How AI Will Impact the Way Marketers Work

Sara Payne [00:00:10]:

Welcome back to the Health Marketing Collective, where strong leadership meets marketing excellence. I'm your host, Sara Payne, and I'm bringing you fascinating conversations with some of the industry's top marketing minds. Today, we're diving into a hot topic, AI and its impact on marketing. This isn't a debate about whether AI will disrupt marketing. That ship has already sailed. AI is here to stay, and it's becoming a ubiquitous part of every marketing program and team. But the question on all of our minds is, how do we best leverage AI to help really level up our marketing programs in 2025? To help us answer that question, I'm thrilled to welcome Dale Bertrand, founder of Fire and Spark, a digital marketing agency. Dale has an incredible background in AI.

Sara Payne [00:00:52]:

In fact, it was the focus of his grad school studies. And he has a real passion for helping marketers use technology to really elevate the quality of their work. He consults and educates marketing professionals on the use of AI, and he's here to share some actionable insights and practical advice that will empower all of us as we head into 2025. So let's dive in. Welcome to the show, Dale.

Dale Bertrand [00:01:14]:

Well, thanks for having me.

Sara Payne [00:01:15]:

Yeah. I'm I'm thrilled to meet you, and I'm really eager to listen and learn from you today. I've followed some of your work previously. So I'm excited to have you here. And I wanted to start off with a conversation around one of your philosophies, which is that people should leverage AI to better their work, not replace it. And I wondered if you could start off by elaborating on that concept that you're, you know, so passionate about really using AI to better our work and not replace it.

Dale Bertrand [00:01:44]:

Well, yeah. This is something that I've I've talked about on stage a bunch, which is, like, using AI to do better work rather than to automate your work. A lot of times when people first start using AI, they think that, well, instead of writing emails, instead of writing blog posts, I can use AI to do that work for me instead of well, maybe you could spend the same amount of time doing that type of work, but you're gonna do it better. You're gonna write a better email. Maybe it maybe it's gonna be more comprehensive, or maybe it'll, be more attuned to the way that the recipient wants to hear the information or would better understand the information. But But you're spending the same amount of time on it, but you're just getting a better output. Like, I love the idea of doing better work or getting better results even if it's the same amount of time that you're spending on on the work. That's a different way of looking at the results that you're getting from using AI rather than just always thinking about AI in terms of efficiency or productivity or saving time.

Dale Bertrand [00:02:45]:

That's that's a dangerous way to look at AI Yeah. You know, rather than than just, like, doing better work or higher quality work or getting better results.

Sara Payne [00:02:56]:

Yeah. Absolutely. I love that because I think it's easy for any one of us to fall into that trap of focusing on efficiencies over quality. And, you know, on that note, you've really cautioned against that over automation, of those types of efficiency tasks because there could be that inherent degradation of of quality. And I don't know that anybody's gonna be surprised by that. I think most people would, you know, believe that there would be some degradation of quality, but I think it's a good reminder as we're having this conversation. And I wondered if you could share any specific examples where you've seen AI make some some errors or assumptions that, you know, were were a little bit alarming.

Dale Bertrand [00:03:38]:

Yeah. I mean, AI hallucinates. I I don't like the term hallucinate because it makes it sound like, hallucinations are always bad. Hallucinations can be creativity when that's what you're using the AI for. Like, when when you're using AI to help you brainstorm because maybe and and I'll give you a great example. For me, I do a lot of conference speaking. So at the beginning of the year, like in January, like it is now, I'm thinking about concepts for workshops, keynotes that I'm gonna do at conferences during the year. And I'll give the AI some examples.

Dale Bertrand [00:04:12]:

Like like, I had a technical career before I went into marketing. So I actually in my former life, I built a supercomputer for the US government. So I'll give that idea to AI, and I'll say, come up with some creative ideas for marketing keynotes at for marketing conferences based on, like, an in that an engineer would deliver who built a supercomputer for the US government. And I'll have it come up with creative ideas based on, like, marketing trends, 2025 marketing trends. And I want it to hallucinate. I want it to be very creative. I want it to talk about, things like, computer memory and how marketers need to remember. Just crazy things that it might come up with so that I can look at a long list of creative ideas and then pick out a few that I might be able to develop into marketing conference keynotes.

Dale Bertrand [00:04:57]:

That's creativity, not hallucination, but it's actually the same thing. The the dangerous hallucinations that we're always talking about are when we're asking generative AI like ChatTBT to come up with facts and it gets the facts wrong. That's that's the wrong way to use ChatTBT. We should never be doing that. But when we're using it for creativity to brainstorm and it comes up with something unique and novel, because it's it's really just applying randomness to to to synthesize creativity, that's actually a useful form of AI hallucination.

Sara Payne [00:05:32]:

Yeah. Absolutely. I love that distinction. I think that's an important one to make. And I think sort of the logical next question or pathway to go down here is to talk about trust. Right? Trust is a big factor here in the adoption of of AI into marketing programs. So what would you say, Dale, to marketing leaders who still might be skeptical about the adoption of AI into their programs?

Dale Bertrand [00:05:57]:

Well, it depends on what it is that they're skeptical about. Are they skeptical that I mean, there's so many things to be skeptical about, and and it's all valid. Right? Like, we have there are AI vendors that might be misusing the data, and, yes, we should be cautious about that. And then also employees that might be using it now when you with without your permission, and and you don't even know. There there are many organizations that have rules against using AI. And guess what? Your employees are using it anyway. And you might be skeptical about its capabilities because there are AI vendors that are promising the moon right now, and we all know that the capabilities they're promising can't possibly be true. It's just not possible.

Dale Bertrand [00:06:38]:

If it sounds too good to be true, then guess what? It is. It is. We we know that. Right? Like, we've been here before with all with many, many different technologies that have rolled out over the last 20 years. Like, we know that. So, like, yes, there are very good reasons to be skeptical. The problem is we don't want our skepticism to prevent us from adopting technologies that are going to be useful and help us to to get results and improve productivity and quality and all that good stuff that we want. So we do have to do the hard work as marketing leaders to figure out which technologies we should adopt, what skills our teams need, and how to deploy these tools and upscale our teams so that we're benefiting from these technologies.

Dale Bertrand [00:07:19]:

Because within the noise, there are some tools and skills that we need. We just need to figure out which ones they are.

Sara Payne [00:07:27]:

Yeah. Absolutely. In in preparation for this conversation, we were talking about sort of the the, you know, the list of, ways in which AI will affect, marketers most. And I know you have a strong perspective on that. So could you share, the different ways that you believe AI will impact marketers?

Dale Bertrand [00:07:46]:

Well, well, I'll tell you a story. Like, I started using I mean, I started with AI a long time ago because I I studied AI in grad school. So I was building out technology back then, so I was doing AI before ChatTBT. Before it was cool. Yeah. Yeah. Before it was cool. When ChatTBT came out, you know, I gave it to my team, and we were using it for content just like everybody was, and it didn't work.

Dale Bertrand [00:08:06]:

You know, you don't wanna use everybody by at this point has realized that you don't wanna be using ChatCPT to write blog articles. That's not the right thing. What we quickly figured out is that using it for creativity and brainstorming and ideation is is really can be useful. So if you're if you're trying to come up with creative ideas for campaigns for ad copy, if you're trying to come up with headlines, subject lines for emails, the that's those are that's really useful. And, you know, some people have, have said, you know, well, why do you need AI to help you write? Why don't you just write? Like, what what I found is that in some ways, sometimes, I'm doing more work and I'm spending more time than I was before AI, but I'm just getting a much, much better result. And I'll give you an example. One would be, like, updating persona documents. Like, I'm what what we used to do was we would we would, spend a bunch of time up front, interviewing, interviewing some customers, maybe having some conversations internally, putting together a persona document, and then using that for for years, to produce content and campaigns and all that good stuff, around that persona.

Dale Bertrand [00:09:23]:

Now we're able to much more frequently update persona documents based on emails that we receive from personas, based on conversations that we have from customer with customers, on the phone, based on transcripts that we receive from recorded conversations. We can we can almost, in real time, update persona documents because we have AI tools that can help us do it. And the way that we do that is we'll have a persona document, let's say, like, in Google Drive, and we'll have, a transcript from a recorded phone conversation. We'll give those two things to, in a in a large language model like ChatChippity or maybe Gemini, maybe Claude. And we'll ask it to suggest some updates to the persona document, and then we'll approve the ones that that we like. The the whole process takes maybe 5 or 10 minutes every time we do it. And then we apply 1 or 2 updates, and then we move on with our day. And we do but we do that on a more, you know Real time.

Dale Bertrand [00:10:21]:

Regular basis. Yeah. Almost real time. And so that's more time updating persona and margins than we had spent in the past, but we get a much, much better result.

Sara Payne [00:10:32]:

That's a great example.

Dale Bertrand [00:10:33]:

Of our personas.

Sara Payne [00:10:34]:

Of what you're talking about earlier, which is quality over efficiency. Right? It's this ability to be able to learn more about your audiences in real time and then apply that to the campaigns that you have in market or or going to be deploying in the, you know, the coming days or weeks.

Dale Bertrand [00:10:50]:

Exactly. And you wouldn't get there if you were just focused on efficiency. And if your leadership was only focused on, you know, how can I shrink my team? Or, you know, I've got 5 marketers on this campaign today. How do we make that for tomorrow? You'll never get there.

Sara Payne [00:11:05]:

That's fascinating. Do you have any other examples of of just sort of, really strategic ways to deploy AI that are giving you these quality gains that you shared in that example?

Dale Bertrand [00:11:21]:

Well, for me, when I'm doing thought leadership, I'm deploying content on a number of different channels. So it'll be email for me, it'll be email, LinkedIn, and then, YouTube videos. And I'll get feedback in the form of email replies and comments on the other 2 channels. What I'll do is I'll in the same way as I do with the persona example, I'll automatically update what like, whatever the concept is that I'm writing about based on that feedback that I'm getting. I wanna be careful here because I'm never asking the AI to write for me, but I am asking the AI to suggest updates, and then I do the writing. And I'm asking the AI to suggest updates based on the feedback that I'm getting, and those are email replies and comments. And I actually just did that this morning with something that I posted on LinkedIn where I got a bunch of reactions to to, basically, an idea that I had that I wrote about at length on LinkedIn. And I got maybe 30 comments from 30 different people that helped me refine the idea.

Dale Bertrand [00:12:22]:

And I gave the the LinkedIn post and the comments to AI, and I said, well, based on the reactions to this post, suggest some changes that I might make to help me refine this idea. And it and it and it did, and I didn't copy and paste. I just went back, and I refined what I had written based on the ones that I agreed with. And that really helped me. Right? So I'm doing more work, but I'm getting much better quality output. And and, eventually, what these ideas turn into for me is, keynotes that I do on stage. But you can see how I'm refining my ideas over time, and AI is helping.

Sara Payne [00:12:59]:

Yeah. And and I I love what you're saying here, and these are great, insights and inspirations for others to be able to to take forward and use in their their own programs as well. But you're absolutely right in that. That's actually still a lot of hard work. Right? Like, I I'm even thinking about all the copy paste you had to do from each of those LinkedIn comments. Right? Like, I don't even know that. Does LinkedIn have a little widget where you can download all the comments you got on a specific post and be able to upload? I mean right? Like, I know this is a tactical example, but that's that's hard work to to, in real time, take that feedback that you're receiving on a on a post.

Dale Bertrand [00:13:38]:

And Yeah. But the the realization I want you to make is the realization that I came to while I'm doing this, is that there's a difference between thinking and and what I'll call it tedium, which is, like, what I'm describing to you is, like, my brain hurts when I'm doing what I just described to you because I'm doing a lot more thinking and a lot less tedium. The AI is helping me to spend more time thinking through the concepts and writing about them. Because back in the day, I would write to think. But the reality is I was I was spending some of that writing time writing, and some of it just kinda like organizing, formatting, proofreading. That wasn't really thinking. That was writing writing. But the but the thinking writing was the was the part that I'm not giving up to AI because that was valuable.

Dale Bertrand [00:14:22]:

Like, when I'm when I'm thinking writing, I'm refining a concept, or I'm coming up with an idea for a marketing campaign, or I'm refining my persona, or I'm or I'm working on my messaging, or I'm I'm figuring out what what messaging is really gonna resonate. Like, that's the thinking that I can't give into AI. I'll never give that thinking to AI. But but everything else I was doing so what I discovered now that I'm kind of partnered with AI for a lot of what I do, that a lot of the stuff I did before AI did maybe I'm maybe half. I don't know how much, but maybe around half of what I was doing was actually tedium. And I can actually spend that time now doing real thinking, and that's why I'm getting better results.

Sara Payne [00:15:00]:

Right. Right. And I guess the point that I was making is, like, it's a choice. It is a conscious choice to be able to say, I'm going to I am going to slow down when what might seem to be tedious work, but I'm gonna make an intention intentional choice to take this feedback and insight that I'm getting and feed it to AI so that I can enhance the quality of what I'm doing. Right? Like, that's a very intentional choice, and that to me is a choice to, you know, not go the easy route. Right? It is a choice to enhance the quality, and that's what I mean by by hard work. Right? Like, you're you're you're choosing to go down that pathway because of this, you know, the the the belief and the strive for for better quality work.

Dale Bertrand [00:15:50]:

Yeah. Yeah. And and if instead you say you make a different choice, which is I'm going to use AI to create something that looks like a blog post, then you're not doing any of the hard work.

Sara Payne [00:16:00]:

And you're

Dale Bertrand [00:16:00]:

doing something that looks like a blog post. Right.

Sara Payne [00:16:04]:

Absolutely. We were also talking about, you know, that it's it's not only gonna impact AI, not only impact how marketers do their jobs, but also will affect the way that consumers will find products and services. Did you wanna comment on on that part of it just briefly, the the how consumers will find products and services?

Dale Bertrand [00:16:26]:

Yeah. I think this is a distinction that I always make because it frames the conversation well when we talk about AI. People are always asking me, like, how's AI gonna impact marketing? And it's gonna impact marketing in a bunch of different ways, and it's important to make the distinction. Like, AI is gonna change the way marketers do marketing, but it's also going to be applied to the algorithms that rule digital marketing. Like Yes. Like Google's algorithm and the social algorithms and email algorithms, like email filters. There's a lot of algorithms out there that are implementing AI, and that matters. But that's different from how marketers are gonna use AI.

Dale Bertrand [00:17:04]:

But then the other piece of it is that because of the way, software is implementing AI in so many different ways, consumers are going to find the information that they need to make purchase decisions around products and services, differently because of AI. And one way I would illustrate that is, like, going forward over the next year or 2, what I would expect is for this there to be this bifurcation around search platforms where there are traditional search platforms like Google that are that will be using AI. But these traditional Google type search platforms are gonna be used best by by consumers to make decisions, to decide between products, or to decide within a product category, to make a purchase decision, in other words. But then there's this other category of conversation. We'll call them, like, generative engines, generative AI platforms like chat gbt or perplexity that are more information engines, where if I wanna know how to tie a tie or to to change my oil or if I wanna if I want to understand the difference between socialism and communism, I would have a conversation with one of these generative AI search engines. Or if I'm planning a trip to Japan, and

Sara Payne [00:18:22]:

I wanna explain to it

Dale Bertrand [00:18:23]:

that I'm a family of 4, and I have teenagers, and they love nature. And I'm lactose intolerant when it comes to choosing restaurants, and I want an itinerary for 15 days. And and I give it 50 other details because I I wanna make sure that I get the right itinerary. I'm not gonna that's not a Google search. That that that doesn't look anything like a Google search. So there's there's 2 different types of search platforms, and the and consumers are just beginning to figure that out. But the technology is making it possible for consumers to to to go to 2 different types of places for 2 different types of information inquiries. I'm I'm I'm making up the language as I go here.

Sara Payne [00:19:06]:

Yeah. And you're you're so you're sort of alluding to the fact, Dale, that that we're not quite there yet. Right? Like, this is what's coming next. That's Consumers are just sort of starting to realize the difference there and that this will be coming. As you think about, you know, marketers prioritizing their their sort of channel strategies, that their budget spend for 2025, do you see, you know, as you're as you're consulting with folks, are you recommending any changes in, you know, how they're going to market with with various different, channels and the prioritization of that budget spend sort of based on some of this, you know, early indication of where this is going to go? Or is this gonna be, like, we're gonna be learning along the way and and sort of, like, verdict still out on exactly how that's gonna sort of impact the overall budget spend and where people are, communicating to reach their audiences.

Dale Bertrand [00:19:59]:

So in 2025, budgets are tight. They're I guess, what what what what our leadership wants is more more with less. Right? So, basically, we need to figure out how to get more from the the budget that we have and make sure that we can show that the resources that we are, that we're using are making an impact on the basically, making an impact on the metrics that our c suite cares about. Like, basically, a tangible impact that is measurable, and that's very hard. That's difficult with, what we would call, like, dark traffic, traffic that isn't measurable. And then, also, if we know that we need to spend money on brand marketing, but it it because it accelerates the performance marketing channels that are measurable, but it's it's sometimes hard to justify. So in 2025, when it comes to, like, the generative AI search channels that I was talking about, we want to start measuring the shift. We want to start, paying attention to where our audience is searching for information related to the services that we offer.

Dale Bertrand [00:21:25]:

And a lot of that is just asking them because it's not measurable. Yeah. It's just not all measurable. The mistake that we often make is that we we invest in the channels that we can measure. It's like searching where the light is.

Sara Payne [00:21:40]:

Right. Right.

Dale Bertrand [00:21:41]:

Like, if we can see it in GA 4, then that's where gonna where we're gonna put our dollars. But, the where the puck is is going in the analogy, there's, like, skating to where the puck is going. But, like, where where things are headed is that our customers are going to be using these generative AI platforms more and more, and that is just not measured. It's a conversation. It's not even a search. It's a conversation. So we're gonna discover when they start using when when they hit that tipping point. They're not there yet, but when they do hit that tipping point, we're gonna discover it by asking them.

Dale Bertrand [00:22:19]:

So we need to start putting those feelers out there in 2025. That's what 2025 is all about. So we put those feelers out there by making sure we're asking the right questions. And then when the point comes, which will be towards the end of 2025 going into 2026, then we need to be we need to make sure that we're we've got visibility in those platforms. Like, basically, our brand has visibility in the generative AI platforms. And that that's that's what we need to be working towards in 2025. But right now, in January 2025, we we still need to be optimizing for Google. Like, it's still Google is still, like, 80, 90% of the game when it comes to organic search.

Dale Bertrand [00:23:01]:

It it is shifting. And then the other thing that's important is, like, Google is going to win this game because they have the best technology. They already have everybody on their platform. Like, they're gonna win. The thing is we don't know what Google's gonna look like when they win because they they are going to own the generative AI Yeah. Search game, and they're gonna own the traditional search game. It's just we don't know what we need to do in order to optimize for both of those yet.

Sara Payne [00:23:28]:

Yeah. That's so fascinating, just to think about where we are today, how much has already evolved, and will continue to evolve at a very rapid pace. Obviously, Dale, marketers are gonna be on very different sort of ends of the spectrum or different points along this spectrum from an adoption standpoint. If a marketer listening today is sort of early on in integrating AI into their campaigns, do you have I know you've given a lot of great sort of tips already and advice already. Do you have any thoughts on on where they should prioritize to begin? And, obviously, this is somewhat of an unfair question because we don't know what their objectives are. Right? Like, we have to make some assumptions here. But in a general sense, where should people begin?

Dale Bertrand [00:24:17]:

So everyone's starting somewhere different. If you're just getting started, then just start. You know, start where you're at is really where what it comes down to. Like, if you if you're just getting started with it, then using it for anything, you'll you'll begin to learn some intuition around, what it's good for, what the limitations are, how how to use it. I think it's import and what we're talking about here is generative AI. There's more than just generative AI. There's also a predictive AI because you can use AI to predict a number of different things, which is which is also important. But but really starting to use it and getting some some intuition is important.

Dale Bertrand [00:24:53]:

If you've already been using AI, then what I would do is, talk to colleagues and join some groups, to make sure that you're asking colleagues what they're getting the most value out of in terms of tools or techniques, or methodologies around using AI. There's so many different tools and strategies out there that you've got to learn from a trusted colleague who is getting value from something. I follow AI for a living, and I only try things that I hear from somebody I trust who is getting value from something. Because I cannot just randomly try stuff that looks interesting. I would be trying literally hundreds of different things a day if if I were if I were to do that. So I I only try stuff that somebody I trust tells me is working for them. So that's what I recommend for people.

Sara Payne [00:25:49]:

So okay. Let's put that into real time practice here, and I'm gonna ask you, where is AI delivering the greatest value, for you? Again, I know you've given some great examples.

Dale Bertrand [00:26:00]:

Yeah. Yeah. Yeah.

Sara Payne [00:26:00]:

But do you have a couple you know, 1 or 2 more to to share with our audience today?

Dale Bertrand [00:26:05]:

Yeah. I mean, the tool tip for today is just this morning, I created a 10 minute video for my team, where I was showing them Google's deep research. And I don't know if anybody really knows about that tool at this point, but what it does is it does research on a topic for you. And it's the equivalent of paying somebody to do 4 or 5 hours of research on a topic across 30 or 40 different websites to research a topic. Now for example, if you wanted to research a public figure who does a lot of speaking on a very specific topic, let's say, parenting. Let's say there's a parenting speaker who knows a lot about parenting and you wanna know what does this person say about parenting when they speak and because I wanna learn all of it. It would find everything they've they've said, and it would find look. Go to 30 or 40 different websites, find all those pages, and it would compile a 6 or 7 page document on what they've said.

Dale Bertrand [00:27:06]:

Wow. And if if that's useful to you, then you would read that 6 or 7 page document, and you would learn it, and you wouldn't have to do any of that research. So what I found is that if the information you're looking for is available on the web across dozens of web pages, not 1, not 500, then this is a very useful tool because it will save you 3 or 4 hours of work. And so I made I've been using I've used it a dozen times in the last couple weeks, and it saved me 3 or 4 hours each time I've used it for various different things. So I made a video for my team this morning, and I said, hey, guys. You should really be using this tool because it's it's been it's been working really well for me. Now you need Google Gemini, which I believe

Sara Payne [00:27:56]:

you I was gonna ask you.

Dale Bertrand [00:27:57]:

Yeah. In in order to use it, but it's $20 a month. So it's a no brainer for me.

Sara Payne [00:28:04]:

Absolutely.

Dale Bertrand [00:28:05]:

So, I that's my tool of the day.

Sara Payne [00:28:09]:

Love that one. I we're just starting to experiment more and more with with Gemini on our team here. Seems to be far superior from a from a visual standpoint in terms of what can it it can produce comparatively to ChatGPT, but this was a new, capability I hadn't heard of yet. Obviously, experimenting with using ChatGPT for similar, types of, you know, queries and and outputs, but, this seems superior for sure. And, obviously, assumption here is that those channels have to be open API. Right? Like, LinkedIn would be excluded from, that that search, if you will.

Dale Bertrand [00:28:49]:

It it it needs to be information that you can find in Google. Interesting. I think that's true.

Sara Payne [00:28:57]:

I know. With all these things, they change so quickly. And and right here, I'm I'm putting you to the to the test on a tool that you've just started to to learn. But, no, I really appreciate you sharing that example, so folks can get in there and start playing around with it. Any others come to mind?

Dale Bertrand [00:29:12]:

I'm trying to think I mean, very similar to that one. I mean, I use notebook l m. But have you used note notebook l m? I don't know if that one's another one that people know about or if it's new.

Sara Payne [00:29:21]:

I don't know about it, but I I

Dale Bertrand [00:29:23]:

Well, same type of thing. You would love it. You you put any type of information. I'll I'll tell you the last time I used it. The last time I used it, I, I found a blog that had a bunch of useful information on it. And there were 10 articles on the blog I wanted to read, but I didn't have time. So I took all 10 articles and I gave it to notebook l m. And what notebook l m does is it makes a 20 minute podcast out of the articles.

Dale Bertrand [00:29:50]:

And I listened to the to that podcast on double speed. And what's really cool about the podcast is that it's 2 people talking to each other. So it's insanely easy to digest compared to reading 10 technical blog articles.

Sara Payne [00:30:08]:

Right. Or just a robotic Siri voice, right, talking to you. Like, this is a conversation I want in nature.

Dale Bertrand [00:30:15]:

Yes. But I wanna give you an appreciation of how how, easy to digest this is. So when when I was in grad school, we wrote technical papers on AI. And one of the papers I wrote 25 years ago, I went back to read it, and I didn't understand it. Like, it was it was, like, really. So I gave it to notebook l m, and it explained it to me. And this is a paper that I wrote in grad school 25 years ago. So it's like so if there's if there's a a technical paper that is, like, well beyond you because it was written by a PhD, you can give it to notebook l m, and it'll give you a podcast version of it.

Dale Bertrand [00:30:55]:

Like, imagine if you were listening to, like, an a New York Times podcast, and they explained a research paper that had been written by an MIT PhD on some esoteric topic. They wouldn't they wouldn't be for, a PhD audience. It would be for a general audience, and you would expect to be able to understand it. Right? Yeah. That's what this tool does. Like, that's how powerful it is.

Sara Payne [00:31:20]:

This is education in 2025, folks. I mean, this is, like, the the 2025 version of of cliff notes, but for extremely technical topics.

Dale Bertrand [00:31:29]:

So imagine a world where you could understand any technical academic paper in 20 minutes in a fun conversational format that feels like a podcast written for the public. Like, that's that unlocks a lot. Like, you gotta wrap your head around that. That unlocks a lot. So that's so that's, I've been using it a ton because there's there's a lot of stuff that I there's just just a lot that I that just was inaccessible beforehand. And I'm a pretty technical person. You know? I've I've studied, yeah, I'm a pretty technical person. And there there was a bunch out there that was just too dense and too un like, I just couldn't it was just inaccessible to me.

Dale Bertrand [00:32:12]:

Right? But then notebook LM just unlocks it like that Yeah. Because of the format.

Sara Payne [00:32:18]:

So great. So great. I'm definitely gonna check that one out. Alright, Dale. We're heading into my favorite part of the show, the quick fire round. I'm gonna throw out some rapid questions, and and you give us your best answers. First question, what's one way marketers can use AI that most aren't thinking about yet?

Dale Bertrand [00:32:33]:

To learn anything. You can have a conversation about any book even if, you don't give it the book. You can have a conversation with a book that you you you never even bought.

Sara Payne [00:32:45]:

Love that. What's the biggest myth about AI and marketing that you'd like to debunk?

Dale Bertrand [00:32:50]:

That it's gonna take marketers jobs. Like, it's already creating new jobs in marketing.

Sara Payne [00:32:55]:

So great. Love that. What's the one piece of advice you'd give to marketing leaders as they embrace AI?

Dale Bertrand [00:33:03]:

They need to be the ones learning it, driving it, and begging their team to adopt it.

Sara Payne [00:33:10]:

God, that's such great advice. Okay. Last question. Give us one bold prediction for how AI will shape marketing over the next 3 year let's say 3 years.

Dale Bertrand [00:33:20]:

We won't even be talking about it in 3 years. It's gonna be like breathing oxygen. Yes. So imagine if I walked into the room with you and said, hey. Did you breathe oxygen today? Right.

Sara Payne [00:33:33]:

Great point. Great point. Well, Dale, I've learned so much today. This has been an incredible conversation. Thanks so much for sharing your insights. Where can our audience find more of your work or or connect with you?

Dale Bertrand [00:33:46]:

Well, I try to post daily on LinkedIn, so let's connect on LinkedIn.

Sara Payne [00:33:50]:

Love it.

Dale Bertrand [00:33:51]:

And shoot me a note if you have any questions about anything related to AI or SEO. That's that's what I write about.

Sara Payne [00:33:57]:

Fantastic. Thank you, Dale, again for being here today, and thanks to our listeners for joining us. And if you found this episode helpful, don't forget to subscribe wherever you get your podcasts. That's it for today's episode of the Health Marketing Collective, where strong leadership meets marketing excellence because the future of health care depends on it. We'll see you next time.