Ep 722: How to Build a Team of AI-savvy Marketers

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Building AI-Savvy Marketing Teams: Specific Strategies for Sustainable Impact

Amid rapid AI advancements, marketing teams face mounting pressure to adapt and scale their capabilities. Recent insights reveal a detailed, actionable approach that cuts through generalities and addresses the real challenges decision makers are facing today.

The Foundation: Structure Before Experimentation in AI Marketing

Initial AI adoption in marketing typically begins as unsupervised experimentation. This approach offers value but often lacks clear business outcomes. Establishing a defined strategy, such as forming an AI council within the marketing team, creates a central hub for setting objectives and tracking AI experiments. This allows for learnings to be surfaced at the leadership level, ensuring that AI adoption is not just a series of isolated wins but part of organizational learning.

Prioritizing structured workflows early—like encoding brand voice into AI outputs and repeatable AI-driven processes—ensures consistency and protects core brand equity, even as the pace of AI tool innovation accelerates.

Selecting and Scaling the Right AI Marketing Tools

The landscape is crowded with AI-specific marketing tools and platforms integrating native AI features. Instead of purchasing every trending product, marketers benefit from first providing all staff access to versatile tools with broad applicability. This facilitates effective education and training at scale—critical when deploying new technology to teams exceeding 100 members.

Once baseline proficiency is established, high-impact roles benefit from specialized tools tailored to distinct functions, such as SEO-focused AI platforms. Use cases can then be refined on a per-team basis, increasing AI’s direct contribution to business objectives like content velocity, pipeline impact, and conversion rates.

Mistakes to Avoid: The Myth of End-to-End AI Marketing

Early assumptions that AI would singularly deliver high-quality, end-to-end work for marketers proved optimistic. The reality is that AI outputs often require significant guidance—especially in prompt engineering and final human curation. Outputs may lack brand consistency or fall short creatively unless systems are clearly defined and team members are trained to use AI as an extension, rather than a replacement, of existing workflows.

Organizational Evolution: New Roles for AI Marketing Maturity

A tactical yet often overlooked approach is to create specialized roles focused solely on AI adoption and integration. Examples include dedicated AI and creative technology strategists embedded in creative departments, tasked with evaluating and implementing the latest tools, and directors of AI marketing transformation overseeing cross-functional adoption.

Rather than merely layering AI atop traditional marketing structures, leadership can reimagine org charts to accelerate transformation, ensuring that both the technology and the people evolve together.

Maintaining Marketing Differentiation Amidst AI Slop

As AI-generated content becomes ubiquitous, the risk is an influx of generic, low-value marketing outputs—so-called “AI slop.” Leading organizations counteract this by leaning harder into authentic, human-driven content that maintains brand voice and delivers true value to consumers. Platforms and detection tools are increasingly labeling or filtering out synthetic content, raising the stakes for distinctive quality. High-performing teams focus on the blend: using AI to scale, while human expertise and taste elevate the final deliverable.

Redefining Who Can Be a Marketer in the Age of AI

AI tools are lowering traditional barriers, enabling new entrants without deep marketing backgrounds to perform at a proficient level. However, core marketing intuition, ideation, and breakthrough strategy remain difficult to automate. Small teams especially benefit from AI’s power to cover a wider range of activities, but specialized expertise and strategic know-how are still critical for high-value results.

Future-Proofing AI Marketing Teams

Given the velocity of AI tool evolution, future-proofing is less about long-term projections and more about fostering a culture of relentless learning and structured experimentation. Creating dedicated roles for AI vision and workflow integration ensures sustained progress, even as team structure or core tools shift.

Conclusion: Business Value from Structured AI Marketing Adoption

The path to an AI-savvy marketing team is not defined by the adoption of a single tool, but by an intentional strategy built on structured learning, cross-functional integration, and a focus on business outcomes over short-term productivity metrics. Teams that prioritize experimentation within a framework, proactively assign responsibility for AI evaluation and integration, and balance automation with human creativity are positioned to generate measurable, repeatable value—well beyond simply keeping up with the pace of AI change.

Topics Covered in This Episode:

1. Sprout Social's AI-Powered Marketing Tools
2. Building an AI Savvy Marketing Team
3. Implementing AI Strategy in Marketing Departments
4. Evolving Marketer Roles with Generative AI
5. AI Tool Selection and Workflow Integration
6. Measuring AI Impact on Marketing Performance
7. Creating New Roles for AI Transformation
8. Combating AI-Generated Content Slop
9. Future-Proofing Teams for Rapid AI Advancements
10. Aligning Marketing, Sales, and Product with AI

Episode Transcript 

Jordan Wilson [00:00:16]:
The role of marketers seems like it's changing faster than even I can keep up with. I mean, I have a little bit of a background in marketing. I've done some sort of Martech comms for twenty plus years working with some big brands. So I understand even before AI, how difficult it was to be a savvy marketer. But I think generative AI and large language models have changed that completely. That's because the capabilities have changed and what any, even entry level marketer can now do with the right AI tool at the right time, I think far, like, exceeds of maybe what I could have done ten or fifteen years ago with a decent amount of experience. So for those people who are building teams, I understand how difficult it can be. But on today's show, we're gonna be tackling that head on with an expert on how to build a team of AI savvy marketers.

Jordan Wilson [00:01:13]:
So if if that's something that's been on your checklist for 2026, today's show is for you. Alright. I'm excited to get started. Hope you are too. Welcome to Everyday AI. What's going on? My name is Jordan Wilson, and this thing's for you. It is the unedited, unscripted daily livestream podcast and free daily newsletter helping everyday business leaders like you and me keep up with the nonstop advancements of AI, how to make sense of it all to grow our companies and our career. So if you're trying to do that, sweet.

Jordan Wilson [00:01:41]:
Me too. Starts here. We're doing this journey together. But to take them to the next level, make sure you go to our website, youreverydayai.com. We're gonna be recapping today's conversation in the daily, newsletter as well as keeping you up to date with all of the other AI news that you need to know. All right. Enough of me chit chatting. Let's bring on someone super smart.

Jordan Wilson [00:02:02]:
So, you know, someone that's leading marketer, marketing, I think in a big way. So live stream audience, please help me welcome to the show, Scott Morris, who is the CMO of Sprout Social. Scott, thanks so much for joining the Everyday AI Show.

Scott Morris [00:02:16]:
Thank you so much, Jordan. Great to be here. Thank you.

Jordan Wilson [00:02:18]:
Alright. So you've maybe heard of Sprout Social, maybe you haven't. But for those that haven't, Scott, give us the rundown. What is Sprout Social?

Scott Morris [00:02:27]:
Sure. So Sprout Social is basically a social media management platform. So quite simply, it allows brands to manage their social media across all the different networks. So to be able to manage your accounts on x and on LinkedIn and every place else, to be able to post and publish everywhere, manage the conversations, run analysis actually on what's happening, and manage influencer marketing as well.

Jordan Wilson [00:02:50]:
And, you you know, just just so people know, I'm sure that you've sprinkled in AI in your platform. But just tell us a little bit about how, you know, on your customer side, because we're gonna dive into your internal side first. But, you know, what, AI features and tools are available right now for those people that are using your platform?

Scott Morris [00:03:06]:
Yeah. Sure. Like a lot of companies, we've been introducing AI tools over the last couple of years. Started typically, you know, the same way that you and I probably started using AI and AgenTek AI mainly around sort of content and helping people craft, for example, in our case, posts. Right? So we have AI assist that allows you to keep prompts and gives you some ideas for, social posts to help you craft those posts to basically publish content faster. So that's really where we started. And then we sort of moved into, well, how can you also use AI to actually do a better job analyzing, all the social data that you have and making sense and actually getting some insights out of all of that. And now we're moving into really the age of agentic AI in our tools.

Scott Morris [00:03:51]:
We introduced, something earlier last year called Trellis. It's a it's Sprouts AI agent, and it's really designed to move beyond sort of basic assistance to a more proactive system that accelerates complex analysis. So, basically, think about this as you're able to, work with the AI agent. You're able to ask it a question. For example, it might have access to all of your social listening data, and you might wanna ask it a question. You could be at, Honda, and you wanted, you have a social listening topic around, electric vehicles because you wanna stay on top of what's happening in the conversations in social around electric vehicles. You can actually ask Trellis a question around that. It will quickly analyze everything that it's heard via our social listening platform and come back to you, with some insights.

Jordan Wilson [00:04:39]:
Oh, love it. So, you know, one thing that you mentioned there is, you know, I think a lot of people dipped their toe into AI with some form of content marketing because, you know, in the earlier days of large language models, right, when it was kinda just chat GPT and, obviously, there were some tools that predated that, but, you know, we're simply just creating written content. So, I wanna fast forward and go to the end here, Scott, but then we're gonna rewind to that. Answer the question. Let's do it. How do you actually build a team of AI savvy marketers when the AI tools are growing and expanding their capabilities so quickly. How do you get it done?

Scott Morris [00:05:17]:
Yeah. It it's it's a lot to keep up with. Right? I mean, for all of us, keeping up with AI can be difficult. And for anyone in their job, figuring out the right way to use AI, incorporate it into what they do, the right tools they use, even the tools. I mean, we onboarded some tools two years ago that were doing really amazing things for us. And in some cases, we're not using those anymore because other tools have either emerged or some of the core platforms. Like, we're we're kind of a Google shop. So Gemini has advanced so much in the last couple of years that it can do some of the things that those custom tools were doing before.

Scott Morris [00:05:50]:
But for me, you know, I really, really focus on the foundation first. You know, I got to Sprout a little over two years ago, December 2023. And, people were experimenting with AI, but there wasn't, like, a coordinated strategy in marketing. So that's the first thing that anyone, I think, should do is experimentation is great, but try to come up with a clear set of objectives that you're trying to achieve. I actually created an AI council at Sprout. So we had a couple of the marketing team members on it led by one of my team leaders to really define, the outcomes that we're looking for from AI and then to encourage and manage and track and report on all of that experimentation that all those individual teams were doing so that we could get those learnings and surface those really at the highest level in the organization. Over time, then that's evolved. I mean, as you mentioned, you know, mainly, it was like content creation at the beginning.

Scott Morris [00:06:44]:
So my content team, they were the first ones to obviously leverage AI to be able to craft blog posts and things like that. Very, very basic stuff. At least that's the way we think about it now. So fast forward to a couple years later, and we're really, really focused now on business outcomes. So a couple of examples of that would be, it's not just about the amount of content that you publish. It's what is the, impact on our pipeline or on our conversion rates, when you get a trial list in. Are they converting any faster to be a paid, customer of ours? Those types of things. Also, you know, in marketing, our strongest partner is usually our sales team and then also our product team.

Scott Morris [00:07:23]:
And so, really, how can you leverage AI to be a force multiplier for those things? So it's not just about the marketing team in a silo leveraging AI doing their things. It's really about how the marketing team, sales team, the product team are together aligning around some of the same goals and really thinking about it from a customer first perspective. I have a dream that, you know, we will get to the point where entire customer journeys are a 100% orchestrated by AI. Some companies are doing that today. We're not quite there yet.

Jordan Wilson [00:07:54]:
So, you know, you kind of walked us through what, probably is feeling very relatable to a lot. Right? I think a lot of the early days, you know, 2022, 2023, you know, teams were using AI to try to write more or maybe better content for blog, for social media, etcetera. Right? So as you started to make that shift internally, right, when you started, there in December 2023, what were the signals that you maybe looked for, or what was kind of the writing on the wall that said, okay. This is working, but we need to bring this to other areas of the organization, and we need to go deeper. What is that, those key metrics that you're looking at that you can say, okay. Yes. This is working. We're starting to get a return on what we're putting in.

Scott Morris [00:08:40]:
Yeah. Well, I think in those early stages, as I mentioned, you know, it was a little bit wild wild west. Right? And it was all about individual experimentation. And I think that actually is the appropriate place to start. Right? People needed to get their hands dirty a little bit with this technology and try different tools and and just really experiment kind of in their own little area, in their in their little silo, if you will. But it became clear pretty quickly that while that was great, it was really hard to tie that to any really meaningful outcomes and metrics, you know, other than, again, we could double the amount of blog post that we create or something like that. So what? Right? So you can create more blog posts. Like, what's the goal of doing that, and is it actually impacting the business? And so I think that's when we sort of made that shift and got into that next stage of how the teams were using AI and also focused more on what I would call structured workflow adoption.

Scott Morris [00:09:39]:
Right? So it's not just everyone kind of doing their own thing. It's like, how can we actually build systems, over time and make sure we have things like our brand voice encoded into everything that we do? How can we create more repeatable workflows, leveraging AI, of course? And, and how can we, you know, better train the marketers to really think about AI as a thought partner and as an extension of the work that they're doing as well.

Jordan Wilson [00:10:11]:
So, you know, what were maybe some, looking back at, you know, maybe where you are now? And you kind of said, you know, there's there's still work to be done, but maybe where you're at now is, you know, far better than where you were at in twenty twenty three, December. Right? What were some of those key decisions that you're like, okay. When it came to growing, in in AI savvy marketing team, what were some of the decisions that you had to make, that you can look back at now and say, oh, that was the right decision. But maybe at the time, you're like, is this the right way to go?

Scott Morris [00:10:44]:
Yeah. I think so one of them was, you know, what tools do you actually make available to your marketers? Right? There's so many out there. There are AI specific tools. Increasingly, of course, all of the sort of platforms and tooling that marketers use have AI built in them like our own, right, like Sprout's own. And so I think one of the first things was getting, some tooling into the hands of all marketers that could be used with the wide variety of use cases so that we could also invest in education across the entire marketing org. I have about a 130 marketers on my team. So by by putting some tools in their hands that everyone had access to, it allowed us to scale allowed us to scale the education and the training that we would do with them. Right? So that was the first thing that we did, and then we started introducing more use case specific tooling.

Scott Morris [00:11:36]:
Right? Something, for the SEO team to use. There's a product called AirOps, for example, that the team uses to really scale content leveraging AI, but that's not used by the, you know, PR team. Right? And so looking at, tools that would make sense for each of those individual teams, and then see what sort of interesting outcomes they can get from those as well. So those were some of the things we started doing.

Jordan Wilson [00:12:00]:
What were some, maybe decisions or initiatives along the way that you made? And at the time, you're like, yeah. This this is gonna work, but maybe, decisions that didn't pan out the right way. Right? Like, what are those mistakes when you're trying to, you know, make your marketing team more AI native? What are the mistakes that you made along the way?

Scott Morris [00:12:21]:
Oh, well, there are many. One of them that I will, talk a little bit about is, you know, I sort of thought at the beginning, I thought of AI as being a bit of an end to end solution for our marketers. Like, oh, look at what this can do. If you just put this AI in the hands of the marketer, they're gonna be able to have really, really fast output for of really high quality product. And what I definitely realized is it's more of a middle to middle type of thing with AI. Right? It really is about training and educating the marketers in terms of how they get started. The prompt engineering is so important as we all know. And then also getting them to understand that what it gives them is probably not the final output, especially if they haven't actually leveraged something like, you know, a a a gem in Gemini or something like that that has our brand voice embedded in it.

Scott Morris [00:13:13]:
They might get something that doesn't sound at all like it actually came from Sprout. And so, that's one of the things that that I definitely learned early on, is that it's really more of a middle to middle type of solution.

Jordan Wilson [00:13:24]:
You know, one thing myself with a little bit of, you know, marketing experience, I was actually thinking about this, you know, last week when, you know, speaking of Google, you know, their new, Pameli, photoshoot feature. Right? Like, I remember it, right? I used to work a lot with Nike and Jordan Brand, and, you know, I look back and reflect on some of these projects where, you know, I was the the T shirt designer, I was the photographer, I was the illustrator, and I did, you know, all these different things. And now one tool can do it way better in sometimes 1% of the time. Right? How can you keep up and project kind of that, you know, skill building moving forward when sometimes, you know, these tools come in and, yes, they're extremely, extremely useful and can create, you know, a lot on the business value side. But, you know, even for someone that's maybe built their whole career right on, hey. This is my identity as a marketer. Right? And then all of a sudden now, these set of tools do it way better. How do you, kind of adjust to that?

Scott Morris [00:14:29]:
Yeah. So that's an interesting one. I think let's talk about creative specifically. Right? You gave a couple of examples there. And I think that's an area where in the early stages of Gen AI, it sucked. Like, let's just be honest. Right? The output that you would get, really did suck. And so it was one of the my creative team, in fact, what they not at all that they were the slowest to adopt AI, but, the tools that were available to them when you compare that to the quality that you would get, from someone who had spent, you know, years studying, you know, graphic design, etcetera, and then the output they would get, you know, it just it it paled in comparison to some of the other use cases for ad AI.

Scott Morris [00:15:12]:
That has really changed a lot in the last six to twelve months. I think that, there are so many great tools available that have come so far in terms of the quality of the output. So it is tricky. Right? Because you have to, it it it's a difficult situation to be in if you're someone who's been trained to do that, and now you have technology that's doing a lot that can do a lot of that for you. So, again, it's really about teaching them how to use the AI and how to, extend their own workflows. Another thing that we've done is we're creating, a bunch of roles within marketing that are very specifically focused on helping the teams, better adopt the AI workflow. So I'll use the example of creative and my creative team. We created a new role, a senior AI and creative technology strategist.

Scott Morris [00:16:01]:
And his only job is to basically be evaluating tools all the time, looking at how we can integrate those into workflows to extend the work the teams are doing and building systems that are, again, you know, repeatable, that the entire team can kind of tap into. So I think that's a piece of this that people should not, disregard is it's not just about putting AI in the hands of all of the existing team members. You should think about obviously, people are thinking about org structure and what you know, how many of each role are even needed when you have AI to support the work that they're doing, but also these net new roles that can be created that will help accelerate and advance the work you're trying to do. I'm doing that in other areas as well. We're, you know, creating a director of AI marketing transformation role who will help, like, kind of manage all of this together as one package as well.

Jordan Wilson [00:16:58]:
AI moves too fast to follow, but you're expected to keep up. Otherwise, your career or company might lag behind while AI native competitors leap ahead. But you don't have ten hours a day to understand it all. That's what I do for you. But after 700 plus episodes of Everyday AI, the most common questions I get is, where do I start? That's why we created the Start Here series, an ongoing podcast series of more than a dozen episodes you can listen to in order. It covers the AI basics for beginners and sharpens the skills of AI champions pushing their companies forward. In the ongoing series, we explain complex trends in simple language that you can turn into action. There's three ways to jump in.

Jordan Wilson [00:17:42]:
Number one, go scroll back to the first one in episode six ninety one. Number two, tap the link in your show notes at any time for the Start Here series, or you can just go to starthereseries.com, which also gives you free access to our inner circle community where you can connect with other business leaders doing the same. The Start Here series will slow down the pace of AI so you can get ahead. Yeah. That's a great point. You know, even talking about, you know, roles that don't exist now, and I think that's smart. Right? So if you're out there listening, if you're the CEO and you're trying to grow your marketing department, you know, I I think what Scott just said there is extremely important. It's something I've talked about for for years, actually.

Jordan Wilson [00:18:26]:
I think a lot of roles are gonna maybe turn into more taste making roles. Right? Providing agentic systems, you know, good input and context on the front end, and then really having to have that taste on the back end. And in doing that, Scott, right, we talked about some of these, you know, tools now. You you know, large language models agentic by nature. Right, they can do you know, stitch together multiple things now, whereas six months ago, us humans had to be the duct tape in between those things. Mhmm. Does this even change who can be a marketer? Right? Can an AI savvy marketer be anyone, or do you think you still kind of need that, you know, foundational, you you know, experience, you you know, educational background to really, be an AI savvy marketer in the future?

Scott Morris [00:19:12]:
I think the answer is probably yes and no. Right? Like a lot of other things. I think that it sort of depends on the discipline within marketing. I think there are some where people could step in without a marketing background, without that education that traditionally they've had, and they would be able, through the use of AI tools and other things, be able to pretty proficiently be able to do the work that historically maybe had been done, by someone who specialized in that. And then there's a lot of other areas where I don't think that's the case at all. I think there's certainly a lot around intuition. I think, you know, people, good marketers know good marketing, and I think that, AI can't necessarily replace that. Even on the ideation front, you know, which is an area where Jet AI can actually do a really good job, I haven't necessarily seen some of the same level of breakthrough ideas that I get, for example, from, say, the creative directors of the campaign team that I have.

Scott Morris [00:20:12]:
So I definitely think that, it maybe opens up marketing to be more accessible to folks. And especially if you're at a small business where you're you're not gonna be able to have, you know, a million employees all with specialized roles and you have to have people who are kind of, jack of all trades. I think it gives, AI will make it easier to do more of the marketing activities than maybe you could do before on your own. But I certainly don't think it completely replaces the marketing, team, including the some of the specialty areas that we have.

Jordan Wilson [00:20:41]:
You know, one thing that I think about a lot when it comes to, you know, content. Right? Because in the end, marketers create content. Right? They do more than that, but, you know, from a straight output or deliverable, that's usually what is, you know, the start of the journey. But, you know, one thing I'm always, thinking about is the consumerism. Right? Because the the the input and the output, of what a smart marketer is going to do, that's always going to change. But in the end, right, it still needs to resonate with the end consumer, the end client, etcetera. And, you know, there's obviously because of AI, there's been this surge of work slop. Right? Seeing the same low effort, low quality, type of creative that sometimes originates in a marketing department.

Jordan Wilson [00:21:26]:
So, you know, moving forward and kind of planning for a future where, you know, I've been saying this for years. I I I feel like I'm just drowning, you know, in AI work slop sometimes. So how do the smart marketers, you know, really still use AI but have enough of that, you know, human touch that is like, okay. This isn't like the other 9,000 pieces of content that you probably saw today that were AI generated.

Scott Morris [00:21:52]:
Yeah. AI slop is definitely a problem. Right? And if we just look at social, for example, because that's the space where my company, you know, helps brand manage brands manage their social. You know, social feeds, you could argue, are are turning into AI slop. Right? We've all seen so much of it.

Jordan Wilson [00:22:10]:
Actually, the comments. Right?

Scott Morris [00:22:12]:
Well, especially the comments. Yeah. Yeah. Yeah. Because AI is making content easier to produce, which, of course, is resulting in some of that AI slop. But what I think is interesting is that, what we've seen at least is that marketers, creators, brands are also leaning harder into authentic human driven content because that's actually what audiences value the most. And I think at the same time, you've got platforms, you know, like, Meta and TikTok that are labeling ad generated content or investing in, you know, detection tools and transparency measures to reduce maybe the more misleading or low quality, synthetic media that you might see. So, you know, I think it's it's a real mix of things, but, you know, how you actually, deliver really, really high quality leveraging AI is is an is sort of an ongoing struggle that, that will always be something we have to balance.

Jordan Wilson [00:23:09]:
Yeah. So, you know, I've I've spent, every single day for the last three years covering AI, all the advancements, you know, thousands of hours using all of the tools. And I'll say, especially the last three months, I've felt a shift, both in term of the accessibility, for AI tools, but also the increase in quality for the outputs. And, obviously, a lot of those would fall under the marketing category. Right? So you kind of walked us through your journey of the past two years of, you know, steps that you've taken at Sprouts to build an AI savvy team. So, I'm not gonna ask you to crystal ball it here, Scott, but as you look at the next two years, you you know, number one, are you seeing and feeling this same recent surge, in in, you know, AI's, output capabilities and quality? And then two, if so, how can you even plan ahead to make sure your team stays AI savvy?

Scott Morris [00:24:02]:
Yeah. You know, I was just having conversation with someone the other day about that, and we were talking about projecting out sort of sort of even even, like, the org design of the future. Right? And what will the marketing team look like, you know, three years from now? And it's like, three years from now. Like, six months from now, it's gonna be so different. Right? Just because it is it is changing, so incredibly quickly. Yeah. So what are some so I think everyone knows the tools are gonna get better and better, and everyone knows that the output that you're gonna get from them is gonna be higher and higher quality. So I think it really is about just how do you always try to stay one step ahead of that.

Scott Morris [00:24:41]:
And it feels like you're running really, really fast if you're trying to stay one step ahead of that. I do think, you know, really encouraging, a culture of learning and innovation around AI tooling and be willing to experiment with it. That's super, super important. I do think, as I mentioned earlier, having some of these dedicated roles where people, they spend all of their time thinking about what that's gonna look like six months, a year, two or three years from now. I think, you need to have people who can kind of set aside the the brain time to be able to do that, because you're never probably gonna be able to do it all entirely on your own.

Jordan Wilson [00:25:19]:
Alright. So, you know, Scott, we've covered a lot in today's conversation from using AI on the marketing side to, you know, being a force multiplier, not working in silos, you know, emphasizing the role of authentic human content. You know, but what's your one best piece of advice, for, decision makers moving forward who know that they need to create a team of AI savvy marketers? What's the one most important decision, that they can make today to get that process started?

Scott Morris [00:25:49]:
Oh, the most important decision they can make today. I would say I would go back to what I talked about earlier around being a force multiplier. I would say as you think about how you're going to invest in AI for marketing teams and how you're gonna be building those skills, you are gonna get so much more value out of those investments if you don't think of it sort of myopically and only focused on that marketing team and what the marketing output will be and if you really back it into business outcomes. And that's where I talked before, for example, making sure if, you know, in a b to b environment like I'm in and you've got a sales team and you've got a customer success team, you've got a marketing team, thinking about how those teams are gonna be working together from a customer point of view, to deliver better experiences that will give you really, really great business outcomes, you're gonna get that's gonna pay off for you many, many times more than if you really, really just focused on how do I make my marketers more productive.

Jordan Wilson [00:26:45]:
Scott, some great advice for, some questions that a lot of business leaders, are probably spending a lot of time on. So we thank you for taking time out of your day to join the Everyday AI Show. We really appreciate it.

Scott Morris [00:26:57]:
Thanks so much, Jordan. Great to be here.

Jordan Wilson [00:26:58]:
All right. And if you miss anything, y'all don't worry. We're gonna be recapping it all in today's newsletter. So, if you heard Scott say something, you're like, wait, what was that? Yeah. We're gonna have it for you. So if you haven't already, please go to youreverydayai.com. Sign Sign up for that free daily newsletter. Thank you for tuning in today.

Jordan Wilson [00:27:13]:
We hope to see you back tomorrow and every day for more everyday AI. Thanks, y'all.