The Role of AI in Marketing A Conversation with Katie Robbert

The Role of AI in Agency Marketing: A Conversation with Katie Robbert

Artificial intelligence (AI) is transforming businesses, including marketing agencies. To understand how AI will impact agency marketing, Brooke Sellas of the Marketing Agency Show recently spoke with Katie Robert, CEO of Trust Insights, on their podcast.

How to Get Your Agency Ready to Use AI

Can’t see anything? Watch it on YouTube here.

Katie has extensive experience helping companies implement AI and manage organizational change. At Trust Insights, they use predictive algorithms, machine learning, and AI to help businesses make better decisions faster.

They discussed common misconceptions about AI in marketing, such as the fear that it will replace human jobs. While AI can automate certain tasks, the human touch remains essential in marketing. AI is powered by data and math equations—it doesn’t actually “understand” anything.

Some key benefits of AI in marketing include:

  • Generating transcripts and summaries from audio and video content. This allows repurposing content more efficiently.
  • Curating competitive research. AI can quickly compile lists of competitors’ podcasts, for example, to analyze.
  • Processing natural language and extracting data from conversations. This automates what previously required manual coding.

However, companies should be thoughtful in implementing AI. As Katie explained, technology should be the last P in the “5 Ps” framework: Purpose, People, Process, Platform, and Performance. Start by identifying your goals and team capabilities before choosing tools.

It’s also crucial to ensure data privacy when using AI. Generative models may share your inputs unless properly configured.

For marketers to leverage AI, curiosity and critical thinking matter more than technical skills. Understanding the basics of how models like ChatGPT work will soon be expected. Agency owners should also prepare for AI to disrupt their billing models and hiring needs.

The future of marketing lies in embracing human-AI collaboration. As Katie said, “AI won’t take your job. Someone who knows how to use AI will take your job.” Rather than fearing replacement, focus on enhancing what you offer.

The above summary was generated by AI using a transcript of the interview.

Machine-Generated Transcript

What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for watching the video.

Brooke: The big question you need to ask is, will artificial intelligence enhance our business or not? Because it’s not going to enhance every single business.

Today I’m excited to be joined by marketer extraordinaire, Katie Robbert. Katie is the CEO of Trust Insights, a management agency with extensive experience in artificial intelligence marketing, organizational behavior and predictive algorithms. They use things like predictive algorithms, machine learning and artificial intelligence to help businesses make better decisions faster. At Trust Insights, they light up the dark data.

Katie, welcome to the show.

Katie: Brooke, thanks for having me. I don’t know how we’re going to get through this without just giggling the whole time.

Brooke: I know, this is bad. Like Katie’s that person who you’re not allowed to sit, or I’m not allowed to sit next to during meetings serious because all we would do is like giggle.

Katie: That’s because I can’t take anything seriously. I mean, I should. I mean, everything you just listed off that we do in Trust Insights, like I do take seriously, but not that seriously.

Brooke: Oh, please. I know you way too well for that. So like, let’s get into it then. And I want you to tell everybody first, why did you and Chris Penn, your partner, decide to start Trust Insights? Like, what was the catalyst for that?

Katie: So the short version is that the agency that we were working at, the skills, the things that Chris and I were doing were very quickly outgrowing the services that the agency wanted to offer. So they wanted to continue to offer more traditional digital marketing, which was fine. So they did a lot of content marketing and digital ads and PR. And Chris was very deep into AI already at that time. And that was about seven years ago. And he was already working on predictive forecasting, already working on a lot of machine learning and natural language processing. And there just wasn’t an appetite for it with our clients through the agency.

And so we were feeling burnt out. He was on the road all the time, doing pitches and new business. I was managing the team, which I love doing, but the team was also growing sort of restless because the work was very redundant and uninteresting to them. They wanted to do more of what Chris was doing. And so there came an opportunity for Chris and I to make our exit when the company that we worked for was acquired and the direction of the company was changing. And so we decided at that point that it was the right time to take a risk and try to do this on our own.

Brooke: I love it. I think that’s a great story. And I think that’s how a lot of us make the jump, right? Something kind of like is the catalyst or pushes us into like jumping off and like just going for it.

So before we get really into the nitty gritty, I want you to explain digital transformation. I feel like we should do the Pee-wee Herman like, woo, ’cause it’s such a buzzword, right? But you have a background in digital transformation and artificial, artificial intelligence. Can you just briefly tell our listeners or are people who are watching what that background came from and how you got there?

Katie: Yeah, so digital transformation is really just another way of saying, change management, organizational behavior. And so I spent a long time building and managing teams at a company where the teams didn’t exist. And so I worked at a company that made a transition from clinical research to commercial products. And so in that transition, they had to hire and build out a development team. They had to hire and build out sales and marketing teams. They had to hire and build out creative and UX teams and epidemiology teams and research teams and all those things. And I was there and participated in all of that. As the head of the product that I owned, I played a big role in shaping those teams. And that’s where I really cut my teeth on organizational behavior.

And what I learned through that process is that if you don’t have the right people in the right roles, it doesn’t matter what your end goal is. It doesn’t matter what technology you’re using or what processes you develop. And so when we think about digital transformation, it’s people, process and technology. The challenge that I see in the industry as a whole is that there’s way too much emphasis on technology and not enough emphasis on people, which is why I adapted that simple framework from digital transformation to my own, which I call the five P’s, very uncreative, but marketers like alliteration.

Brooke: We do.

Katie: And so it’s purpose, people, process, platform, performance, because the other challenge I saw with digital transformation was that there was no real way to measure success, especially when you’re trying to measure success around changing your organization. So how do you know you did the thing? And when I approach a project using the five P’s, people, the second P is the one that I spend the most time on. Because if your team doesn’t know why they need to use a new piece of technology or what’s in it for them, what does it mean for them long-term? What role do they play? Even if it’s a small one, they’re not going to take ownership of the process. They’re not going to want to use a new platform and your performance is going to suffer.

Brooke: I love that. That’s a great one. Write that one down, folks, because I think that’s really important. And I also think that when we do talk about any sort of transformation, whether it’s digital or otherwise, it’s so important to have the right butts in the right seats is the terminology I use. Excuse my Southern-ness. But yeah, I think a lot of people do put emphasis on the tech and not necessarily the people, and that could go really wrong really quickly.

So can you also do the same thing you did there and just give me the most straightforward explanation you can of artificial intelligence? Because I’m sure most of the people who are going to be listening or watching understand it and have heard about it at least. But for those who are kind of like a little bit shy about artificial intelligence, what would you say is the most straightforward way to explain it to marketing people?

Katie: So artificial intelligence is just a series of map equations. There’s three main categories of artificial intelligence. And I had to come up with my own acronym so that I could remember what they were. And so the acronym ironically is FOG, as in my foggy brain, ’cause I can never remember it. But it’s F-O-G. So there’s the three branches are find, organize and generate. So for artificial intelligence to work, you need to find information, data, quantitative and qualitative. You need to organize it and then you can generate with it. And so a lot of what people are talking about right now is the third branch, which is generative AI, where you’re creating something that new or you’re editing your content or you’re having a conversation with chat GPT thinking that you’re actually talking to a human, but you’re really talking to a series of math equations. So artificial intelligence is math that continues to quote unquote get smarter as it learns more. And so the more data, the more information you give to the large learning model, the system, the database, whatever you want to call it, the more it, and this is where it’s confusing, the more it understands. And by understands, it just means it’s taking in more information. It’s not becoming sentient and understanding how to be human.

Brooke: So like, seeing the patterns, right? It starts to develop like pattern recognition, right?

Katie: That’s exactly it. So if you think about something like predictive texts, so if you’re texting your friends on your phone, predictive text is using pattern recognition to know how you talk. And so for me, I tend to curse a lot. And so my phone recognized that pattern and stopped correcting certain words.

Brooke: Ducking.

Katie: Ducking.

Brooke: Ducking.

Katie: And cheat.

Brooke: Oh, did you see that actually Apple is making an update that auto correct will not change ducking. It will use the real word.

Katie: The real word.

Brooke: Which we won’t say here, but you know what we’re getting at.

Katie: Exactly.

Brooke: Okay, so now we know what digital transformation is. We know what artificial intelligence is. How would you assess the current state of marketing when it comes to AI readiness? Let’s just say for the average marketing agency, right? Just the middle guys, what do you think is the potential for AI readiness?

Katie: Not great. And I say that not because AI isn’t going to transform a lot of companies and marketing teams, but it’s a different skillset. And so you may already have some of the skillsets on your team. And when I think about the 5P structure, I really focus on the people. And so maybe you have someone who is a content writer, but unless you sort of do that assessment, you don’t know that they actually have a passion for development and coding. And so maybe you already have that person who could learn artificial intelligence. If you have a team that is not mathematically inclined or statistically inclined, it’s going to be difficult to use artificial intelligence ’cause there’s a lot of that that goes into it.

Now, the good news is that companies are popping up every day. I’ll be interested to see how much of them sort of stand the test of time, but there are connectors and interfaces that didn’t exist even a few months ago for people who want to use AI, but don’t want to have to hand code or use open source information in order to build these processes. What I would recommend for a company that’s trying to bring artificial intelligence into their company and not just check the box to say, we use AI, is to really challenge the question of what is the purpose that this is going to serve? How is it going to enhance what we do? How is it going to help our customers? And you may find that it’s not even artificial intelligence that you’re looking for. You’re just looking for a little bit of automation.

Brooke: That’s a great distinction. Yeah, because it’s not the same.

Katie: It’s not the same.

Brooke: So let’s start with the most common misconceptions that you think a lot of marketing agencies or fears that marketing agencies have right now when we talk about digital transformation and or adding AI to their operations.

Katie: The number one question, I feel like this has been floating around for a few years is will AI take my job? And the answer is no, AI won’t take your job. Someone who knows how to use AI will take your job. And so it’s a matter of, you don’t have to be an AI expert, but you need to understand just the basic principles of it, what it can and can’t do. And I think that there’s a lot of concern, especially for content writers, content marketers, and generators and creators of, well, if AI can write a blog post, why do they even need me? Well, AI can write a halfway decent first draft of a blog post, but it’s not, I would not recommend that you just go ahead and publish that on your website. And there’s, I don’t want to go too far down the rabbit hole, but there’s a lot of reasons why using AI generated content is a bad idea. Not only for, you lose that human touch, but then you run into potential copyright issues. A lot of the search algorithms will ding you negatively for if they recognize it as AI generated content. And then you also sort of lose that trust with your customers that they’re no longer talking to a person, which I know Brooke, is something you’re very passionate about.

Brooke: Definitely, but like, let’s just go slightly down the rabbit hole. I want to add to the US Copyright Administration, I forget the exact name, but they actually came out in March and they said that any content that is created with artificial intelligence, you can’t claim as your own. What’s the word I’m looking for? You can’t, you don’t own that content. So I think that’s something that business owners should really pay attention to. Obviously the content that you write for your site should be owned by you, that should be your IP. So yeah, just a little note there, but give me like the top three reasons why, maybe that’s one of them, I don’t know, why businesses shouldn’t just write a blog post in ChatGPT and publish it to their site, just like that.

Katie: Well, one of the things that is becoming better understood but wasn’t well understood when a site like ChatGPT launched and this, you know, a lot of this will be different in the next, you know, six to 12 months, is that the data that powers something like ChatGPT, there’s only so much history there. So one of the exercises that we did to demonstrate that was we created a prompt saying, you know, write a blog post about the, you know, top 10, you know, ways to handle SEO in 2023. And the 10 ways that came back were out of date by about five years.

Brooke: Wow.

Katie: And so one of, so I think the answer to that question is probably the number one thing is the information that you’re getting out of these systems may be out of date and/or incorrect. If you’re using something like ChatGPT, you don’t necessarily have sources. It doesn’t tell you where it’s getting the data. If you use Bard, this built into Bing, then it can tell you where it got the source information from, but it still may not be what you’re looking for. And so it’s, if you have to do that research anyway, do it on your own versus relying on a third party tool and then having to go double check that information as well. It just creates more work for you. And it’s not really saving the time, which is the whole point of using these tools.

Brooke: Yeah. I mean, I don’t know if you’ve done this, but I did the exercising, exercise, I hate exercising. I did the exercise of asking ChatGPT to write a bio, you know, a professional bio for Brooke Ellis. And I mean, it included all kinds of stuff that wasn’t true. I was like, wow, I’m so accomplished, but like half of it wasn’t true. So I think, you know, if you haven’t done that yet, definitely do that exercise because I think that will be very eye-opening ’cause obviously you know what you’ve done, who you are, as to how wrong some of the information is that it returns.

Katie: Yeah, I actually did do that exercise and ChatGPT is convinced that I’m a professor at Rutgers University. But that’s sort of the other side of it is that the data in ChatGPT as of today, and this will change, is only as recent as 2021. And so it doesn’t have that historical knowledge. So if you accomplish things in your career five, 10 years ago, the system doesn’t know about it. Conversely, if you are newer to your career, the system probably doesn’t know about it. So there’s a lot of gaps in the information. And so it’s good at writing general things. It’s good as a starting off point, but I wouldn’t use it as the be all end all. And I would like to believe that a lot of marketers aren’t using it that way, but I’m sure there are some who are.

Brooke: Yeah, unfortunately, I think there probably are some who are using it that way. And I’m sure they’ll learn quickly that that’s probably not the best way to do it.

So let’s flip the script and talk about some of the benefits that you think artificial intelligence and or really putting an emphasis on digital transformation can bring to a marketing agency. And can you provide any examples of maybe some of the clients that you’ve worked with at Trust Insights or like a fun story, like a hero story?

Katie: So I think that some of the things that artificial intelligence are really good at are the quote unquote unsexy things. So generating transcripts or cleaning up a transcript is a really good use case. And so if you’re not using AI, like a system like Otter for example, to generate your transcripts, summarize those transcripts, then you’re definitely missing the boat on a really good use case for artificial intelligence.

We do at Trust Insights, we do a lot of recordings, our podcasts, our live stream, our webinars, our speaking engagements. There’s video and audio for all of those things. And we use a system like Otter to generate the transcripts. And then we use a system like ChatGPT to clean up the transcript.

Brooke: Interesting.

Katie: And so at no point have we the human put our hands on the thing, but we can then take that content ’cause it’s now a piece of long form text and repurpose it, include it with the video, include it with the audio, include it as a standalone blog post. And so we’ve now transformed this piece of content into five or six different pieces of content all without having to do anything. And so it’s just extending the life of a single piece of content by using AI to do those things that a person would otherwise manually have to do.

Brooke: And that’s Otter AI, right? It’s O-T-T-E-R.AI, right?

Katie: That’s right.

Brooke: Yeah, it’s a really good service. We’ve been using it for a few years and are very heavily reliant on it. Every Thursday at 1 p.m. when we do our live stream, we always take the transcript from that, turn it into long form content, but we also export the transcript, bring it back into our video to generate the closed captions because it’s easier for us to take control over that because then we can correct the content versus relying on the AI from a system like YouTube or another video provider to, you know, mangle my last name like it always does.

Katie: Are you Robert?

Brooke: It’s usually Robear, like R-O-W-B-E-A-R.

Katie: Oh, okay.

Brooke: And I’m like, well, it’s close enough, I guess.

Katie: Close.

Brooke: So you do want to have some control over the content and using systems like that are hugely time-saving.

Katie: It can help you start some of that research. We were doing a live stream yesterday and we asked both ChatGT and Bard, just as an example, like, what are the top 10 marketing podcasts right now? And then one system came up with one list, one system came up with a different list. And so what we would do from there is start to cross-reference those lists and figure out, okay, here’s our short list of podcasts that we want to learn about. Let’s go ahead and start doing more research. If we were launching our own podcast from scratch, we would then at least have a starting point to sort of do that competitive analysis for.

Brooke: That gives me such a great idea to do that for this show. I’m like, oh, that’s a good, let me write that down real fast ’cause that’s a really cool idea. I like that a lot.

So, I mean, there’s so many advantages to, obviously, using AI and to getting on board with digital transformation, but I’m sure you’ve seen some common hurdles that companies face or agencies face as they’re trying to implement AI into their processes. So what have you seen, like the most common mistakes or hurdles, and then how did you help that client or person overcome that hurdle?

Katie: So in terms of, so you’re calling it digital transformation. I usually refer to it as change management, which is really what it is because digital transformation assumes that you’re really focusing on the technology. And change management is more of a holistic, focusing on the people in the process. And where it goes wrong, and I’m actually in the process of writing about this, is that people choose the technology first and then try to retrofit in their people and their processes. And it really needs to be the opposite. Technology should be the last thing you’re considering if you’re undergoing this kind of change management or digital transformation. It’s the last thing you should be considering.

There’s a lot of shiny objects out there. There are, I think the MarTech list came out recently. It’s the MarTech 11,038. And so there are 11,038, as of a few months ago, and that’s probably more, tools that you can include in your tech stack. And so it’s an overwhelming amount of tools and every tool does slightly different things. You should be choosing your technology last. It should be the last thing you consider.

So you need to do your, go through the first few P’s. So what is your purpose? What is the problem you are trying to solve? What problem will a new piece of technology solve? What are the gaps? What are the challenges, the pain points? Go through that whole exercise. And then you need to go through your skills assessment. Who do I have on my team currently? Do I have to hire full-time employees? Can I get away with contracts? Do I bring on an agency like Trust Insights to fill in some of these gaps? Do I bring on an agency like B Squared to fill in some of these gaps? But you need to do that assessment first.

And then you can say, okay, here’s everything I know. Now I can go ahead and choose a technology, a platform, to meet the needs that I’ve outlined. Because you also want to see what processes do I already have in place? Am I starting from scratch? Do I already have a repeatable process that I can build on? Is this something that I can automate? How am I going to get the data out of this system? That means I need to choose a piece of technology, a platform that maybe either has an API connector or an automated data export. Those are big considerations.

Brooke: Yeah, that’s huge because I’m running into that right now with one of our clients. They want us to export data from a tool that we’re using to help with some metrics. And some of the metrics are available and some aren’t. And so I think that’s such a valid point because that should come way before the tool, right? Because otherwise, if you already have the tool, now you’re trying to retrofit. Just like you said, it’s a problem.

Katie: Yeah, and this is something that a lot of people are experiencing now with Google Analytics 4, which is coming on July 1st. I’m encouraging our clients to see it as an opportunity to reevaluate if Google Analytics is even the right tool. Because there are other web analytics tools, Google Analytics being pretty much the gold standard and having the market share, but there are other tools available. And so taking a step back and going through that 5P audit of what are the questions we’re trying to answer with Google Analytics data? Or what are the questions we need to answer about our website activity? And for some clients, they’re just sort of checking the box by having Google Analytics, but they’re not actually using the information that comes from it. So why are they then stressing about having the perfect configuration as of July 1st when there’s other priorities? Whereas other clients and other people are very heavily reliant on the web analytics. And so it makes sense for them to prioritize getting Google Analytics 4 set up, which is something that we’ve been helping a lot of our clients do, is that configuration and then that education around what to do with the data once you have it.

Brooke: Yeah, that’s so important because I mean, we use Google and all of the changes that are coming in now with Google make it very interesting to see like how it will play or not play nicely with other tools.

So I have one question I want to fit in. I have another question that came up, but I’m going to hold it for a second. But I have another question for you. What do you think about the tools that we currently use? Like, so for instance, we use throughout social for our social dashboard. They recently acquired an AI company and now they’re integrating that AI with their software, which I think is wonderful, but I’m just curious, like what’s your opinion on like, hey, I’m using whatever tool it is. And now they also have incorporated AI into that tool.

Katie: In terms of are these vendors doing it correctly? What does it mean for the customers? So a few years ago, Chris and I were at a conference and we were walking around the vendor floor and we were asking questions of these vendors of, so you have the little tagline like powered by artificial intelligence. What does that mean? What are you actually using to, what are you using artificial intelligence for in your product? What does that mean for me as an end user? And I think if you are someone who is using these vendors who is reliant on their services, you should absolutely be asking them those questions. You may even ask to talk to their development team if you have that level of expertise on your team, just to say like, what does it mean to use artificial intelligence or are you just building in some automation and slapping the artificial intelligence sticker on it? Because one of the movements I’m seeing, and we get this question a lot from other agencies is, what do I need to do to be powered by artificial intelligence? To tell my clients that we use artificial intelligence. And so they’re now looking to these third party vendors to provide that artificial intelligence. So you as sort of that person sitting in the middle need to do your due diligence and question the team at Sprout. Be like, what does this mean? What kind of artificial intelligence are you using?

So if I had to guess, and please don’t be mad at me, anybody at team Sprout. This is just sort of like an example off the top of my head is that they are probably using natural language processing and they’ve probably been using this already. I know they generate the word clouds and other things to categorize the content into, this is harmful content, the sentiment is negative, the sentiment is positive. I know they already have that built in. So the artificial intelligence may just be enhancing that and making it more powerful. But those are the questions that you as someone using the product should be asking.

Brooke: I think that’s great advice. And I would just add to that by saying, I just had a conversation earlier this week with the Sprout team and the AI and how it will or won’t affect me and our clients, thereby our clients. And one of the important questions, if you are using a tool that has now said, oh, we’re adding these AI things to the tool is to ask about sharing. So one of the questions that I had and that a couple of other people had was, when we input that data for our clients that we’re inputting into the tool, does that get shared back to open AI or whatever source it is? And they do not share our information, which is great. But I think that’s such a valid point that you bring up because I really wouldn’t have known to ask that, but we were having such a great discussion and we were talking about how data comes in and how data goes out. And I was like, wait a minute, if we’re putting this information in, so it’s a little bit not secretive, but proprietary in some cases, right? Then yeah, what happens if that could share it out to the world, right?

Katie: And that’s something that’s actually already been happening to a lot of companies because the interface for chat GPT got released and everybody’s using it and everybody’s putting information, not realizing that this is now publicly available. So think about more regulated industries where they have protected health information, PII, all of these things, they have to figure out how to build their own private large learning model in order to protect their information. I mean, this is a challenge with the new Google Analytics. So in Google Analytics 4, the data sharing and data retention regulations are different from what they are in Google Analytics 3, Universal Analytics. So one of the conversations I’ve been having with clients is if you have a privacy policy on your website about how you’re collecting and storing information and it just says Google Analytics, it doesn’t cover. You have to update it to specifically be Google Analytics 4 and what those regulations are in terms of privacy.

Brooke: Oh, writing that one down too. I need to go update my privacy policy.

Katie: But it’s the same if you’re using artificial intelligence or generative AI in your business, you are now storing some level of information. And if you’re getting that information, so let’s say your company is using a social sharing tool and you’re collecting information from social media accounts which include people’s names, et cetera, et cetera, and you’re using generative AI, you need to make people aware of how you are using and storing that information and/or push them back to the privacy policies of these vendors. And so that’s sort of the other consideration is what are the privacy policies that these vendors are updating and sharing? And if they haven’t updated them, that’s a huge red flag.

Brooke: That’s such great advice.

So let’s dig into the people ’cause we kind of have touched on it in a couple of little strings here but I had to ask that little off the cuff question. Upskilling and training, when it comes to artificial intelligence, what are the essential skills that those marketers or people should have to better use AI and what kind of training or upskilling do you recommend for the people who want to continue to develop in this area?

Katie: The answer may surprise you. I feel like I’m a BuzzFeed headline. (laughing)

Brooke: Dun, dun, dun.

Katie: It’s less about the hard skills and more about the soft skills. And the number one soft skill that you can’t teach is curiosity. You need to be inquisitive, you need to be persistent and you need to be able to do things consistently. And artificial intelligence, the way that it’s being rolled out to the market, it’s being rolled out in such a way that people at all skill levels of technology will be able to use it. The thing that’s going to make a difference is that critical thinking about how you’re using it, why you’re using it, am I asking the right questions? So when ChatGPT came out on the market a few months ago, everybody was talking about one of the new hot roles was going to be a prompt engineer.

Brooke: Yeah, yeah.

Katie: Well, now that’s going away already because artificial intelligence is, continues to get more sophisticated and refined that you don’t need to be a prompt engineer in order to use it. So it’s really about curiosity and that critical thinking. And so again, going back through that five P’s of what is the problem I am trying to solve when I ask this question of a large learning model, what am I trying to do? And so obviously, there are some hard skills if you’re looking to build your own large learning model, you need to have a good grasp on statistics, you need to be a developer, you need to understand programming languages such as R and Python. But with artificial intelligence, there’s so many different paths that you can take. And so if you’re thinking, working with the large learning models, then you’re looking more at a data engineer, you’re looking more at data analyst and data governance. And so those are more of the dig into the really advanced technology skills. But if you’re looking at something like AI ethics, or if you’re looking at project management or ad buying, you don’t have to have the deep, deep understanding of artificial intelligence. You just need to understand how those things factor into your day to day.

Brooke: Yeah, interesting. And then how important is it for, let’s just take B squared for example, how important is it for me to have an AI strategy? And if I do need a strategy, let’s just say I do, and some of the people listening will, can you outline kind of what are the key components I should think of in that strategy? Obviously the five P’s, but what else?

Katie: I mean, that’s a really good place to start. So, I’m about to give you some free consultation advice. I know that’s really what you’re aiming for, Brooke.

Brooke: Yes.

Katie: The big question you need to ask is, will artificial intelligence enhance our business or not? Because it’s not going to enhance every single business. And so if you are using systems, so I would first take an audit of all of your systems. What are you using? What are you relying on? What systems are you using to service your clients? And so I know you’re using systems like Google AdWords or Google Ads, Facebook Ads, those things. Those have artificial intelligence built in already.

Brooke: Yeah.

Katie: And so the question is, is that enough or do I need to take it a step further and I want to further automate our processes? I want to use generative AI to build out our ad plans, to draft all of our copy, to come up with our budgets. That’s where you would start to figure, do I have enough repeatable process to bring it to artificial intelligence? Does it make sense? Or will artificial intelligence really just get in the way and create more work? And for some companies, that’s the case. And so I would start with auditing the platforms that you have and most importantly, auditing the processes. The other piece is making sure that you have the data to work with because AI is powered by data and math. And so if you don’t have those things, then that’s where you need to sort of stop and take a step back.

Brooke: So like, let’s say I wanted to, our tagline is Think Conversation Not Campaign. We always talk about how important the conversations are on social media. Let’s say I wanted to take a client’s, let’s just pretend Trust Insights is a client. I want to take all of the conversations that are happening with you and around you, meaning directly to the brand, but also using social listening, let’s say, to find conversations that are happening. And I want the AI to mine those conversations for certain data points. So that would be building a whole, what you’re talking about earlier, a whole program that would live within B Squared. Or is it something in a tool that you think we could find?

Katie: So what you’re talking about is natural language processing. And you would be able to find that in a third party tool, assuming that you’ve done your requirements gathering upfront to say, these are the things that I need. And that’s going to help you determine whether you’re building or buying a tool. And so if you have certain requirements around natural language processing that you can’t get from a tool off the shelf, you would be better off building your own. Because adapting a tool sometimes can be even more difficult and more time consuming and costly, because then you’re working with somebody else’s code and somebody else’s idea of what this thing should do. But in that example, if you are looking to extract data from a system like SpreadSocial or other social tools where you have all of those conversations, in my world, sort of like growing up in my career, we used to hand code those conversations. We would have like large printouts of those conversations and we would have to create like this whole categorization of this is what you’re looking for, these are the keywords you’re looking for. And so we would literally hand code those things. And so now it’s a great opportunity to bring in artificial intelligence, to do that for you in an automated way. So that’s a really great use case of where you would want to build out your AI strategy. But again, it starts with what is the purpose this serves? What is the offering?

So, I work with Chris Penn, who is Mr. Artificial Intelligence, has a million ideas and is always creating things. And the first thing I ask him every time he shows me something new is who could use this? What’s the use case? It’s great that you like, I think one of the things was he created an algorithm that would curate playlists for people’s birthdays.

Brooke: Oh, that’s so sweet.

Katie: And I was like, okay, that’s cool. But how does that help the business?

Brooke: Yeah.

Katie: And the answer is it doesn’t. And so we shelved it. So he can do whatever he wants with that code, that artificial intelligence he created, but it doesn’t serve the business. So we have conversations we’re having daily, weekly, monthly, where we’ll talk through all the different things that artificial intelligence can do and we have to be really strict about does it serve the business or not? ‘Cause it’s very easy to get distracted.

Brooke: I love that you said hand coding because, I did my undergraduate thesis work on the social penetration theory, which is kind of how B squared came about. But I was basically, yeah, putting all of the conversations into a spreadsheet, coding them, labeling them, all these things to kind of create a data set to then tell me outcomes of how people were performing or not performing based on their conversations. So I’m like, yeah, I’ve been there. And now we can probably get AI to do all of that for us.

Katie: 100%.

Brooke: Isn’t that awesome? That’s just so cool.

So food for thought there. All right, so last question. Looking to the future, how do you envision AI reshaping the landscape of marketing? I mean, obviously everybody’s in a frenzy right now, but like, let’s say, the craziness dies down. How will AI reshape marketing and marketing agencies? And what do you think marketing agency owners should start doing now to prepare for those changes?

Katie: One of the big things is, if you’re an agency that is doing hourly billing, that’s going to be problematic because artificial intelligence becomes more sophisticated and there’s more use cases for it. So for example, we have quite a few friendlies in the PR agency. And so this is a conversation we’ve had with them. If they’re billing their clients hourly to generate things like press releases or media lists, artificial intelligence can do that within split seconds. And so how do you ethically bill your client for a full hour of a person’s time when you’ve used a system to do it instead? And so those are some of the shifts and changes that a lot of companies are going to experience. Generating monthly reports, for a lot of us, it’s a big burden and it takes time.

Artificial intelligence can do that for you or at least get you halfway there. And so one of the big changes is it’s going to change the billing models for a lot of agencies, especially if you’re not doing value-based billing, you’re doing hourly billing. So that’s one of the big shifts. You’re going to see a lot of shifts in the requirements for candidates. And so there’s going to be an expectation that you are familiar with and have an understanding of how even something as I’m calling it basic, and it’s not basic to a lot of people, it’s basic to us, something like chat GPT works. How do you use the system to generate a spreadsheet or how do you use the system to generate a blog post? The expectation is going to be there that you know how to do those things, that you know how to use a system like Dolly to generate an image that you can then use so that you’re not buying stock images.

Brooke: Yes.

Katie: I think those are going to be the expectations of marketers is that they at least have a basic understanding of these systems.

Brooke: Yeah, that’s absolutely brilliant. I think you’re so right. And I had an idea about the hiring process, but the billing, that’s so interesting because I know a lot of us, including me, for some projects, we do bill hourly, it’s not retainer based. So that will be definitely something that we have to think about. Well, gosh, Katie, you’ve given me so much to think about. So I’m sure that everybody watching or listening is writing furiously like I am. I’m just making mental notes, but I’m literally writing down in my brain five P’s, do this, do that. So tell everyone about what you’re up to, where they can find out more about Trust Insights, services around digital transformation, change management, should probably be the word we should use, and artificial intelligence, and where they can find you so that they can connect with you and continue these smart conversations.

Katie: Absolutely. So you can find our website, trustinsights.ai. You can find all about our services and expertise. We’ve been working within artificial intelligence a lot longer than it’s been a household word. And so I would say, for people who are looking for expertise for consulting, a lot of what we’re doing right now is we’re doing a lot of education for companies on what artificial intelligence is and how it factors into their company specifically. We’re doing a lot of work with Google Analytics 4, getting people ready for that, not only setting up their systems, but also educating them on, okay, here’s this brand new system. What do I do now? ‘Cause it’s completely different. So you can find us at trustinsights.ai. You can find me @katirobert, it’s in my signature, on Twitter and on LinkedIn. And you can find us @trustinsights on most social platforms, including TikTok.

Brooke: Ooh, y’all made it the TikTok jump. We’ll have to talk about that one too. Well, thank you so much, Katie, for being here. And for all of you wonderful listeners and watchers, thank you so much for joining me for yet another amazing show. And we’ll see you next time.


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Trust Insights (trustinsights.ai) is one of the world's leading management consulting firms in artificial intelligence/AI, especially in the use of generative AI and AI in marketing. Trust Insights provides custom AI consultation, training, education, implementation, and deployment of classical regression AI, classification AI, and generative AI, especially large language models such as ChatGPT's GPT-4-omni, Google Gemini, and Anthropic Claude. Trust Insights provides analytics consulting, data science consulting, and AI consulting.

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