with us here today. As a quick reminder, stateofmarketingai. com, you can find the full report there and download it for yourself. also if you have not reviewed this podcast, we would love your [01:15:00] feedback either on this episode or the overall typical format.
[01:15:03] Mike Kaput: Uh, every review helps us get in front of more people and improve what we’re doing here. So Paul, thanks again. Really appreciate you answering all these questions and breaking down these trends for us.
[01:15:14] Paul Roetzer: Yeah.
[01:15:15] Paul Roetzer: great work putting the report together, Mike. And final reminder, get your MAICON tickets. Mike and I would love to see as many of you as possible in Cleveland, September 10th to the 12th. POD200, get you the 200 off, and it’s MAICON, MAICON.AI
[01:15:28] Paul Roetzer: Thanks for listening to The AI Show. Visit MarketingAIInstitute. com to continue your AI learning journey and join more than 60, 000 professionals and business leaders who have subscribed to the weekly newsletter, downloaded the AI blueprints, attended virtual and in person events, taken our online AI courses, and engaged in the Slack community.
[01:15:53] Paul Roetzer: Until next time, stay curious and explore [01:16:00] AI.