Building the Modern Marketing Team in the AI Era:
Team structure, the skills that matter now, and where AI fits in

Courtney Kehl: Alrighty. Let me kick things off here, bear with me, I’m gonna share the slides, and then we’ll dive in. I know folks are just joining, so we’re right at the top of the hour.

Courtney Kehl: Cheers! There we go. Get all situated. How are you doing, Stephen?

Stephen Banbury: I’m doing good, yeah. Excited to be here with you today, talking about this. It’s very top of mind for everyone in marketing.

Courtney Kehl: Yeah, it is. We actually were just, as we were coming into this, just talking about the interest level has definitely spiked, more so than we’ve seen in the past. So I think things are kind of leveling off as far as where AI fits into the whole mold of things, and we’d love to dive into that.

Courtney Kehl: Give folks a couple more minutes, but as we’re… as we’re waiting for people to join as well, just kind of the overall topic is talking about the modern marketing team, now that we are fully in the AI era sort of what are the various skills that we’re seeing bubble up, as opposed to, you know, pre-AI. There’s, you know, the more formalized board of version of that. Where does it fit into the workflow? Just sort of the different advantages that do come with utilizing AI versus other scenarios where folks are looking at headcount and pulling things back and budget and such.

Courtney Kehl: So, with that… I think… I mean, we’re a minute past.

Courtney Kehl: I’m gonna go ahead and introduce Stephen Banbury. I’m thrilled to have you as our guest. Head of Marketing, we’ve actually worked together, gosh, what’s it been, 10 years? Off and on over the last 10 years?

Stephen Banbury: Sounds right.

Courtney Kehl: Different companies, and is currently heading up marketing and ClearlyRated. So I’ll leave you to kind of give the rest of your intro there, because I’m sure I won’t do it justice.

Stephen Banbury: No, no, it’s fine. I’m just gonna repeat what you have here.

Courtney Kehl: Yeah. Sure.

Stephen Banbury: what I would say is that picture of me that we have is actually not AI-generated. That is a human-designed picture.

Stephen Banbury: Just in case people are thinking, well, here you go, AI is everywhere. I lead the marketing function at a company called Clearly Rated. We are a client experience, a CX management platform.

Stephen Banbury: We serve professional services firms, so in AEC, architecture, engineering, construction, staffing, accounting, legal, and many others.

Stephen Banbury: And of course, I have a podcast called The CX Catalyst, so if you’re interested in client experience, then go check us out on the usual platforms. But, delighted to be here with you, Courtney.

Courtney Kehl: I love the podcast, but I didn’t actually realize you have that.

Courtney Kehl: Just out of curiosity, where… so, where do we find it? Where, like, is it a live podcast? How… give me more info.

Stephen Banbury: Yeah, no, well, we have live people on it, it’s AI agents, yeah. We basically, I’m interviewing CX experts within accounting and or consultants, or just people that spend their life looking to improve experiences of customers and clients, different to customer service and customer success. YouTube, Spotify, and, Apple Podcasts is where you’ll find us. So, yeah, having a lot of fun with it.

Courtney Kehl: That’s cool, very cool, I’ll have to check it out.

Courtney Kehl: Awesome. Well, let’s dive in. Just kind of recap, we’re going to go over the… how AI is shaping… reshaping the marketing team, and sort of what are the various forces behind that.

Courtney Kehl: What does that actually look like? The modern team, as we’re calling it. And then, of course, the skills that matter. So, we are finding that when you’re looking to hire folks, there’s specific skill set that is bubbling up and becoming more important. Where does AI actually fit into your day-to-day? Where does it fit into the org? I think that one’s definitely a valuable piece to dive in on. And then, of course, how do you actually make this practical and implement it, today, or in this quarter, ideally?

Courtney Kehl: So with that, let’s talk about the reshaping of the actual marketing team. Over to you.

Stephen Banbury: Yeah, so it’s an… I read, there’s a report out by McKinsey & Company, and it’s called The State of the Organization, for this year, and McKinsey talks about three, what they call, tectonic forces, that are reshaping organizations. Economic disruption, workforce shifts, and technology disruption. Which, of course, is AI. So when I think about the AI era today, you know, obviously you can read the slide, but output is definitely easier. Creating more impact is down to humans and being collaborative.

Stephen Banbury: When everything ladders up, when AI ladders up to your business strategy and outcomes, then it’s… it’s going to be way more, impactful.

Stephen Banbury: The old all chart, and we’ll get into that, and we’ll show a couple of those, is, you know, a little slow.

Stephen Banbury: Compared to organizations that are embracing and utilizing AI in the workflows and daily… their daily practice.

Stephen Banbury: And it’s really the team still. I think there was, there’s a lot of discussion around, you know, how AI agents can be replacing humans, but actually it’s the team often today that’s really differentiating, when you think about.

Stephen Banbury: You know, that human connection is actually more important than the way that humans have taste, in a way that, as you know, AI doesn’t always have. So, Yeah. So maybe we could go on to that next slide.

Courtney Kehl: Yeah, yeah.

Stephen Banbury: Where we talk about, yeah, what teams get wrong.

Stephen Banbury: Very good. Oh, yeah, perfect.

Stephen Banbury: So, to work well, AI needs to be much more than just a plug-and-play tool. You know, AI agents, AI and human employees, they really need to, like, collaborate together. And so, I think there was a thought that you would hire an AI engineer or an AI, you know, prompt expert.

Stephen Banbury: But that’s actually not particularly the smart thing to do. And then, we talk about confusing, well, more content with better marketing. So, I don’t think there’s anyone here today that hasn’t heard of the word AI slop.

Stephen Banbury: And in fact, I didn’t realize this until recently, but the Merriam-Webster dictionary, their word of the year in 2025 was SLOP.

Courtney Kehl: Wow.

Stephen Banbury: That just tells you how ubiquitous that is. And in fact, there’s an article in the New York Times just a few days ago where they talk about Spotify, LinkedIn, and others really trying to dig out what they call a digital sewage of low-quality content.

Stephen Banbury: So, you know, making sure that, you know, there’s a propensity to have, like, more human-involved content. It doesn’t mean you can’t be using AI, but not just purely AI content that’s being put out there in the wild, is important. And then.

Stephen Banbury: Another mistake I think people make is they… they treat it as either… either humans doing that, or it’s automated, and there’s no middle ground. And I think that’s a bit of mistake when you really look at the work to be done, and the outcomes that you’re trying to drive to.

Courtney Kehl: Yeah, yeah, 100%, all great points. I mean, the either-or piece is very eye-opening because it’s not an either-or. With AI tools the way that they are. Of course, we’re implementing them, but I do see them much more as something that we leverage as opposed to just giving ownership to.

Courtney Kehl: Great point. I want to encourage everybody to put in questions into the chat, and we’ll be sure to dive in on those. I just love this bit, because I did see this sort of surface over the last 6 months, and actually earlier, like, probably in January of this year, so I guess at this point, it’s almost 8 months ago.

Courtney Kehl: But essentially, the context around this is, I was being told to take a team of two dozen marketers, and then sort of flatline it to these key roles. The growth engineering would be a headcount, the marketing strategy is a headcount, and so on.

Courtney Kehl: So there would basically be a marketing team of 5 with the head of marketing or the VP.

Courtney Kehl: And then underneath this is really… the idea was to build out agents and have all of these different areas owned by an AI agent, with the actual human at the top, kind of orchestrating and overseeing the success… the success of that. This idea, 8 months ago had a lot of eyeballs, and it was circulating through, you know, a lot of different orgs and different companies that I spoke with. It has since shifted, and that pendulum has kind of come back. And so, with that said, let’s maybe talk through what the actual modern team looks like.

Courtney Kehl: Over to you.

Stephen Banbury: Yeah, I think the… the org chart that you showed is… feels a little dystopian.

Stephen Banbury: There are certainly areas, as we look into this, that you can outsource to AI, right? So when I think about this slide, it… I mean, AI has obviously impacted this, but I actually feel like this is how marketers should be thinking about their organizations regardless of AI, honestly.

Stephen Banbury: When I think about the team that we have is, you know, what are the outcomes that we’re driving to? So, what is the quality versus the quantity of output? And that could be, like, the assets that we’re doing. So, are we good gatekeepers? Are we being good brand stewards of the content that we’re putting out?

Stephen Banbury: Although I’m obviously still interested in generating leads and MQLs, actually, what the team… the KPIs that we have, the OKRs for the team are really around SQL, so Opportunity and Pipeline. So, you know, that’s definitely a shift,

Stephen Banbury: But something that we’ve always been very focused on. And then, you know, the some of the, kind of, day-to-day, very, kind of, like, manual aspects of what we’re doing they can be automated. So, like, the integration of, some of the, the, you know, whether it’s Claude or ChatGP or others, into some of the systems that we have and the tools that we use are allowing us to update, create all sorts of, like, new, wonderful things much more effectively.

Stephen Banbury: We can talk about the gating of that, but certainly there’s a creation of more of an end-to-end responsibility for the outcomes that we’re driving, whereas we could be having, like, multiple different people. So this is a lot around, like, having a proper, like, a DACI or a RACI model too, but, definitely having clear ownership around each of the outcomes is super important.

Courtney Kehl: I’ve got a question here, let me actually go backwards.

Stephen Banbury: Okay.

Courtney Kehl: Geared toward you, Stephen. Have you ever downsized your org as a result of AI?

Stephen Banbury: It’s a really good question, no, is the very simple answer to that. However, what I would… the two things I’ll say. One is… I have not been hired because of AI, so when I thought about the role that I was, thinking about hiring for, I thought about do I need a person for that, or can that activity be done by… or through AI utilizing that? And so, I’ve actually, you know, not expanded my team and got a new headcount, because I’m able to use these tools to make that team more efficient.

Stephen Banbury: The other thing I would say is, you know, we have natural attrition like all teams, like all companies, and so when we bring new people in.

Stephen Banbury: It’s really important, they don’t need to be necessarily AI-native, but they need to be practicing, adept at using these tools, and something that they’ve been using every day.

Stephen Banbury: Because that, that just brings in new smarts into the organization, more efficient, more efficiency. But, no, never let anyone go because of it, but, certainly have been much more thoughtful about new hiring.

Stephen Banbury: Or actually adding to the organization as well.

Courtney Kehl: Sure. We’ve seen that as well. Folks have stalled on their hiring. I do think that’s come back now, and we’re seeing a bit of a hiring burst now, or, you know, that’s picking up. But we even ourselves looked at having an AI operator.

Courtney Kehl: Thinking that that person could just guide all things AI. I think there’s a bit of a course correction on that. So this is… this is what we’re actually seeing, and then maybe you can talk through this, having your… your team as well, how you… how you lay it out.

Stephen Banbury: Yeah, I mean, there’s obviously, like, different functions within marketing. These are some of them, you know, and I’m really thinking, what are the what are the outcomes? What are these functions actually producing?

Stephen Banbury: And… versus, like, oh, I need a headcount to it’s not so much, like, the title and name, right? It’s more like, what is the activity that’s being driven, right? And there, that’s where you can see the gaps. Like, do I need a new person? Can I be more efficient? Can I outsource that? You know… I always think about, do I hire, do I do that inside, or do I outsource that, right, for an agency or something, which is always a good thing to do.

Stephen Banbury: So the head of growth marketing, brands ready, events. I mean, obviously, something like events is very physical. Like, we run these CX boot camps, which are, like, hands-on workshops for, like, 30 to 40 people. I’m not outsourcing any of that, right? That is, like human to human, very important. But other parts of this, you know, we’re definitely… I mean, I think you… at the bottom of this, we have, like, revenue operations, so, for me, specifically, that’s marketing operations.

Stephen Banbury: We’re using AI tools across all of these different verticals, whether that’s growth, brand, outreach, for example AI is playing an important part, so instead of adding it into each box, we can just, like, run that along as just, like, something people are using, like, every single day for some aspect of what they’re doing.

Courtney Kehl: Right, I think that’s a big takeaway. It’s the underlying, sort of, platforms and foundation that then support each of these various work streams. And with that, I mean, that’s kind of where those skills, the human skills versus the AI tools, and which one for what, and who for what, plays a big, big part of this conversation. I will say, for us, I’m always encouraging folks to just start using AI, and that’s last year, about this time, just use GPT, use Cloud, use Perplexity, I mean, dive in, and then you’ll get more comfortable. And fast forward now, there’s certain… certain ones I use for certain things, but I don’t lock myself into that because of how fast the changes are, and how the releases are… they’re all catching up with each other in different ways.

Courtney Kehl: Anyways, it is… it’s… it’s certainly a fun time. But around the skills and with the human… the human pieces versus the human elements versus the AI elements.

Courtney Kehl: We are seeing there’s certain areas that go… that are… are bubbling up.

Courtney Kehl: And is this… is this… was this me that talked… no, this is over to you, Steven. Go ahead, give it a whirl.

Stephen Banbury: I mean, this is kind of an old quote, but, an organization called the AI Marketing Institute, they kind of rebranded and been super successful. They ran a… they still run a podcast.

Stephen Banbury: And they said that, you know, AI isn’t going to replace marketing but marketers that aren’t using AI will be replaced by those that do.

Courtney Kehl: Sure.

Stephen Banbury: And you can insert that into pretty much every function, right, across the board. Whether that’s sales, or ops, or whatever. So, but in terms of, like, the impact AI delivers value where it’s clearly linked to strategic goals and business outcomes, we’ve kind of said that, and so rising in value is the strategic thinking.

Stephen Banbury: Editorial judgment, taste, right? That’s something that, you know, in the world of design and branding, for example, you can certainly iterate quickly, but you really need a human hand at the tiller, right?

Stephen Banbury: I watched The Odyssey the other day, so I’ve got, sort of like, the boat and steering the… steering the ship in my mind, so sorry for the water-filled analogy. But, you know, data interpretation, certainly AI is very important. You can bubble up themes, do sentiment analysis very quickly, because you can get through that data, but the interpretation and actual judgment around that, and then what you do with it, is super important. And then, you know, actually orchestrating across an organization so that you’re all on the same page is very much human-forward.

Stephen Banbury: When I think about… You know, an example of ourselves, if we are… we have a state of the industry report that we put out. We do one around buyer’s insights, for example. So we have a designer who is designing the template.

Stephen Banbury: We have a writer who’s doing the analysis with the data analytics team and writing that piece.

Stephen Banbury: But… We can then, once we have that, we can then repeat it very easily by using AI because we have the template, because we have the words, to generate that report.

Stephen Banbury: But then you just don’t put it back in the wild again, you actually have to have a human… you need the writer to make sure it’s all written properly, the designer that it’s all, like, designed properly before you put it out. So, you know, that’s working in conjunction with AI.

Stephen Banbury: Positioning messaging, customer empathy, I sort of thought about this, currently, where… is it rising in value or holding steady, and when I think about this, I might put it in rising in value more, just because I think that, with AI agents, that human connection is more important than ever.
Stephen Banbury: And so, you know, creating experiences human-to-human versus synthetic is actually maybe holding steady now, but I think it’s gonna increase in value more and more and more and more, honestly. Right, right. Of course I don’t know if we commoditize some of the skills, right? So, you know, the team, how they’re actually pulling reports, pulling data, how they’re integrating workflows, whether it’s with Webflow or HubSpot or other tools.

Stephen Banbury: Basic design, as, as we say here. Yeah, these are things that are, like, perfect use cases.

Stephen Banbury: For AI to be doing, yeah.

Courtney Kehl: Right, yeah, absolutely. I mean, I think there’s a lot of takeaways there. The human element is becoming more and more important, and of course, AI cannot do… they can’t bring judgment to the table.

Courtney Kehl: They can give an out… you know, you’ll get the data around it, but you’re not going to actually get the human judgment, you’re not going to get that empathy, you’re not going to get the one-to-one relationship, or to your point.

Courtney Kehl: AI doesn’t… can’t taste the food, you know, so…

Stephen Banbury: Yeah.

Courtney Kehl: Yes, yeah.

Stephen Banbury: I haven’t thought about that. And as any great chef will tell you.

Courtney Kehl: Oof.

Stephen Banbury: And I’ve seen Gordon Ramsay say this a lot. Did you taste the food before you put it out for service?

Stephen Banbury: Absolutely have to do that, yep, yep.
Courtney Kehl: I’m a huge fan of Gordon Ramsley. Well then, so where does it actually fit in, and how can it be implemented in the best way? Where does it not fit in? I think this one’s pretty straightforward, but it’s great to see it kind of laid out, so maybe you can walk us through this.

Stephen Banbury: Yeah, it goes a little bit to, sort of, the example I gave around, kind of like, a piece of content, for example, and the design of that, and the ideation around that you kind of you’re augmenting the human with their AI, but you need to be very thoughtful about which pieces you need to look at your own company and the work that you do, and be thinking about, well, what can I automate? What should I automate? How can I be more efficient? How can I create some scale?

Stephen Banbury: What I need to… do with a human is such a…

Courtney Kehl: Two minutes.

Stephen Banbury: is, you know, keeping the human in the loop, right? We’ve talked about that. So augmenting with it, and then what are the things that you really need to keep?

Stephen Banbury: Just, like, really 100% focused on the human, so… but I think when you look at the work that you’re doing, you can create those use cases and then go practice on those.

Courtney Kehl: Yeah, yeah. For us, we kind of look at the human piece as the bookends, and then see where the… that… obviously, we need the… those eyeballs and the checks and balances to interweave throughout, but without a doubt, you need a human at the start, and you need a human at the end. And that allows for that accountability as well.

Stephen Banbury: Yeah, there was, I think in the same report by McKinsey, I think they said that, like, one in four leaders, expect that AI agents would act as autonomous teammates to the employees in the short term.

Stephen Banbury: So, you know, it’s… the humor’s always going to be important in the equation, for most of the time.

Courtney Kehl: Yeah, yeah. I think the biggest takeaway with AI tools, and as we integrate them into our day-to-day workflows and the processes, it certainly is the execution piece, right? So the execution piece is expedited.

Courtney Kehl: But the judgment, taste, orchestration, that’s… that’s the area, that AI will… will never really have a handle on, and that’s where I feel confident that… that the world will actually grow and become, you know, a more interesting place, as opposed to AI taking over, in… in those you know, a year ago, two years ago, what does this mean for us?

Courtney Kehl: Yeah.

Courtney Kehl: So, how do we actually start this? How do we actually make some of these takeaways tangible and implement?

Stephen Banbury: I mean, the first thing is you’ve got to start using it, right? There’s no better thing than starting to use it yourself and understand it. You know, if there’s someone on your team, you know, work willingly, right? If there’s someone that’s passionate about it, how do you, like, involve them in it?

Stephen Banbury: You know, look at the current roles that you have, we talked about this, not the titles, but the outcomes, right, and the activities, and the outputs as a leader in your team, you probably know what’s going well, what isn’t going well, what’s slow, what’s fast, and is there an opportunity to use AI to speed up something?

Stephen Banbury: And that goes to, actually, the third point, which is redesign a workflow around it this quarter. And don’t feel like you have to boil the ocean, right? This is something like, you know, even if you’re picking one workflow, like, start somewhere and think about that to make it easy. The one thing I would say is just to the point of AI governance.

Stephen Banbury: Which I think people should be aware of, is you need AI governance to ensure ethical, transparent, and a compliant use of data.

Stephen Banbury: So, you know, this is important, especially, you know, I was running, looking for some insights around a big data set.

Stephen Banbury: You’ve got to make sure, at least for me, I’m taking out the email addresses, I’m talking about the person-identifiable information, the PII, right? So, you know, it’s important to make sure that you’re doing this within the constraints of the company. If you don’t know what the governance is.

Stephen Banbury: Talk to your… talk to your legal department. But, you know, just make sure you’re doing the right thing, obviously there, so I just want to mention AI governance as well. And then, obviously things are moving so fast. It’s actually… It feels overwhelming because every day, there is a new piece of information or a new functionality that’s available. So definitely, like, think about a cadence where you’re reassessing the tools that you’re using, and thinking about the skills as well. So, I think those are all really important.

Courtney Kehl: Yeah, yeah, I think those are great takeaways. I mean, the hygiene piece… that’s… I always think about hygiene, because every… We recommend at least once a quarter you, you know, make sure you do your housekeeping.

Courtney Kehl: And certainly, I would apply that sort of in the same cadence around these AI tools, and as folks are getting more comfortable. It’s certainly widely adopted now, so I think we’re in that next step, sort of this exciting AI era.

Courtney Kehl: But intentionally rebuilding workflows, knowing that AI is going to be utilized, and kind of calling that out and creating that process, I think, is a really great way for a leader to start, you know, putting some of this into action and seeing what’s working and what’s not, and how it can be best utilized within your team.

Courtney Kehl: Awesome. So recap, the approach, you know, is the most important. It’s not about the tool, it’s… I mean, as we all know, GPT and cloud, they all have their various strengths, and I think they’ll probably be chasing each other for… for a good while here. But it’s the approach that’s… that’s attention… that’s becoming the bottleneck. You know, where are we just throwing AI in, and that’s hence the AI slope? Or can we actually look at those as accelerators to… to the work output?

Courtney Kehl: Structure around outcomes. We pivoted in the last year or two. We were not time tracking in the same way. We’re really looking at, okay, what are we bringing to the table, and what does this mean, and what are our goals here, and how do we hit those?
Courtney Kehl: The judgment piece, the taste, the judgment, the editorial, is very important. I think folks are really looking at the content that they’re getting from the point of view of, did AI create this? And it really takes that personalization out.

Courtney Kehl: So much so that we’re actually all telling our tools to remove the M dashes and make it look less AI. It’s almost, you know, like that pendulum swinging back automate, augmenting, and keeping human peace. So, I love the easy button. Being an American, I want the easy button. So if I can automate my whole life, I would. But at the end of this, I think the big takeaway is really that the human piece is coming back stronger than ever, as it should.

Courtney Kehl: We are human beings. Let’s keep it that way.

Courtney Kehl: And then again, just start with one or two, or even three that you feel comfortable with saying, okay, let’s… let’s look at the creative here. How do… where do we want this tool to put in? Maybe on your social network, like, just get those initial drafts, those types of pieces, and intentionally map that out, I think will really give folks that sort of extra confidence in how they use… utilize AI.

Courtney Kehl: That’s it. Hit the end! Well, time check. Well, it’s almost like we know what we’re doing. Any final thoughts as we’re wrapping up here?

Stephen Banbury: No, I think, we covered a lot of ground. I think the main thing is, start, identify some areas, and always check the work. Always check the work, I would say. Quality control is paramount. You know, more output doesn’t necessarily mean better output, and certainly doesn’t necessarily mean better results, and so you really need to always keep a keep tight to the outcomes that you’re driving. You know, am I driving a pipeline, for example? How am I showing up in AEO, GEO, and SEO? Like, you know, all of those pieces. So, you know, I would definitely think about what your strategy is around AEO and GEO. If you’re a marketer, I would… I would definitely be thinking about that.

Courtney Kehl: Yeah, yeah. There’s a funny tagline, or I don’t know if it’s a tagline more so a campaign, but, I saw this open in the more recent Black Hat security show, and it said, my CEO spent the whole weekend vibe coding. Now what?

Courtney Kehl: I have been on the receiving end of that, and the now what is… now we gotta go through all of this and actually look at, like, what is… what is, you know, the right level of quality, and is this just slop?

Courtney Kehl: So anyways, yeah. Well, thanks everyone for joining. We do have a lot of folks that are interested in the recording as well as the presentation here, so we’ll be sure to get that out.

Courtney Kehl: And reach out. We’ve got, you know, all sorts of ways to lean in and hopefully make this easier for everyone.

Stephen Banbury: on LinkedIn, I think the email addresses are there. So, look forward to hearing from people and discussing them, continuing the discussion.

Courtney Kehl: Yeah, absolutely. Great! Thanks, everybody. Have a good day.