The Surprising Truth About AI Adoption in Marketing Teams

Reading Time: 28 minutes

What if everything you thought you knew about technology adoption in marketing was wrong? Imagine a world where C-suite executives are more comfortable with AI than digital natives. Well, according to groundbreaking new research from Lightricks and the American Marketing Association, that world is already here.

For decades, we’ve operated under the assumption that new technology adoption flows from the bottom up. Young professionals, fresh out of college, bring new tools and techniques to their organizations. But AI is completely flipping this script, creating an unprecedented divide in marketing teams that threatens both innovation and career growth.

The numbers are startling: while 61% of executives use AI weekly, only 42% of entry-level marketers do the same. Even more concerning? 65% of executives have received formal AI training, compared to just 34% of early-career marketers. This isn’t just a gap – it’s a canyon that’s growing wider every day.

Today, we’re joined by Corbett Drummey, a pioneer in the creator economy and AI space. As part of Lightricks, which recently partnered with the American Marketing Association on this groundbreaking research, Corbett brings unique insights into this shifting landscape. His experience leading Popular Pays through its successful acquisition by Lightricks, and his current work developing AI tools for brand safety, puts him at the intersection of marketing leadership and technological innovation.

AI in Marketing: Unpacked host Mike Allton asked Corbett Drummey about:

✨ Reversed Adoption Pattern: Traditional bottom-up technology adoption is being replaced by executive-led AI integration.

✨ Training Determines Success: The growing training gap between leadership and staff is becoming a critical career factor.

✨ Bridge The Divide: Organizations must actively work to democratize AI access and training across all levels.

Learn more about Corbett Drummey

Resources & Brands mentioned in this episode

This episode was sponsored by Lightricks, in partnership with the AMA.

Full Transcript

(lightly edited)

The Surprising Truth About AI Adoption in Marketing Teams with Corbett Drummey

[00:00:00] Corbett Drummey: The adoption curve here is definitely led by executives and it’s so, it’s so weird to look at because we’re used to the, the younger entry level folks driving that adoption curve. But instead, I think there’s one or two things going on here. Like I mentioned, I think people know that this is a very fast growing and still evolving product.

But I think one big thing underpinning that discrepancy between entry level and executive adoption. Is that the executive players in the space, I think they have a business perspective from their years in the industry, having gone through some changes, I think they know what’s coming, even if it’s not there yet.

And so I think entry level folks are using these tools and there’s some useful things, but there’s a lot of things that are still not quite ready for prime time. There’s, you know, there’s some warts and things that aren’t really working right in these early products. It’s still very early stage. And so it’s in beta for a lot of times, but executives, they know that that’s just the beginning.

And so I think they’re eyes on the ball with these new tools coming out.

[00:00:57] Mike Allton: Welcome to AI in Marketing: Unpacked, where we simplify AI for impactful marketing. I’m your host, Mike Allton here to guide you through the world of artificial intelligence and its transformative impact on marketing strategies. Each episode, we’ll break down AI concepts into manageable insights and explore practical applications that can supercharge your marketing efforts.

Whether you’re an experienced marketer just starting to explore the potential of AI, this podcast will equip you with the knowledge and tools you need to succeed. So tune in and let’s unlock the power of AI together.

Greetings program. Welcome back to AI in Marketing: Unpacked, where I selfishly use this time to pick the brains of experts at keeping up with and integrating or layering artificial intelligence into social media, content, advertising, search, and other areas of digital marketing. And you get to learn to subscribe to be shown how to prepare yourself and your brand for this AI revolution and come out ahead.

Now, what if everything you thought you knew about technology adoption and marketing was wrong? Imagine a world where C suite executives are more comfortable with AI than digital natives. Well, according to groundbreaking new research from Lightricks and the American Marketing Association, that world is already here for decades.

We’ve operated under the assumption that new technology adoption flows from the bottom up. Young professionals, fresh out of college, bring new tools and techniques to their organizations, but AI is completely flipping this script, creating an unprecedented divide in marketing teams that threatens both innovation and career growth.

The numbers are startling. While 77 percent of executives use AI weekly, only 43 percent of entry level marketers do the same. Even more concerning, 65 percent of executives have received full formal AI training compared to just 34 percent of early career marketers. This isn’t just a gap. It’s a canyon that’s growing wider every day.

But today we’re joined by Corbett Drummey, a pioneer in the creator economy and AI space as part of Lightricks, which recently partnered with the American Marketing Association on this groundbreaking research. Corbett brings unique insights into this shifting market landscape is experience leading popular page through a successful acquisition by Lightricks and his current work developing AI tools for brand safety puts him at the intersection of marketing leadership and technological innovation.

Hey, Corbett, welcome back to the show.

[00:03:19] Corbett Drummey: Thanks. It’s great to be back. Thanks, Mike.[00:03:21] Mike Allton: My pleasure. I’m so excited to have you here and to help us all kind of understand what is going on with A. I. And these executives and how it’s being adopted. And where I want to start is the research showed that this A. I. Adoption of marketing jumped from 73 percent to 90 percent in just a few months one year. What do you think is driving this dramatic acceleration?[00:03:44] Corbett Drummey: I mean, yeah, we all have seen it in our day to day lives, but it’s really crazy to see the stats of the overall usage in our industries. I think that big jump up to 90 percent it’s really for two things, two reasons.

Number one, I think that when it when I tools first came out, they really captivated people’s attention. But in the last year, we finally had very practical ways to start using them in our day to day workflows. So number one is just they have become useful. But I think there’s this increasing focus on AI this is different from other tools we’ve seen simply because executives, I think, notice where the trend line is going. And it’s also a product that’s changing and growing faster than anything else before. And so I think that adoption is basically we have some real world initial use cases for AI but then everyone knows more is coming, and so we’re paying attention.

[00:04:35] Mike Allton: And that is really interesting, because AI does seem to be different, right? We’ve talked about how, you know, younger people typically lead those technology adoptions, bringing in new tools, and they’re kind of willing to play around and test things. They’re willing to be wrong, when I think a lot of executives are not.

Why else do you think, though, that AI is so different?

[00:04:56] Corbett Drummey: First off, just to state that again, it is really different. I can’t think of anything similar in any technological shift. One thing that comes to mind for me is, for example, when I was starting my career in marketing and advertising over a decade ago there was of course a huge social social shift with like Instagram Twitter, et cetera being more and more important Facebook, of course.

And it felt like we were always as entry level teammates back then trying to push our brands to adopt or push our clients to adopt things talking about the importance of things. And it felt like the leadership was kind of stuck in. Ways of working with that, that they’ve been used to, but now it’s, it’s very different.

The, the adoption curve here is definitely led by executives and it’s so, it’s so weird to look at because we’re used to the, the younger entry level folks driving that adoption curve. But instead, I think there’s one or two things going on here. Like I mentioned I think people know that this is a very fast growing and still evolving product, but I think one big thing underpinning that discrepancy between entry level and executive adoption is that the executive players in the space, I think they have a business perspective from their years in industry.

Having gone through some changes, I think they know what’s coming, even if it’s not there yet. And so I think entry level folks are using these tools and there’s some useful things, but there’s a lot of things that are still not quite ready for prime time. There’s, you know, there’s some warts and things that aren’t really working right when these early products, it’s still very early stage.

And so it’s in beta for a lot of times, but executives, they know that that’s just the beginning. And so I think they’re, eyes on the ball with these new tools coming out. So yeah, I think it’s a mixture of business experience and the fact that the products aren’t really there yet for a lot of the times.

And that’s, what’s driving like the executive focus on adoption, even though the entry level teammates aren’t using it all the time yet.

[00:06:46] Mike Allton: I think that observation about experience is spot on. It was something I’ve been thinking about a lot as well. Generally speaking, executives are older. So they have more experience in business, but they also have a much more, a richer understanding of just history and society where we’ve gone and I think they can just feel that AI is different from, say, a brand new social network or or a new tool. I mean, they see that there’s just so much more depth in this technology, but there was one statistic that I want to drill down to a little bit more. And it, it goes beyond just the fact that more executives are using AI or understanding it, but they’re significantly more comfortable with AI, which really stood out to me.

And it was like 55 percent compared to entry level marketers, just 33%. What do you think explains that confidence gap?

[00:07:41] Corbett Drummey: You know, I think I think people are using it for different tasks depending on their job and you know, entry level teammates are using it for the day to day work and finding that it’s helpful but not transformative.

And I think that executive teammates are using it for different things. Like, I think execs are using it for strategy and collaboration reasons, not just, you know, content creation, etc. But I, I think I’d have to guess it’s also just a willingness to lean into it, knowing that it’s going to change everything about their work and so they need to get familiar with it.

So there’s this discrepancy in confidence as well as training. Executives have a lot more training in this, which is, again, very different from the norm. Usually people pick it up in their personal life, bring these tools to work, and this is completely flips the script here where executives are both teaching themselves and getting formal company training and are more like satisfied in their desire to learn about it, whereas there’s younger entry level folks who aren’t getting the training they want, as well as you know, are left to their own devices to learn about it.

So it’s a completely different on most yeah aspects of adoption and training versus traditional trends that we’ve seen in the past. I think,

[00:08:45] Mike Allton: I think that’s just an astute observation because as I think back to how I used AI initially, how the people in my circles my social circles, colleagues and friends and so on, who are, they’re not entry level marketers by any stretch, but we’re, we’re practitioners and technicians.

We’re the ones creating the blog content, the social posts and that sort of thing. And so of course that’s where our first minds went to when it came to using Chat GPT. Oh, it can help me write an Instagram caption. Oh, it can help me write an outline for a blog post, which it can do all those things.

But like I’ve said on the show many, many times, if you don’t put a lot of pre work into it, you’re not going to get great output. But if you ask it to sit with you and have a conversation about marketing strategy or business strategy or something like that, it’s remarkably good without a lot of pre work because it just has that total world knowledge. But one thing you mentioned there was the training. So let’s, let’s talk about that for a second because as you mentioned, we’re seeing the substantial disparity in training between leadership and staff. What do you think the implications are for marketing folks and career development?

[00:09:52] Corbett Drummey: Yep. I mean, there’s a few things there. One perspective is we should talk about what companies should do, knowing these stats. And the other is talking to teammates on the ground and talking about how they should be thinking of these things, knowing the stats that we’ve uncovered through the survey.

So for example one interesting stat is that for executives only 13 percent say that they want more training than they have, but for entry level folks, it’s about 27%. So more than double say that they want more training than they have access to. So that’s really important for, for, for both stakeholders here.

Companies should know that there is a desire for training, which. That never happens, right? Like no one ever says I want more training, but everyone knows that this is going to be important for our jobs and companies should be really receptive to offering formal training here. And it is really important how you use these tools.

One thing I would say is that a lot of times people use AI tools they, they don’t work and then they don’t try them for a long time, but things are changing so quickly that the same tools are completely different six months later. And so I think consistent training is required and companies should know there’s a latent desire for entry level teammates to get that training.

So if they hear anything, they should be responsive to that. On the converse angle, like I think that entry level teammates should advocate for training if they want it. 41 percent of entry level people are self directed in their training. So that’s the vector through which they learn the most.

Whereas for executives, 65 percent are learning from the company’s training. So it’s, it’s really different. We expect entry level people to be self directed, but I think, you know, when you see almost half of the teammates getting, you know, versus, you know double the amount on the, the executive side, getting company training.

I think that’s just something that we should point out. If you want training, advocate for it. And if you’re a company, consider offering it

[00:11:37] Mike Allton: either through the report or through your own experience. Do you have any indication of what that training should really look like? Is it a video training, read a book, listen to podcasts?

What, what should they be looking for?

[00:11:50] Corbett Drummey: You know, the, I would say that There are a few people in each organization that have a lot of expertise here. And one thing I’ve seen is that most people aren’t aware of the sheer different ways that AI can be useful. One random example is, you know, I use ChatGPT a lot for manipulating spreadsheets, you know, uploading a file and then asking it to change something.

And it’s like having a junior analyst you know, on, on your team. And it’s, it’s good enough at so many things, but it’s also good at, helping you you be good enough and to learn things and so a lot of times things break down organizations between different stakeholders So for example, I’m waiting on someone technical to do something this like AI really does shrink that gap where instead of me passing something off to someone who is a technical capability I can be good enough with AI to do it myself And so whether it’s like a little bit of coding a little bit of you know Spreadsheet manipulation a little bit of data analysis the the fact that you can you know you upload files and do all these things now most people aren’t aware of all the different ways you can use it So I’d say for training the number one thing just personally I would advocate for is highlighting various use cases because then once people see it, it’ll stick with them. But you know, I’d also ask companies be responsive And, and hear about what people want to learn more of.

Usually I don’t think people even know how good it is at so many different tasks.

[00:13:09] Mike Allton: Yeah, that’s exactly right. That’s actually been like a, a nonstop theme with this show. I mean, every, every episode we’ve tried to surface use cases like that. And I’m always, you know, being exposed to new ideas, new ways.

Either I see somebody else doing it, or it just occurs to me. And just a couple of weeks ago, I was trying to determine what the monthly Downloads for this podcast were and because I’m getting stats from three different places and none of them offer this monthly view. And I just wanted to see how I was progressing month over month.

So I was downloading the daily stats and I was going to import them into a spreadsheet and calculate the monthly totals and then get an average from that. And halfway through that project, which probably would have taken me an hour, I realized, duh, I can just throw the files into chat GPT and ask it, right?

Oh my gosh. And within seconds, not only did it have the answer, it gave me a cute graph so I could see how the things were progressing month over month.

[00:14:01] Corbett Drummey: So sometimes we get this interesting data back and we have the data and the interpretation is a little open. But one potential reason, for example, why executives have been adopting.

This is that they’re instead of individual contributors, they’re often used to collaboration and delegating things, et cetera. And it is this is like having a you know, an analyst across many different forms from data science to coding to design, et cetera. So I’m not technical across any of these fields like design and engineering.

But you can ask it for code. You can ask it for a quick design of something. And these are all prototypes. You really need experts to polish and finish the work. But if there’s one thing I think AI is really good for, it’s prototyping and I’d say also scaffolding. So, for example executives are often doing strategy work, and I can’t for the life of me sometimes remember certain things, but if you ask it for an outline, you know, humans are better at filling in the outline, but AI is better at, like, remembering pieces that you, so you don’t forget them and leave them out.

So I’d say those are two examples but, you know, for I do expect this gap to close just because I think it’s going to continue transforming our work. But it’s interesting seeing this, this gap. And I think training could help. So if you’re, if you’re a company, listening to this from executive I’d really lean into that for your team.

[00:15:14] Mike Allton: And one of the things that the data showed that stood out to me was that there were different concerns across different levels. Executives tended to worry about client expectations while entry level marketers might’ve been, Focusing on ethics and copyright. How do you think teams can bridge this perspective gap in AI adoption?[00:15:33] Corbett Drummey: I think both are really important. And so I think both sides can learn from the other. In terms of their concerns, as you mentioned, it makes sense why people are concerned with these. So for example executives being concerned about just will this work meet clients demands, even though they’re adopting it, they know that there’s gaps in what it can do, that it’s not perfect, that there are you know, hallucinations or problems.

And so I think that awareness is driving that. So definitely the top concern for executives are, Hey, you know, 46 percent are asking, is this work going to be acceptable for my client? The other part is they do, they do worry about. Will this work there? Will this these tools diminish my teammates in a creativity?

And I think that’s also really important to talk about, because if you’re early to AI, it’s very easy to let AI steer you into. I almost would call it like mid level work. Like the default response will be fairly average. And so you you need to know how to use it to make yourself better. And in AI assisted person will be better than someone without AI.

But I think executives are worried about you know, will people lean on this for as a crutch? And just will I get, you know, average or mid level results back from, you know, what you’re asking this is AI tools. So if execs are worried about is the work acceptable quality level? And, you know, will this diminish my teammates creativity?

On the other side junior teammates and entry level folks are thinking, well, okay, Is the work going to be, you know, good enough quality for, for my outputs, but they’re more concerned on things like bias and copyright issues and infringement issues which you’d think executives would be worried about, like executives are usually the ones worrying about legal stuff like that, but this might be a little bit of a generation thing of this is a, the entry level folks are more familiar with the creator economy, I’d say they grew up with it more and they’re thinking about, you know, where’s this training data coming from or or, or is it, yeah, is it going to be biased?

We’re living in a really you know, Interesting media environment to say the least but I’d say yeah, everyone’s concerned about quality and accuracy, but the difference is I’d say is Executives I think they they don’t want this to diminish people’s latent creativity and the entry level folks are just making sure hey This is are my outputs biased from you know, the writing I’m getting back or is it do I have to worry about copyright issues?

But it’s really weird to see that the copyright stuff didn’t appear as a top concern for executives

[00:17:45] Mike Allton: Yeah, and that all makes a lot of sense. That reflects a guest lecture that I was just giving this past week for Baruch College in New York City, and I was talking to these young marketers who are about to enter the workforce.

How about how they need to learn how to customize and personalize AI and give themselves an entire team of AI assistants as they go into new jobs, but also need to be aware of not being too reliant on AI. Folks, we’re talking with Corbett drumming about the massive differences between how executives and staff are adopting AI.

And I’ve got several more questions. You aren’t going to want to miss, but first a quick word from our sponsor.

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So Corbett, for the marketing leaders who are listening to us right now, and they want to figure out how to resolve some of these differences and just adopt AI across organization.

What role do you see them playing in democratizing AI access and training in particular in their organizations?

[00:19:45] Corbett Drummey: You know, I think, I think there’s, there’s two points here, although I’ve talked a lot about. You know, painting it as, as something really good, which I think it’s healthy to be, have an eye on the horizon.

I think first off executives could just make, I think it’s important to make sure you keep your ears open to the feedback you’re hearing from your entry level teammates and your individual contributors. So you know, there’s concerns that they’ll be bringing about how this might impact their day to day work.

And I think it’s important to listen to and Use that when communicating your own ideas on the importance of adopting these tools. But outside of listening to your teammates and their concerns, since they differ from, I think, what yours would be as a company executive I do come back to the training part because you know, executives are learning mostly, like, two thirds mostly from the company.

Half of them, more than half of them are learning from outside sources. But only a third are teaching themselves, and that completely flips on the, side. Most employees about where they learn th

Most of the magic from you know, it comes from seeing other people use it and how these in the workplace and so that that training is specific to your workplace, I think will go really far compared to what you might pick up on your own just from the Internet. And so one other note that we don’t we haven’t talked about, which is a little of a of a interesting wrinkle to this is that now in a post pandemic world.

Well, there is less in office work, and I think that one of the ways historically junior teammates have leveled up is they are in office and learning from people, and I think everyone loves a flexible work environment, but if you are completely remote, it’s very, it’s a lot less likely that you’re going to pick up these tips and tricks from your team.

And so I think that also might be a compounding factor in terms of One of the reasons why there’s this gulf and learning and or appreciation of these tools. So I’d say if you want to, if you’re a junior teammate and you want to you know, pick up the pace in terms of your, your adoption of this, I think you can, like I said, advocate for company training, but also just try to be around teammates who are using it.

And I think getting into an office environment can help. And just so you pick it up kind of by osmosis. And I’ve, I’ve learned a lot of tips and tricks around the office for different creative tools. That I would not have picked up by myself. So I think, I think the workplace context of the tools is important in terms of how people use them for things that would be in your day to day.

And just picking up by osmosis is another random point that’s worth mentioning.

[00:22:02] Mike Allton: That is a great point to mention. In fact, it was something we talked about in a previous episode with Ashley Gross and her kind of tip or recommendation for remote employees like myself. I’m in St. Louis, Missouri. I don’t have an Agorapulse employee within 500 miles of me.

So there is no option for me to go to any office. Our headquarters are in Paris, but what we do have is a vibrant Slack community. And, and her recommendation for every, every business was to have a Slack channel or someplace where people are. Conditioned to regularly go and share what they’re doing with AI recently.

Like I should go and share the thing I did with the spreadsheet, because I’m sure I’ve got coworkers who are also wrestling with spreadsheets now and then. And we’d love to have that recommendation. And I would love to know how they’re using AI and, and, you know,

[00:22:48] Corbett Drummey: That is an amazing recommendation. I’m very, we have a Slack channel for everything.

I’m very surprised that I’m not in one for that. We used to have a productivity channel around the pandemic because there’s so many tips and tricks when we started working remote briefly around the pandemic. But that’s a really great one because there’s so much you can do now. Every, every, It feels like every week there’s a new frontier model being released, et cetera.

As you know, Lightricks being a content company, we’re building our own AI tools from, you know, LTX studio, which is an amazing AI video platform to for Popular Pays. We, we made this really cool AI brand safety tool called safe collab. And we see cool uses in our Slack channel around our own tools and how you can use them.

But yeah, I mean, there’s all these periphery things. You learn there’s, there’s an AI for everything. If that’s, if you are remote, that’s a really good recommendation is to kind of condition the team to just be dropping in tips for that. And it really helps everyone move forward much faster.

[00:23:40] Mike Allton: And by the way, you know, we did an entire episode, you and I, Corbett, about the amazing things that you guys are doing with your tools and, The AI power development. So I’ll have a link to that in the show notes, because folks, if you’re doing anything with video or want to do anything with video, they have some amazing, amazing tools that you can look into.

I just, I kind of hinted at that at the outset and I needed to say more, but I also talked in the outset about that weekly usage statistic, and I don’t want to get your take on that 77 percent executives. Versus 53 percent entry level is really shocking to me. What specific AI tools or applications do you think that these executives are using?

Maybe that junior staff aren’t.

[00:24:20] Corbett Drummey: It’s a really good thing to talk about. First off, like you said, that discrepancy is really surprising. Again, I can’t think of any other trend where executives are using things on a weekly basis where entry level teammates aren’t for something so strategic as this but yeah, the usage, again, does differ.

For example in terms of the executives, it’s things around like collaboration. Everyone’s using it for writing both, both entry level and executives. That’s the number one use case. So I’d say the classic ChatGPT. But I think there’s a little bit of difference where I’ve seen a lot of people in leadership default to ChatGPT almost as like replacing Google.

And so I think. understanding that you can ask threads and follow up on it and keep context of a search is very different from how you Google things. And so I’d say, of course, writing is the top use case across the board, but execs are using it for things like design collaboration strategy and a few other random ones like audience targeting.

And so these are more like collaborative multivariate uses, whereas on the entry level, it’s like, you know, writing, brainstorming, content creation, et cetera. But the, the data that the weeklies is shocking. It’s 77 percent for execs and only 53 percent for entry level. I’d say on a personal basis, the best things you can do is try just defaulting for a week to ChatGPT for search results.

Now I, I, I mostly do that. Like three fourths of my own searches are through ChatGPT and not Google. And that’s a really good like entryway into it. It builds a habit and then you’ll find all these really cool ways you can branch off from that initial use case. Funny enough, I don’t use it for writing really.

I use it for scaffolding things but I don’t use it to write, but that is currently the top use case.

[00:25:57] Mike Allton: Yeah, that makes sense. I recall being on a company meeting a couple of weeks ago and in the course of the conversation, our CEO said, well, let’s just, let me look that up in chat GPT instead of a Google search.

And it was a little jarring to me that, that he was, he was doing that. And I realized, oh yeah, okay. More and more folks, that’s, that’s what they’re turning to as the default, because it’s giving them a set of a list of options. It’s just giving them the answer. But one of the interesting things also that I picked up on in the research report from, from you and AMA was that it indicated that 27 percent of the executives want to be in the driver’s seat.

And while that, that might sound like a low percentage, compare that to just 5 percent of entry level marketers. What does that tell us about the future of marketing careers?

[00:26:43] Corbett Drummey: Yeah, this, this is actually one of the more interesting points I really wanted to talk about. But yeah, going back to it again, there’s that hesitancy gap.

So. A lot of this could be due to training. It could be like just the broad awareness of where, where AI is helpful and where it’s going. But that stat is one of the most interesting ones around, you know, 27 percent of, of executives being okay or wanting AI in the driver’s seat with, with little human oversight and only 5 percent for entry level.

That that’s, of course, there’s a lot of things here that makes sense. For example, It might be entry level folks are worried about their job being disrupted if AI is primarily in the driver’s seat. I would, I would disagree, by the way. I think it’s increasing everyone’s productivity, but we don’t see it taking jobs.

It’s more of, you know, you should be worried about the teammate who’s using AI taking your job versus just AI itself taking your job. But there, there have been a few places where, you know, as I think execs see places where AI could be really helpful even without much human oversight. But one of the top use cases was audience targeting, for example there are certain things like that where it’s so complex that it’s hard for, for humans to really input things in, in time enough to really move the needle better than AI can.

And I’ll give you one example, like many, many people use Facebook ads. And for a while now, the most effective way of using it has been just kind of letting AI learn and serve things with, you know, not the same human oversight you’d be used to specifying your own audience. So that’s one where marketers are more used to, but more and more will be that.

I also want to shout out our team built, I think the first use case where I would strongly prefer only AI used like in the driver’s seat versus any, this is pretty wild, but when we really safe collab, I’ve seen clients have people spend four to six hours vetting a single creator. And we put that creator into our brand safety tool and it catches things the humans never could.

Like it can look back through years of audio, visual texts, et cetera, and highlight, you know an audio piece in a clip from two years ago or whatever. And that is the precision that humans can’t achieve. And so I like, you know, I think that human oversight is necessary to kind of, you know, approve accepted and deny results.

But that’s one where I don’t want humans doing that work. It’s both routine and they should be doing more strategic work, but also they’re not good enough at it. Like this is for AI. And so I think we’re seeing more and more of those cases. Things like targeting catching, you know, brand safety things now that these models are multimodal and can view audio, visual, text, et cetera.

There are growing cases of that, but I think, again, entry level might be worried about job displacement where in fact, I think, I think people should be more worried about not using these tools and not growing. Both as a company and personally, then, then being, you know like a lot of people are scared of adopting tools, but instead you should be scared of not adopting them is on my, my real honest take about it.

[00:29:29] Mike Allton: Yeah. That, that makes sense. I mentioned a moment ago that I’ve been talking to students at Baruch college. I’ve talked to students at Otterbein College. I’m talking to a group of students at Emory in a couple of weeks. And what’s interesting to me about each one of these instances is that I’m coming in as a guest lecturer to a general digital marketing course where they basically aren’t talking about AI. It’s not being taught. They’re not being formally trained. So how can, you know, marketers who are coming into the workforce or, you know, they’ve been there just for a couple of years, these early career, early entry marketers, how can they close this, this AI gap?

Do you think, especially if they’re not receiving formal training?

[00:30:10] Corbett Drummey: It’s a really tough question. I mean, podcasts like this, that’s like I think that I’d go back to try to, If you’re remote tools, like you said around having a community you’re in, whether it’s your colleagues at work or a community where people are sharing these, so you can get more exposure to it, but see what works best for you, whether it’s a great podcast on, on how marketers are using it.

on Slack, et cetera. Working with teammates you know, in proximity with them. So you can pick up these by default, the work habits. But it is a challenge and then, you know, advocating for more, more formal training. But yeah, it is. The one classic answer to is you can use AI to learn AI. And actually, interestingly, I’d say the most frequent use case for not the deepest I’ll go.

Like I go big. pretty deep on certain tasks like data analysis, et cetera, and content creation with AI. But my most frequent use case is using AI to learn about other things. And that could be random things I’ll, I’ll take a picture of and say, what is this? Or, you know, it could be quick facts I’m looking up, but I use it to learn about pretty serious topics too.

I’m not super qualified to read a lot of Papers, but you know, there’s all these papers coming out on on everything from a development to scientific research, etc. And you can use AI to summarize things and to be an expert in your field. And so I think you exposure for the day to day work tasks, but you can become.

pretty expert by using AI to kind of crawl dense information and help it make help it be accessible to you.

[00:31:33] Mike Allton: That is such a great point. You know, we, we talked lately about a notebook LM being able to feed it all kinds of PDFs and documents, and then have it generate a really fun and entertaining five minute podcast.

We listened to that. We’ll teach you or summarize, or you can even have questions with it back and forth but another great. Just a general use case, like you said, is if you’re being suddenly asked to do something new in your role that you’ve never done before. Maybe your team needs you to put on a webinar and you’ve never done a webinar or you’re going to a live event next month that you’ve never exhibited a live event will bring a on AI on and have a conversation with it and allow it to tell you.

Here’s the list of all the things you need to think about, because if you’ve never done it before, you’re not gonna be able to fill in that list very well. Now you can figure it all out once you have that list. Mhm. But AI can be a real asset there. I think

[00:32:21] Corbett Drummey: that’s exactly right. And that’s when I say scaffolding, that’s kind of what I mean around like that you’re interviewing for a job for a marketing brand manager role, and you only had a narrow background before, and this is a more broad role.

You can say, you know, if I’m making a marketing plan for X, Y, and Z, what should I consider? It’s not going to make you like the best tagline or the funniest. And it, you’ll have more creative idea in it, but it’s really good at making sure that you’re thinking of all the pieces along something, whether it’s a document, you’re drafting a plan, you’re crafting, et cetera.

So that that scaffolding use case is really powerful.

[00:32:52] Mike Allton: And one of the really interesting things for my last question for you, Corbett, this ongoing conversation that we’ve been having on this show and even outside the show is How is AI going to affect my job, my colleagues jobs, the makeup of my marketing department at my company, or the company overall?

Did the research tell you anything about changes in how marketing teams might be structured, the roles that might be necessary over the next few years?

[00:33:18] Corbett Drummey: We didn’t dive into that one specifically with the, the research in terms of asking marketers how their teams are changing, for example. But I’ve seen it day to day.

We’ve, we architected our marketing team. It’s making everyone more efficient. What’s crazy too, is it’s really hit the marketing landscape first, compared to any other space. Like AI will change everything about everyone’s jobs. But there are certain industries that are more regulated ranging from, you know things where you’re in physical product production to medicine, etc.

And content. It was kind of the earliest and wild wild west use cases of of AI impacting our day to day jobs The first tools were these LLMs and content creation tools that are really changing all of our day to day works. So I’d say We know that it’s gonna change everything about marketers roles and it won’t stop and we are also kind of the ground zero for that, for that change.

So it’s tough. It’s tough as a creator, as a marketer, as even someone building these tools to constantly have to learn the next thing or, you know, integrate the next library or model that’s come out. But I guess it’s better this than the other, which you don’t want to be in a field that’s totally static, but the pace is fast and we’ll get faster.

So the last thing I’d say on that on that part is I would really encourage everyone to use these tools for their own enrichment, like, you know, I don’t think I ever would have been able to dedicate the time to be a software engineer, for example with, with what I have today, but I have used these to make a very simple web app, and that’s, you know, I, I’m not a designer, but I’ve used this to make a, I’ve used LTX Studio to make a movie, and of the story I’ve always wanted to create.

So I think that this should enrich everyone. It’s, it’s tough to learn everything and it can feel exhausting at times to stay on top of things, but it can be really enriching and it can help you branch out into things that you might never thought possible. So I am an optimist about this stuff. I think that it’ll empower people, not replace them.

And they can be used in, in great ways. So to say, you know, stay optimistic about it, keep an eye out for where it can help you. We all should be looking out for making sure it. We’re using it in a, in a like ethical in ways that are productive and helpful, but keep an eye out that there are a ton of ways where it can be used in that, in that way.

There are a ton of great use cases for it.

[00:35:24] Mike Allton: What a great way to wrap up. Thank you so much, Corbett. This has been so insightful for folks who want to learn more about you or connect with you. Where can they go?[00:35:33] Corbett Drummey: So I would go to Lightricks. com because we have a whole suite of amazing products. And, but we’ll be posting about this survey.

We have a dedicated site with some really cool visualizations and graphics. It’s our survey with AMA, the American Marketing Association, but I would follow us on Twitter. We’re posting cool stuff all the time, ranging from our new products, these survey results, et cetera. But if you have a moment, check out the site because it has the, the coolest visualizations.

And you can also share this easily with your colleagues to you know, kind of spur them into action about some of the stuff we talked about today.

[00:36:04] Mike Allton: It’s terrific stuff. Like I said, we talked about it in a previous episode, so we’ll have a link to that episode. Everything that Corbett mentioned today, including the report, we’ll have linked in the show notes, check it out.

And by the way, don’t forget if this is your first foray into AI marketing and you’re kind of feeling overwhelmed by things like LLMs and Claude versus Gemini, I’ve got an AI marketing primer for you. It’s free. It’s in the show notes. It’ll help walk you through what all these terms and tactics mean and help you get.

Started on your journey into AI today. That’s all the time we’ve got for today, friends check us out in the next episode until then. Welcome to the grid.

Thanks for joining us on AI and marketing unpacked. I hope today’s episode has inspired you and given you actionable insights to integrate AI into your marketing strategies. If you enjoyed the show, please subscribe on your favorite podcast platform and consider leaving a review. We’d love to hear your thoughts and answer any questions you might have.

Don’t forget to join us next time as we continue to simplify AI and help you make a real impact in your marketing efforts until then keep innovating and see just how far AI can take your marketing. Thank you for listening and have a fantastic day.

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