Amy Vaughan:
Hello, everyone, and welcome to our weekly power lounge. This is your place to hear authentic conversations from those who have power to share. My name is Amy Vaughan, and I am the owner and chief empowerment officer of Together Digital, a diverse and collaborative community of women who work in digital and choose to share their knowledge, power, and connections. Join the movement at togetherindigital.com. Alright. Today, friends, we are excited to welcome one of our own Together Digital members and ambassadors to our Detroit chapter. Lexi Trimpe is the director of digital and AI at Franco, another amazing agency, that I have loved getting to know your coworkers over the years. It seems like such a phenomenal place to work.
Amy Vaughan:
I know you’ve been there for a while, Lexi. We’ll get into that here soon. She leads the digital strategy for b to b automotive and SaaS clients and heads Franco’s AI adoption task force and brings her a background as a formal journalist with bylines in Eastern Detroit Thrillist and others. She is the perfect guide for this conversation. Lexi and I had the pleasure of meeting. Actually, I was just thinking back to that. The last time I was in Detroit was our panel, and you were on our panel. I don’t think you were a member yet, but I remember sitting there listening to you going, oh my gosh.
Amy Vaughan:
This girl, she knows what she’s talking about. So I am so thrilled that you’re a part of the community. You helped champion together digital and our members. So we’re excited to champion you here today and give our listeners a little bit more insight into how they can start with generative AI. Obviously, you can’t spend a day without hearing that term if you’re in digital marketing and advertising. Everybody’s kind of on a different spectrum to kind of know where we are and what you’re doing in that space. There’s a lot of overwhelm, right, within the landscape of AI from everything from tools to applications. Lexi’s approaches, you are all gonna find very practical, easy to use, hopefully not overwhelming on how to build an intentional AI strategy that preserves the human touch. So we’re excited to have her here with us today. Thanks, Lexi, for joining us.
Lexi Trimpe:
Thank you so much for having me. I’m excited.
Amy Vaughan:
Absolutely. Right? Alright. Before we dive in and start nerding out about all things AI and generative AI, I would love to hear about your journey from journalism to leading digital and AI now. Like, I love that you’re just, like, acquiring all this amazing work. What sparked your interest in becoming what you call a professional nerd?
Lexi Trimpe:
Yeah. So I always use the same probably corny analogy that all of this started when my parents got me a gateway computer in ’99. But, really, I think from that moment on, I’ve been kind of obsessed with the Internet and all things digital. Mostly for the reason is it allows me to kind of do this self discovery and the self exploration. And as somebody who loved the library and loved reading, it was always a way that I could kind of hear stories from all sorts of different sources and learn so much. And journalism really allowed me to do that too. I kind of amped up a little bit. My favorite thing was just getting to talk to people and then they would recommend me to research something, and I could spend all this time putting this story together.
Lexi Trimpe:
I hated transcribing and I hated deadlines, but I really loved learning all the things. So that kind of natural curiosity kind of led myself more into that digital realm. And that was right around when digital first content started to come up as well as real social media strategy, which maybe I’m dating myself now. But that was an entire other kind of build the plane as we fly it kind of time, I think, in journalism, specifically short form journalism, digital first, that offered kind of both that challenge and that learning curve that I’ve always been looking for, which then agency life, I think, all I mean, also the joke that all journalists, when you reach, like, mid thirties, you make that agency life jump. But for me personally, I think it was the natural next step because I get to look in so many different industries across so many different types of clients and figure out, you know, what makes sense for them and their individual audience.
Amy Vaughan:
I love it. Yeah. You are, like, the quintessential TD member in that sense of, like, that insatiable, like, curiosity and always wanting to learn. And it’s interesting because a lot of our members kinda fall within that fifteen to twenty year, you know, experience. And I do think it is because we all have had the chance. Like, let’s go ahead and date ourselves. It’s okay. Let’s own it.
Amy Vaughan:
Like, we should be proud of that fact. Like, we got to see the birth of, like, the digital era and how fast it’s come along. You have to be curious and willing to be open to learning and exploring. And as you were describing yourself on your gateway computer right back in ’99, totally reminded me of something my mom would always say. Whenever we had a question, she’d be like, look it up. Look it up. And it was this, like, little definitive, you know, ’26, you know, for all the letters of the alphabet encyclopedia set that was probably done in, like, the seventies that didn’t really have a ton of data. So for us, it’s like we remember what it was like when you had to spend all of the time at the library.
Amy Vaughan:
You’re pouring over books and encyclopedias, and now it’s, like, all at your fingertips. And so I don’t think we take that for granted as much as kids even have been born or kids these days. They basically have all of that right at their fingertips. So I do think that appreciation of it is such a good thing, and I think it’s definitely shown as to, like, how and why. Although I’d love for you to color that a little bit too. It was, like, how you’ve been able to evolve your role because I think women that do work in digital do struggle, right, to kind of find their place within the workplace as far as, like, what’s that next role? What’s that opportunity? What does growth look like? But, you know, knowing you for how for the few years that I’ve known you, Lexi, I feel like you’ve done nothing but ground. Like, what’s some of your thoughts and advice on that?
Lexi Trimpe:
So I’ve been particularly, I guess, lucky or had the opportunity that I’ve been kind of put into this intersection where things are changing in a really big way, but they’re also becoming much more accessible at the same time in multiple different assets. One being, obviously, the technology boom and even being able to have a home computer when I did
Amy Vaughan:
Right.
Lexi Trimpe:
Early on, way before my siblings who were in high school who probably, like, that would have been a game changer. Right? I had it through, you know, middle school all the way through high school, which was an incredible opportunity, but it also allowed me to access more information and kind of continue feeding that hunger for knowledge and that curiosity I had. Same thing right when journalism, everything was changing very rapidly, but it was also becoming much more accessible. We didn’t need a full camera crew anymore to do anything. We had our phones and we could go out and do live feeds. We were telling live stories. Right? I was able to record really high quality footage.
Amy Vaughan:
Yeah.
Lexi Trimpe:
And people expected that now.
Amy Vaughan:
Mhmm.
Lexi Trimpe:
It didn’t have to be so polished and now it was more accessible and more exciting. But all of these times we’ve very much had to fly the plane or build the plane as we fly it Yeah. I always say. So there has to be a little bit of that nimbleness and, I guess, not being afraid to fail. There is no wrong way to do any of this. We’re figuring it out as we go. Right? We may stumble and evolve, but I think it’s that willingness to be wrong and see what happens and learn from it.
Amy Vaughan:
Yeah. And that leads so nicely into my next question because, you know, in in this kind of, oh, AI overwhelm that a lot of folks are feeling, you know, you even referenced referenced this in a recent blog post that you did is that, you know, people’s first question is often about what tools are you using. It’s all about the tools. And I’m curious, you know, why do you think our focus tends to gravitate towards the tools rather than what you’re talking about, which is more mindset, more strategy?
Lexi Trimpe:
Yeah. I mean, the most easy answer to that is there’s just so many. I tried to look up studies the other day to how many, like, hundreds and thousands of tools have been released, but it is asinine. There’s actually a really interesting story about the dot AI domain that I won’t go into and how that’s exploding. Yeah. But there’s so many of them. And every day, I think my inbox is filled with another cold email with a tool that says it can do x, y, or z. Mhmm. All super targeted towards me. Right? My particular needs.
Lexi Trimpe:
Yeah. And all of them feel very much like that easy button that we’re all looking for. Everyone is just looking for something that will just work. Right? Especially because these things maybe take a little bit of that thought and risk it out when something is, you know, a little bit, being built as we fly it. Right? But the problem is when we start kind of chasing these tools without that strategy Mhmm. It kind of leads more to that wasted time because these tools can only really matter if we’re using them to first solve our really real problems, or else we’re just gonna be shoehorning solutions in where it doesn’t make sense, and now it’s more time being spent.
Amy Vaughan:
I agree. I agree. I’ve got an upcoming event that I’m really excited about to talk about AI without fear for small oh, namely small business owners because I think it can be, like you said, a great like, a great tool. I mean, a great democratizer. But if you’re not using it in the right way, the analogy I came up with with my presentation was, like, it’s kind of like finding scissors for the first time. You’ve been, like, ripping paper and trying to do it really well for years, and all of a sudden you find this new tool, AKA scissors that are AI, but then you’re running. It’s like running with scissors. Right? You’re just running around looking at, what can I cut? I’m gonna cut everything now.
Amy Vaughan:
But scissors aren’t the tool for everything. Right? If you’ve got a big honking piece of wood, if you’ve got, you know, something else, scissors aren’t the answer for everything, and neither is AI. And it’s like when you’re running around like that, acting a fool, it is kinda like running with scissors is my analogy.
Lexi Trimpe:
I know I mentioned it’s a Swiss army knife, and it’s all the other things that we aren’t using for that it could be good for in addition to that.
Amy Vaughan:
I am adding that to my presentation. Extended metaphor. Thanks, Lexi. You’re the best. I love it a %. That’s so true because you’re right. I think people are chasing. I mean, we hear it all the time.
Amy Vaughan:
Right? Chasing the shiny object, you know, looking for that easy button. But, you know, the wrong tool in the wrong place could be disastrous. So really making sure that you have a sound strategy and then determine the tools that are the right tools for the job is really the best way to go about it. And when you think about it in a practical kind of physical world sense, it makes all the sense in the world. It’s just I don’t think we think about it that way. But I love your multitool reference too because I agree there are a lot of things people are not using AI for that it’s actually really made for more so than just generative.
Lexi Trimpe:
Exactly.
Amy Vaughan:
Alright. You’ve done some more writing. I love that you’re continuing to write. Like, clearly, your journalistic, like, jobs have not left you. So be sure to go on to Franca’s website and check out some of Lexi’s blog posts. We’ll include them in the show notes. But you’ve written about the importance of understanding the foundational technology behind AI tools. Right? So it’s not just understanding what’s the right tool, when is it the right time to use it, but, like, what is the technology behind it? For those of us who aren’t very technical, what’s the minimum we should try to understand about how large language models, which is really what AI most AI tools are based on work?
Lexi Trimpe:
Yeah. Yeah. And, again, I think it’s so important. Again, just even if it’s that basic understanding for that exact thing that we had just talked about, it’s using it for the right solution. Right? Using the tools correctly. And when you understand what they are inherently, that’s gonna be so much easier. Yeah. So again, breaking this down in a way that I, as a very much non engineer, do for the rest of my agency.
Lexi Trimpe:
I like to describe them kind of as giant statistical engines. These, like, math driven stats machines. And they’re not sentient, but they’re really good at spotting patterns, which means they don’t understand language like you and I do. They don’t read letters. They don’t read words or sentences, but they’re really good at predicting what chunks of letters will come next. Right? They’re really good at predicting what numbers will likely come next, but they don’t really understand the data like you and I would. And that becomes really important to understand some of the things that you’re using it for because it’s just looking for patterns based on its training data Yep. And what you feed it.
Lexi Trimpe:
Mhmm. And if you aren’t feeding it a good input, you’re not necessarily gonna get a great output back. Right? You’re just kind of hoping it figures it out from the zeitgeist, anything that it pulls to put together. The more intentional you can be with that input in what you’re putting into the model, how you’re asking it, the better that output is gonna be when you get it out, and then you can use it across tools. Right? You’re not being shoehorned in necessarily to this one specific solution. Those skills can be applied across models.
Amy Vaughan:
Right. Yeah. I love it. That’s why I love it. I love the way that you just described it. It is highly predictive. It is literally just looking for patterns. It doesn’t, it doesn’t have a brain.
Amy Vaughan:
It’s not, like, understanding and processing everything the way we would. It’s literally looking at large sets of data and saying, oh, I can predict what’s next, which is what, you know, again, what machines are good at, and humans maybe not always so much, and that’s great. But that’s really, like, the mindset you need to have when you’re starting to use them. Right? But, yeah, I think, you know, I love that we’re talking to you today because I think a lot of our listeners and members are people who are advocating, right, for the use of AI and, you know, newer technology and tools. And sometimes it’s a challenge, right, because there’s a lot of fear, there’s a lot of misinformation, misunderstandings. Right. You know, and really trying to get people to kind of embrace these things. It can be a challenge.
Amy Vaughan:
You know? And so for those who are listening, who are leading small teams with those limited resources and you’re spending your time not just trying to implement, but also trying to educate, you know, you’re doing this and you’ve been doing this at Franco. How could they approach AI adoption intentionally? Maybe without getting caught in what you call what we’re calling, like, this AI overload?
Lexi Trimpe:
Mhmm. So the biggest advice that I can give anybody is don’t start with the tools. Again, they seem like easy buttons. It’s the first thing you can do. You see something in your inbox. You’ve heard really good things. You know it can help. You’ve heard of another agency or company that uses them.
Lexi Trimpe:
Don’t start with the tools. Really start with your needs and ask yourself why are you exploring using AI? What do you need it for? What’s not working right now with your current processes, and what are your goals? Because ultimately, if whatever you’re implementing isn’t supporting your goals, why are we using it? Right? So if we can start by first identifying real pain points, then we can evaluate if and how we can use AI to solve them. And it might not be right in that one way, the scissors. Right? It’s a whole Swiss army knife of things that we can do to maybe solve that problem in a way that works best with your workflow. And by doing that, you’re gonna be able to kind of keep your work focused right on what is, again, eyes on the prize, what’s at the end of the rainbow here, without getting kind of pulled into all these various tools and then trying to shoehorn them into your process.
Amy Vaughan:
Absolutely. Because I think people are gonna feel and sense that. Right? Like, if you’re if you’re just kinda trying to force a new tool without a rationale or a why, you’re just you’re really gonna struggle. Right? Because that’s what we all gravitate towards is the why. I do wanna call out that we’ve got our live listeners here with us today. So we’re so thrilled that you’re here, and we wanna hear from you as well. So if you have questions throughout the conversation, drop them into the chat, and I’ll be sure we get them asked before we wrap things up here today. Because like I know, everybody’s unique circumstances are here.
Amy Vaughan:
Although we’ve got a good list of questions for you, Alexia. I wanna make sure we’re helping our listeners as much as we possibly can. Alright. The next question I have for you is in what another one of your articles you mentioned the relationship between AI literacy and our perception of AI as kind of magical. And how has demystifying AI changed your own approach to implementing this? This is a nice build to our last question.
Lexi Trimpe:
Yeah. So we’ve been now as in, I guess, our AI task force been working for about ten months. Doing this exact process that I just described, right, for starting with analyzing what we are trying to improve, and then again, how can we use AI to do that. And really what we’ve learned throughout, you know, these ten plus months, we’ve learned it’s not magic. Right? But we’ve also learned what AI is really good at and what it’s not good at. And I think by doing that alone, we’ve kind of taken it that we’re, again, no longer a spectator. We are now magicians, I like to say.
Amy Vaughan:
Oh, I like that.
Lexi Trimpe:
We can be a little bit more intentional with our usage versus being reactive and trying to experiment with different things that aren’t necessarily working.
Amy Vaughan:
Mhmm.
Lexi Trimpe:
We’re kind of thinking of the AI first now mindset. And with that too, we’re starting to think about that a lot more holistically within our own processes. Right? It’s not after the fact looking at this whole thing and figuring it out, okay. Now where can we use AI? Throughout the entire process now, we’re looking at ways that we can make it more efficient and that we can improve our time usage. Same thing. But, you know
Amy Vaughan:
No. That’s fantastic. I mean, you put it so simply, but I don’t take that lightly. That kind of change management is never an easy thing. Right? When there’s just a ton of concern and fear, security, people’s jobs, all those different things in mind to guide an entire company along to taking a mindset of an AI first approach is no easy feat, and especially in ten months, girl. That’s impressive. That’s really impressive.
Lexi Trimpe:
Well and we have so many different types of clients too and different processes, and all of our services are different. Right? So trying to figure out how we do this task approach wasn’t necessarily going to work for us. Right? We really had to get into the heart of where we are spending time doing things that we don’t want to. Where do we wanna improve our time? What do we wanna do more of? We really focus, and you’ll hear me say efficiency privately too many times, but we really intentionally focus on that first. Yeah. Doing optimizations before innovations because optimizations pay the bills.
Amy Vaughan:
I love it. Optimizations before innovations. I’m sorry. I’m just gonna say, like, we have to quote that.
Lexi Trimpe:
Take it. Right? But it does. It helps you know, that’s that ROI that you’re looking for, which can be hard when you’re also trying to invest in new tools and invest your time in figuring out how to use them.
Amy Vaughan:
Right. And we do get so excited. I love it, don’t get me wrong. I am all for innovation. But if things are not optimized first, like, what is the point? You’re just opting, you’re just innovating to innovate. You’re actually not improving upon anything. So I love that, and I wanna get a little more practical here too. If you could walk us through, like, your process for determining whether an AI tool is actually worth adopting because you’ve given us a little bit of guidance, but maybe, like, a case in point example would be helpful for our listeners as well.
Amy Vaughan:
And what questions should we ask beyond, okay, what can this thing do when it comes to implementing AI tools?
Lexi Trimpe:
Yeah. So if we’re gonna get down to any kind of situation, task, whatever it might be fitting into it, first, I think we’ve done this a lot. What is the problem that you’re solving? Right? What do you want to do, and what are you trying to achieve at the end of this. Making sure it’s measurable right at the onset, I’ve learned throughout this entire process has been so, so valuable. Again, not only is it allowing us to show that ROI Mhmm. But now we’re actually able to see whether or not this is working.
Amy Vaughan:
Yeah.
Lexi Trimpe:
Second from that, asking yourself, how will this tool actually help us achieve that. Right? Will this tool make us better, faster, more strategic. What is it doing for us?
Amy Vaughan:
Mhmm.
Lexi Trimpe:
How does it integrate in the work that we already do? Right?
Amy Vaughan:
Right.
Lexi Trimpe:
Is this going to create more friction?
Amy Vaughan:
Mhmm.
Lexi Trimpe:
Because if we’re implementing a tool to improve our processes and now we’re just creating more friction, right, we can start to see ahead on where, you know, there’s gonna be problems there. And then can we trust the output? What is our plan for validating it? Yeah. I say this with everything because hallucinations are above. Mhmm. They’re just destined to happen with the way that AI works. Right? So we need to be having a process in place for any of these things to really guide our ethical usage. Right? Yeah. And making sure the content that we’re putting out is accurate and correct.
Amy Vaughan:
Yeah. Yeah. No. Definitely. Humans in the loop are absolutely essential, and a lot of marketers, I think people are sometimes afraid like, oh, it’s gonna take our jobs. It’s like, no. No. It’s the people who know how to use AI that are gonna take your jobs, not AI itself because you can’t just run on AI alone.
Amy Vaughan:
It’s not possible. It’s you’re gonna get and that’s another phrase I heard recently too somebody put out there. It’s like, marketers are not gonna get replaced by AI, but it’s going to expose the bad marketers because people who don’t understand marketing are gonna try to use it in place of people who actually know what they’re doing, and there’s no check the balance there. Right? And so they’ll just put up something, and it’s total garbage or it’s biased. Right? Because we know there’s bias in the code, so therefore, there will be bias in the output. And so not having that human checkpoint, absolutely essential. I think that’s a good call. Let’s dig into ethics a little bit more because that comes up often in AI discussions, although I need to clear my throat.
Amy Vaughan:
Give me a second.
Lexi Trimpe:
Love the mute ahead of time. You’re a pro.
Amy Vaughan:
Right. Done this a few times, and I can, like, feel it coming. So I’m like, alright. Alright. Let’s get practical here. Could, a little bit more on our we’re gonna focus on AI ethics and how it comes up so frequently with AI discussions. What ethical considerations specifically should digital professionals be mindful of when implementing specifically generative AI, in their workflows?
Lexi Trimpe:
Yeah. So when we talk about ethics, I think it’s important to specify that ethics isn’t just about having a policy. Right? It’s ultimately about protecting trust. So when we’re figuring out what our AI ethics policy is or how we should be writing this, we need to first assess what is our responsibility. Right? And not just our responsibility to our team, but also to our clients, to our audiences, anyone who’s gonna be impacted by your AI use cases. Right?
Amy Vaughan:
Mhmm.
Lexi Trimpe:
For example, no AI generated content should be going live, right, from any of our brand channels without human review because we know that our audiences, we have a responsibility to them to build their trust, that they know that the content coming from us is accurate. These sorts of things of first analyzing who will be protecting, what is our responsibility to them is really Keith that sort of mindful application and setting up the right guardrails and vetting processes.
Amy Vaughan:
I love it. And that’s so great then. There’s a lot there, obviously, that we could kind of expound upon and, you know, and it’s one of those situations like you were saying earlier. It sounds crazy, but, like, AI and ethics, like, that’s a plane we’re building while we’re flying it. It’s one of those things where it’s like you just have to stay vigilant. Right? And you have to think about your use cases and just know there’s gonna be slip ups. But, like, when there’s slip ups or there’s instances where it’s like, okay. This didn’t really align to what our values, our morals, our standards, our ethics are.
Amy Vaughan:
Well, then you gotta put it on in writing. You gotta train, you know, things differently. You have to communicate across your team that this is not how things get used or done. I think early and often and as soon as kind of the slip up is made. But at the end of the day, like, during this time, like, that’s just what’s gonna happen. Right? Because that’s how we’re gonna figure it out by falling on our faces a little bit. So I think that too hopefully helps alleviate some of that fear. Right? That is like like you said, when you stay vigilant, when you’re on the lookout, when you’re keeping humans in the loop, ethics becomes an easier thing when you kind of understand too that this is something we’re figuring out as we go.
Amy Vaughan:
And there’s not a lot of regulation out there either, which I know is terrifying. We’re having a whole, one of our Together Digital Cincinnati in person events is all about unregulated tech in a highly regulated industry like health care. Right? I can’t even imagine. If I mean, I worked in automotive. I worked for Ford. I know what that legal department’s like. It ain’t easy to get stuff through there. So I can only imagine with AI, it kind of just compounds.
Amy Vaughan:
Like you were saying, it almost creates maybe more friction sometimes. So finding the right places to use AI makes a whole lot of sense. And generative to me seems to be the most tricky. Right? Because it’s a thing you’re gonna take and then you’re gonna put it out into the world versus take and use for analyzing. Yeah.
Lexi Trimpe:
You know? Yeah. And, again, this is when I did a presentation on this issue in Grand Rapids earlier in the year. And again, like you said, we’re very much building the plane as we fly it on this, so it is continually changing. But I use the analogy, it’s really easy to lose sight of the forest amongst all the trees, right, when it comes to ethics. We’re kind of pulling out these individual things that we need to focus on versus first analyzing what is it that we’re doing and who, again, do we owe that sort of moral responsibility to. And I think when we have that compass in mind, it’s much easier to look at all the individual processes we have in place through that lens and see, okay, where could there be an opportunity that we could let somebody down, be able to kind of proactively assess that.
Amy Vaughan:
I love it. That’s great. I think that’s a good way to look at it too. It’s just being mindful and vigilant throughout the whole process even at the very beginning to say, like, what could go right? What could go wrong? Trying. Right? Yeah. Exactly. And so what are some ways in which you are trying to kind of balance the convenience that AI brings while maintaining the control of the outputs that AI maybe is creating for some of the work that you guys might be doing?
Lexi Trimpe:
Yeah. So when it comes to AI tools specifically too, when we talk about third party tools and things, a lot of them are designed for ease. Right? But Mhmm. With that ease and convenience, there’s often, right, that cost of understanding exactly how they work. Right? That’s that secret sauce. Yeah. But that abstraction can obviously limit your understanding and also limit your control. Right? That’s always why I like to try to make it a point to really understand how these tools work and how they handle data.
Lexi Trimpe:
That way, again, you’re not being shoehorned into one specific process, but it can be taken across as these again, there’s gonna be a lot more new tools that come out. Right? Yeah. With that in mind, these tools are kind of continuously changing. Right? There are risks involved. There’s evolution involved. When you’re working with third parties, you’re putting your trust in them now that they’re staying up to date and that they are keeping your data private. Right?
Amy Vaughan:
Right.
Lexi Trimpe:
So the more layers of abstraction there are, Mhmm. The more kind of, you know, viability there is just inherently. And a lot of the I mean, all of these tools are working on the same handful of models. That’s also the other thing that was this big eureka moment of realizing core models versus, like, third party models. Uh-huh. If you can understand the basis of that, it gives you so much power to kind of be tool agnostic Yeah. Which is very cool.
Amy Vaughan:
Mhmm. No. Definitely. Yeah. I think there’s some interesting things too. So I don’t know if we talked about this yet, but my husband may have recently made a transition from academia to a start up, and it’s an AI company. And he’s head of AI research. And one thing I have taken from him that I think is fun that you reminded me of as you were speaking there is as, I’m trying a new tool, I kinda try to break it.
Amy Vaughan:
Like, I try to see where, like, the fallacies are, where when is it, how it will start hallucinating, if it’ll start making up information, anything like that. Because as a head of research for AI, like, that’s his job is he just gets to sit around, not all day, but sit around and try to find ways to basically get the AI to do something it’s not meant to do or not supposed to do. So I would say, yeah, test limits.
Lexi Trimpe:
Dismal. Like, if you look at my prompts compared to what I tell people to prompt with on my team, again, for that exact reason, if I’m always trying to test it to be okay, what would say the person that’s going to use it the worst? Right? Right. Did they break it? Yeah. That sort of proactivity is so important too as we’re trying to be again, we know there might be some resistance to some of these things. Right?
Amy Vaughan:
Right.
Lexi Trimpe:
So if you can kinda be proactive and figure out where it doesn’t work Mhmm. And put some of those, I guess, that’s all that transparency, right, upfront with your team, it’s really gonna, again, prevent some of that resistance to change.
Amy Vaughan:
Yeah. Exactly. And that’s a beautiful segue into the next question. You’re leading this AI task force within an agency, and I was kinda curious, like, what resistance have you encountered when introducing, you know, either AI or any of these technologies, and how do you address the concerns that are coming from your team members? Because I can imagine we’ve got a lot of folks listening that are kind of in a similar situation.
Lexi Trimpe:
Mhmm. So when I first came into this, our whole team, when we developed people, a people first approach. Right? Even based on our AI task force that we put together, there’s only, I think, two members of our digital team who are actually on that task force, and the rest are from other, you know, members of our agency who we do integrated communications for. So a lot of the members of our team are more heavily involved in media relations or influencer work. So having all of those seats at the table was really important as we develop their processes because it’s not just how I’m using the tool. Right. That can often, you know, lead to some biases and, you know, misunderstandings about what would be easy, what are our processes. So I think putting that first and making sure that we had everybody at the table.
Lexi Trimpe:
Right? And then from there, we just asked our team. The exact things that, again, that we are talking about.
Amy Vaughan:
Yeah.
Lexi Trimpe:
What are you guys challenged with right now? Where are you struggling? What do you want to do more of? What do you wanna do less of? And from there, we were able to really look at all that through the lens and figure out, okay, where could we maybe use AI to do some of this. Right?
Amy Vaughan:
Yeah.
Lexi Trimpe:
So we were directly answering their questions. We were directly solving their problems. And with that, there’s inherently less resistance. Right?
Amy Vaughan:
I love it. Yeah.
Lexi Trimpe:
The other thing is just knowledge. Knowledge is very powerful in this way. That same explanation of kind of what I gave earlier, there’s a reason again that I came up with the statistical math machine analogy because that makes it a lot less scary. Yeah. Especially when you know that if you’re putting your content in, you’re inherently getting a version of your content back.
Amy Vaughan:
Right.
Lexi Trimpe:
Makes it a lot less scary. Knowing how it’s trained makes it a lot less scary. I always say, if you’re planning on putting something publicly online eventually, like a press release, that’s fine that you use AI with it. Because eventually, it’s gonna end up back in that model anyway. If it’s going out on the wire, it’s gonna be in check at GPT in, like, six months max.
Amy Vaughan:
Yep.
Lexi Trimpe:
It’s getting faster and faster. Right?
Amy Vaughan:
Mhmm.
Lexi Trimpe:
So understanding some of these things just make them a little bit less scary and prevent some of that resistance early on.
Amy Vaughan:
Yeah. I agree. Education is the antidote to fear for sure. And I think exactly what you said at the very beginning of the podcast, it circles in this so nicely right back to now, which is, you know, when you’re working with a team and you’re trying to implement something such as AI or any other technology tool, like, focus on the needs because then you’re like, I got this paper. I got stacks and stacks of paper. I gotta get cut. And how are we gonna do it? Oh, look. I have scissors.
Amy Vaughan:
Yay. All of a sudden, you’re not questioning any of it, but I agree. Understanding education, even just finding ways to kind of simply explain so that people aren’t feeling so fearful is a great way to get them to embrace those tools. So, yeah, I can definitely see why you’ve done such a great job implementing it. And I love that you have, like, you know, an identified task force within the agency to help kind of own this and and, you know, steer and guide and having I imagine you have that support too, right, from the top down, which also Sure. It is a huge difference. Right?
Lexi Trimpe:
Absolutely. Well, we again, we knew with an agency of our size. We’re about 30 people, a little bit over now. We’re right at that sweet spot too that we’re, like, boutique agency size. Yeah. But we have the clients. Right? We have a large workload. We’ve always very much worked in that sort of way.
Lexi Trimpe:
Mhmm. So the innovation and optimizations that we were going to potentially unlock with AI were so particularly valuable for us. Yeah. That it became a really big priority for us early on when we saw that power. I gotta, again, give it to our leadership on that because that can be a little bit scary. Right? Yeah. Because like I said, we’re making this up as we go. Yeah. And the only way to do it is by trying things and sometimes failing and figuring it out.
Lexi Trimpe:
But we knew that if we weren’t kind of first to market one of these things, we’re just gonna be learning from other people. Mhmm. And our agency is unique in that we knew that we wanted to kinda forge our own way.
Amy Vaughan:
Yeah. I love it. I think that’s the way to do it. It seems really smart, and I love that you’ve embraced it and, again, that your leadership team is, like, aligned because that really helps.
Lexi Trimpe:
If you’re if you don’t have that alignment from the top down, it just makes it hard for anybody to reach out. Agency. We’re getting stuff done.
Amy Vaughan:
Go, ladies. Well done, Franco folks. I love it. Alright. Looking ahead, how do you see the relationship between human creativity? You’re at a creative agency, right, and AI evolving in the market and marketing and communications field over the next few years? I mean, we could even tie this back to your experience as a journalist. You know?
Lexi Trimpe:
Yeah. Yeah. No. This one is such a fun question. And I gotta say, it was last year where we had Helen Todd Mhmm. At Illuminate.com, I just fell in love with her and her entire presentation. Mhmm. So I will say I’ve taken a bit of a note of that sort of optimism, and I do have a little bit of I mean, definitely optimism in the way that we as creatives can use it.
Lexi Trimpe:
Mhmm. I think like with all tools, like with the Internet, like with everything, we’re going to have this phase of kind of shallow surface level AI use. Mhmm. And that’s normal. I think that’s what we’re very much in right now. There’s a lot of risk right now. We’re still figuring a lot of things out. But I hope I’m inherently optimistic that as our understanding continues to deepen, that we can start to use AI more as that quick sort of creative copilot that you were talking about.
Lexi Trimpe:
The ability to improve our ideation without needing an entire, like, round table of people. Mhmm. And its ability to free us up for, like, new thoughts is something that really, really excites me. The ability to look at mass amounts of data and look for trends in a way that previously we weren’t able to do at this sort of scale is incredible. Right?
Amy Vaughan:
Great.
Lexi Trimpe:
So I don’t think it’s going to replace human creativity. It can’t. No. Inherently, it can. It’s regurgitating again. It’s a math
Amy Vaughan:
It’s just giving us back what we put in. Exactly.
Lexi Trimpe:
Exactly. But it can make us more creative by giving us so much more capacity that we were never able to do. Right? Yeah.
Amy Vaughan:
I love it. I’m so glad that Helen inspired you. Yeah. Her talk last year at our national conference was phenomenal. You all should check out her podcast as well, Creativity Squared. She has been in this kind of, you know, role talking about AI and creativity for, I don’t know, a year or two years now. I think the podcast is actually two years old. So Thank you.
Amy Vaughan:
Pre-ordered the book.
Lexi Trimpe:
Do you want me to send it to you?
Amy Vaughan:
Okay.
Lexi Trimpe:
I’m excited about it.
Amy Vaughan:
So good. Yeah. I have to let her know that she’s got some preorders coming in. She’s writing a book, and she really talks about, you know, this like, a lot of times, I think it’s Sam Altman calls this, like, this time point in time the innovation age. And she’s like, no. It’s the age of imagination. Like, this is really not about again, like you said, innovating without optimizing. Like, there’s just do we need more innovation right now? No.
Amy Vaughan:
Because, honestly, it’s hard enough for us to keep up with it. But how can we start to be more imaginative? How can we use AI to actually enhance our ability to be creative? And I I will say too just, like, as a small business owner, you know, on the flip side of things, I know it’s it’s different for agencies, like, trying to adopt and figure out what are the right tools, what’s the right conversations, what are the right ways in which we could use it, how do we talk about using it with our clients. Like, so tricky. But I have to say as a small business owner and, honestly, like, one of my other favorite podcasts that we’ve had on, AI recently is with, Sarah Dooley talking about AI empowered moms and how it’s such a phenomenal tool, just even, like, a little life hack in ways in which you can like, I have gone and asked for, like, tips on meal prep and things like that based on, like, food allergies and concerns. I’ve used it as, like, a little book in the moment therapist for things when I’m, like, in a moment, and I need somebody to, like, help because it just rationalizes it. And it’s got all the CBTs, so cognitive behavioral therapy, like, trained up on it. So yeah. No.
Amy Vaughan:
It’s not gonna replace your therapist. However, in a moment, like, honestly, it at least gets you to slow down and think. And so I’ve used it to plan parties for my kids. I’ve used it for so many different wild things that I would like, it ‘s the Swiss army knife moment. Right? That’s the unlocking is when you start to realize that, you know, yes. It is a great tool, and, yes, it’s something we should be working to champion and educate those at work to be aware of and how we use it, when we use it, all of that. But, also, I think another way to maybe drive down that fear is just kind of start finding fun ways at home to use it.
Lexi Trimpe:
And you might be surprised because, like you said, that pattern recognition is real. And it’s new, like, deep research capabilities have just been wild. Yes. That’s why I always try to show a couple of personal use cases whenever we do a roll out or things on those lines just because, again, it gets us using it. But the mobile app of Chad GPT, the number of times that I just take pictures of things and ask it to tell me about it. I’m a thrifter. Love the thrift.
Amy Vaughan:
I love it.
Lexi Trimpe:
A bunch of weird old patches and pins and things. The number of times I’ve told it to do deep research on it for me and tell me all the history. Stuff like that just takes the ability of something I couldn’t Google before.
Amy Vaughan:
Mhmm.
Lexi Trimpe:
Yeah. Again, just finding those really use cases. What do you wanna know? What do you wanna do? I coded my first JavaScript app in my life the other day. I’m not an engineer, but I got rid of 26,000 emails.
Amy Vaughan:
Right? Oh my gosh. I need this.
Lexi Trimpe:
Oh, right? I was gonna say I spent two hours making the app, but clearing out all the emails. Oh my gosh. It’s amazing. Opening up new avenues of creativity that just previously weren’t even possible, which is so cool.
Amy Vaughan:
That is so cool. Yeah. I’m excited to see where it goes. Also within health care, like, I’m excited there just because there’s so much just for diagnosis and things like that, there’s so much complexities behind, like, a series of, like, test and conversations and symptoms over the years, months, whatever that don’t get tracked, that don’t have pattern, that that anything that the human brain can, like, recognize and and realize. I think we’re gonna see a lot of innovation, I think, in the health care space too. Because I think that pattern recognition is essential in understanding how our minds and our bodies are working. There was another example I was thinking of too, actually, as you were talking, and then it left my I left my non AI powered brain. If I think of it, I’ll bring it back up.
Amy Vaughan:
But, yeah, there’s so many cool and fun and interesting use cases out there, and I do think it’s you know, what are the things that you find belaboring that you would rather off put to, you know, to, like you said, a Copilot. Oh, that’s what it was. Tech support. I have used it for tech support where I’m like, I am struggling with this thing. How do I create like, even, like, setting up zaps. I’m like, I wanna set up a zap for this and that and the other. And I’m like, how do I even do that? It is like a super powered search engine. Right? Because instead of just giving me general search results, it’s actually specifically answering my question. So, yeah, tech support’s been another kind of lifesaver for me.
Lexi Trimpe:
Because I don’t know how to hack life. I swear. My biggest hack is if you were looking up, which I hate Facebook questions, stop asking me Facebook questions. But the Meta AI
Amy Vaughan:
Yeah.
Lexi Trimpe:
I ask it every Facebook question that comes into me because I know it’s a direct knowledge base. Oh. Similar thing. Bing owns or I’m sorry. Microsoft owns Copilot. Microsoft also owns LinkedIn. Go ahead and ask, that Copilot any of your LinkedIn questions. I try to match them up where it makes sense. Yes. Just knowing that they’re gonna have way more access to those knowledge bases.
Amy Vaughan:
And like you said, like, having that understanding helps you know how to use the tool smarter because you’re asking the right tool to do the right job.
Lexi Trimpe:
Ah. Google Ads questions go to Gemini. Right? You’re able to kind of ask the right ones.
Amy Vaughan:
Oh, that’s great tips. Like, I love that. I know some people are gonna take that home for sure. Alright. I have a fun little bonus question before we move on to our power round questions unless we get questions from the audience. I am curious, and this is, like, the latest breaking news. Right? And AI is now we’re being asked not to say please and thank you. Have you seen this on AI? Because, apparently, we’re, like, burning down the world and all of the power and energy that it takes for all of this stuff to compute. We’re being requested not to say please and thank you. Will you continue to say please and thank you to AI? And do you already?
Lexi Trimpe:
Yeah. Here’s the deal. I’m always gonna phrase my input the way that I want my input to come back out. And if I don’t want it to be a bit, I’m gonna be nice to it.
Amy Vaughan:
Right.
Lexi Trimpe:
Beyond that, I think if we’re worried about the, you know, data processing, we probably should stop making studio goodly images, but it’s fine. There are probably bigger concerns
Amy Vaughan:
than the
Lexi Trimpe:
please and thank you. Yeah. I agree. But I think this is where that intentional usage really goes far.
Amy Vaughan:
I love it. I love that answer. That is so great. Yeah. Can we attack some other things other than just genuine? Like, just courtesy, you know, because, like, you’re right.
Lexi Trimpe:
Down for all of last week because of the image generation. So if we could stop that first, it’d be great.
Amy Vaughan:
Right? Oh, I hear you there, Fred. Alright. Let’s get to these power round questions. Alright. I had to ask because it just keeps coming up, and I’m like, you know, I’m just curious.
Lexi Trimpe:
All of my coworkers have asked me this week if I had a can, I won’t lie?
Amy Vaughan:
I believe it. Alright. What does one AI tell people that they tend to overlook but shouldn’t?
Lexi Trimpe:
So I hear it a lot, but maybe not this feature, but notebook l m from Google for deep research, but also that podcast ability within the last couple of months, they introduced the interactive ability. So you can, like, interrupt them and ask them questions now and, like, direct the conversation.
Amy Vaughan:
Mhmm.
Lexi Trimpe:
That’s super useful for me, in all that life. Again, you know, a live person to bounce ideas off of, which is so cool.
Amy Vaughan:
No. It is, really. It’s like the best little intern ever. I love it. Alright. Fill in the blank. The biggest mistake people make with GenAI is?
Lexi Trimpe:
Starting with the tools instead of understanding what they’re trying to solve for.
Amy Vaughan:
I love it. Yep. Exactly. Alright. What’s your favorite moment you’ve witnessed when introducing AI to someone else?
Lexi Trimpe:
Lately, it has been basically any of the ways outside of content generation. Specifically, the deep research when people get to see a, everything that comes back and then all of this, like, citations for it, they’re blown away every time, and it is super cool.
Amy Vaughan:
It’s like my little encyclopedia set. They’re just exploding and becoming infinite.
Lexi Trimpe:
That site. It’s right there for me. It’s so nice.
Amy Vaughan:
Oh, it’s amazing. I love it. Yeah. It’s gonna help a lot with a lot of things. Alright. Last one. What is one thing about AI you wish everyone understood, but most don’t?
Lexi Trimpe:
Hallucinations are not glitches. They’re ultimately, like, baked into how the models work. Right? So validating your output is always going to be nonnegotiable before you put it outwards.
Amy Vaughan:
Yeah. I love it. That’s a great frame of reference for us to kind of keep in our little back pockets there as we continue. Lexi, this has been amazing. Thank you so much. Again, all these insights have been really helpful. The tips, the just the practical advice, just really kind of helping build out and navigate the lands AI landscape with some intention and purpose. You know, it’s just really helpful because, you know, if it does it’s all moving fast.
Amy Vaughan:
It’s all moving furiously, and it can feel a little overwhelming, but it doesn’t have to. I think your measured approach, your open mind about it, I think all of it’s, you know, a really great example for those who are trying to do the same out there in the world. So thank you so much for sharing with us today.
Lexi Trimpe:
Thank you so much for having me. This was super fun.
Amy Vaughan:
Absolutely. Yeah. Long overdue, but, you know, right at the right at the right time. Right? We’re all sitting in the thick of this right now. So everyone who’s listening, be sure to check out our past recordings. All of our PowerEdge sessions are available on YouTube. Also, anywhere that you stream and listen to your favorite podcasts, you can stay updated by subscribing to any of those channels. Definitely, if you have felt like you’ve learned something here today, you’re feeling a little less alone, and you’re looking to meet and connect with more amazing women like myself and Lexi who are just really here and excited to, again, just nerd out together, you know, and come together and nerd out.
Amy Vaughan:
And, also, we’re just really wicked smart and generous. Definitely check out and learn more about Together Digital, Together in Digital dot com. Lexi, I’m excited to come up to Michigan and see you next month.
Lexi Trimpe:
I like this one too.
Amy Vaughan:
Right? Yeah. Absolutely. Michigan, come to our events.
Lexi Trimpe:
Again, together, digital ones are typically open as well if you’re looking to get your talent.
Amy Vaughan:
Absolutely. Absolutely. Yep. We’re excited to have you all here. We’ll be back next Friday, so we hope you join us then. And until then, everyone, keep asking, keep giving, and keep growing.
