AI slashes at all marketing skills and levels

This week, our guest Nathan Roach introduces a framework to identify the gaps and understand AI's role across all marketing skills and levels. Developing from the T-shaped marketer framework, this discussion touches on the importance of focusing on tasks, the risks of becoming caterpillars, and how the skills we already have are still our most valuable assets. Which is a relief for most of us. 

Tune in for:

1. An explanation of how we can level up the T-shaped marketing framework.

2. Why we need to think about the relationship between tasks and skills, and also continue to protect and build on the fundamentals.

3. The dangers of "unearned knowledge" and why we should be cautious not to lose specialist expertise. 

As ever, we get practical, personal and interested in how we move forward with AI by our side.

Co-hosts Olly Veysey & Lisa Talia Moretti are joined by Marketing Director, Nathan Roach and Director of AI Strategy, Prateek Jain.

Links:

Leveling up the T-shaped Marketing Framework, Nathan S. Roach.

AI, Talent & Trust: A Landmark Report on the Future of Marketing Leadership, ADMA

Beyond Skills: Reengineering work, Reejig CEO Siobhan Savage

The hunt is on the Renaissance Man of computing, King's College Professor Emeritus, David Guest

Transcript

Olly Veysey (00:08)
Hello, welcome to IS THIS AI? Where we aim to bring you myth-busting insights, practical ideas, and a little more clarity for the AI road ahead. I'm Olly Veysey co-chair of BIMA's AI Council. If you are wondering who is this BIMA and who are these AI councillors, BIMA is the voice of creativity and tech in the UK, driving innovation and representing the interests of a community of agencies, charities, businesses, and academia. And we on the council are here to help all of those people and you prepare for what AI is bringing.

So we can make the most of this wonderful, mildly panic-inducing technology that is upon us. I'm going to ask my co-host Lisa Talia and Moretti and co-chair of the AI Council to speak to that a little bit more. Lisa Talia, I already know where you are dialing in from and I'm already jealous. Hello, how are you?

Lisa Talia Moretti (01:05)
⁓ Hi, hi Olly really good thanks. Hi everyone, dialing in this time from South Africa, which is, it's slightly embarrassing, this we're in the world is Lisa, but like the Where is Wally?

Olly Veysey (01:14)
It's a little bit.

Lisa Talia Moretti (01:17)
The AI Council really works to demystify and clarify AI for the BIMA membership and the creative tech industries.

We work on initiatives like workshops, we've created the BIMA AI standards, and we also aim to share practical and helpful conversations, just like the ones we have here on the podcast. We also help to forge links between subject matter experts and policymakers, as well as our members, so everyone can get help to access trusted sources of information.

And lastly, we're exploring the current state of AI to find, like Olly said, those people and organisations who are getting it right and spotlighting some of those best practice and also next practice, I guess.

Olly Veysey (01:58)
Thank you. And one of those people, and I'm excited to say also a member of the AI Council, he's been on the show already, Prateek Jain, Director of AI Strategy at Axelerant. Very happy to have you back. Nice to see you again.

Prateek Jain (02:11)
Hello Olly,

Excited to be here and then talk about how AI cuts into marketing. But then let's see what we have to cover today.

Olly Veysey (02:21)
Yep, very excited to have you back, not least because you always have interesting things to say, Prateek and because you bring with you a most excellent guest. Nathan Roach is Marketing Director at Axelerant responsible for leading integrated communications, marketing strategy, and new public relations. I'm interested to hear what these new public relations are and how you understand that, Nathan. Nice to see you. Thanks for joining us.

Nathan Roach - Axelerant (02:46)
Thank you, thank you, Olly. And yeah, start that rumour. So I look forward to talking not about best practice, but maybe talking about better than nothing practice. So we'll get into that. So thanks so much for having me on.

Olly Veysey (02:58)
It's fantastic to have you with us. This is episode five. We have this and then only three more in this first series of the podcast and we are not slowing down. Today our provocation is: AI is cutting across all skills at all levels. And we're thinking particularly about the context for marketers here. So Nathan.

I'm really excited to talk to you about this because I think it's going to be super useful for people. And also because it feels like to me, we are marking a bit of a shift in perceptions and how we're working with AI and really getting into how to make good use of it. So, what do you mean AI is cutting across all skills at all levels?

Nathan Roach - Axelerant (03:41)
Yes, well, I think it's quite evident in some of the panic-inducing commentary that you made at the top of the show that there is this sense that ⁓ AI has sliced across so many things. I do think that just recently, having seen some of the keynote from the OpenAI event just recently, the agent kit announcement with ChatGPT, we can see that the use and integration of applications and programs in

It is so immense and this does touch every aspect of the professional life. And I think it's going to touch more in a deeper way as time goes by. So from the standpoint of it slashing across everything, I think that's something that we all feel. We feel that all of our work in some way has been disrupted in the way we do it, particularly in what we use to accomplish our work in terms of our tool stack and the expectations of our roles thereof with this new application.

This slash of AI across everything. I think it's evident and I think it's something that we all feel within us.

Olly Veysey (04:46)
Prateek, in your role as a director of AI strategy, how are you thinking about this yourself personally, the impact on your practice and also in your business?

Prateek Jain (04:58)
I think it's a great provocation first of all, right? I mean, cutting across all skills, right? I think, and I'm being an engineer, right? It's natural for me to lean towards the technology, And the way I see it is that like what Internet was, let's say in early nineties, right? Where every, some of these industries said, hey, what can Internet do in healthcare? What can Internet do in real estate? But then it cuts across all of those industries, right? All of those professions, directly or indirectly.

Sure, like in the real estate business, for example, right? And in the construction business, you have to construct the buildings, but how you come up with the floor plans, how you share those, Internet has cut across all of those streams. So that's how I see it. It's similar to AI today. ⁓ While some of those things are not clear, some of the things are probably not at the stage where it should be. It's still an evolving technology. It's changing every day. It's probably at a much faster pace than any other technology has evolved in the past.

So therefore, I'm inclined to say that it will cut across all the streams if it is not doing that already. But there are clear signs it will.

Olly Veysey (05:59)
LT, why don't you come in here? Because I know that you've been involved in a significant piece of research around this as well. What are your views on this?

Lisa Talia Moretti (06:08)
Yeah, so thanks Olly. One of the things that came out of some of the research that I was doing for ADMA, an organisation based in Australia, looking at how AI is impacting marketing professionals. And one of the things that we found is the research showed us that more and more marketing professionals have to continue to keep a baseline of fundamental skills, but also need to start adding these kinds of skill sets that they were potentially originally kind of outsourcing to different teams within their organisation. Thinking things like marc-tech skills, right? How these different tools, marketing technology tools work, having an interest in how they work, implementing them within their workflows. But then one of the things that comes kind of really close to this is that these tools produce a lot of data. So certainly marketers are having to become way more data analytic, literate in learning and understanding what these different data points mean.

How that relates to the customer that they're trying to appeal to or the campaign that they've just developed, and then how you kind of stitch all of these disparate pieces of information and data points together to tell a compelling story about what just happened. So there is something there about the additional skill sets relating to technology, understanding how the tech works, having a bit of an understanding on not just how you prompt the machine, but how the kind of fundamentals of the technology work so that you can better understand those internal mechanisations so that you can change your approach to working with that technology, right? So search works in a very different way to LLMs - having an understanding of how those two things work differently changes the way that you interact with that tool. Those kind of technological and data analytical skill sets are going to be increasingly important, alongside marketing fundamentals and continuing to build those marketing fundamentals.

Olly Veysey (07:54)
Nathan, take us back a little bit, if I can ask you to do that. In your article that you published today - Leveling Up the T-Shaped Marketing Framework - we will put the link in the show notes. It's published on the BIMA website.

Give us some background, please. Just a quick overview of what is the T-Shaped Marketer? What sparked your thinking around this? Why did you want to bring this today?

Nathan Roach - Axelerant (08:17)
Sure, I think Lisa set me up really nicely there. There was already this feeling that marketers, in terms of their skill set, that there's this rise of the generalist.

The idea that marketers have to be able to do multiple things, not just search, but also a different kind of discovery in different algorithms, and that also pertains to social, et cetera, et cetera. There's this great broadening, say, of the expectations of marketers generally. And now we have this great disruption, this disruptive technology. And I think it can be rather confusing to understand what does one do as a marketer?

Do we, what sort of framework can we use to understand this intersection? And what does that mean for me, for my role?

For my department? For our services? And I think it's like boiling the ocean, isn't it? Trying to figure out all of this at once and it's moving so quickly. So I think if I could also go back to what Prateek Jain said about the early 90s and the Internet and its disruption. Around that time actually in the UK, David Guest, who today is a professor emeritus at King's College, he wrote this article, it was in 1991, about the search for the Renaissance Man of computing, this multi-disciplinary figure in engineering. So all the way back then there was this stress of course on broadening skills. And that sort of, let's say, call to the generalists developed over time eventually came to the United States. Tim Brown, the former CEO of a design firm in California, he spoke about T-shaped people. And the T-shape now is what I'd like to speak a little bit more about, which is this horizontal bar.

Let's call it the breadth of skill set, you know, and then there's this vertical bar of the depth of that skill set. And we can see this in marketing, we can see it in other disciplines as well, but particularly this this t-shaped ⁓ individual, it caught on in marketing as a means to be able to showcase somebody's depth and breadth of skills where they're currently at, and it helps them to level up, so to speak, and to go further down in the vertical line and broader across the horizontal line. And I suppose my premise is that AI has slashed across the T-shaped framework. There are touch points of AI intersection at every level of the vertical bar. And we've come a long way, generally, when it comes to demand for skill set depth and breadth since the 90s. But now here in 2025, with this intersection of AI, what does this mean? What does it look like? And I think the T-shaped framework could be a way for us to have that conversation, for us to give feedback to our colleagues, for us to also see where we are with respects to AI integration across these skill sets.

It's a simple concept and it's one that's been around for a long time. But I think it's helpful insofar as it helps to kind of give a picture versus all of the fog and smoke around AI integration and how one goes about this. I think that it's pragmatic. At least it's a little bit more pragmatic than the alternative, which is adopt AI. In what?

Everything. When. Like yesterday. Does that make sense, Olly?

Olly Veysey (11:40)
It does, it does, and I think it is, I found it, I only read it for the first time last night, but...found it incredibly useful. We've had these conversations numerous times and as you know, as a writer, we are, Prateek will tell you that I'm protective of my writing sisters and brothers and our value to the marketing process and particularly the ones with deep experience, knowledge and craft. And so,

Prateek Jain (11:52)
Absolutely.

Olly Veysey (12:08)
When you say something to me like, well, AI just cuts across every skill at every level. My first thought is, no it doesn't. Not at the level that I'm working at. And I don't mean that to sound immodest.

But what I loved about your piece is it's like, what this is really about is how can I pinpoint where I'm at with AI adoption per skill? And how do I isolate those gaps? And so you start to look at the different levels you talk about, L1 to five.

And where it cuts across my skills is different to someone who has a different set of skills. And you can start to really make it useful, personal and focused on, you know, where I need to level up versus someone else who might have a different set of skills.

Nathan Roach - Axelerant (12:47)
I understand how there is a level of subjectivity when we talk about skill levels, of course, right? But at least it's more tangible in the sense we can talk about specific skills, we can talk about a specific intersection, and then we can share that between us as colleagues. And I just must say, I think it's very important for us in almost a humanitarian sense to help others.

And to help ourselves to isolate where these gaps are because I think this sense that we have of

AI in everything as of yesterday. What does one do with that anxiety? And while there is subjectivity in skill levels, and this is rapidly changing, it at least gives us a conversation piece to bring to the table so that we can have meaningful feedback and to exchange with our colleagues and to share other ⁓ tools, tactics. And I think, Olly, if I could speak a little bit about your advance level as a professional writer, I'm sure that your experience with AI thus far has not been at what we would call like an L1 level.

You're trying to see how this technology intersects with your L5 level, your more advanced level. And what does this mean, right? How does one use it? Is it just prompt-based inquiry? I doubt that at this point. I'm sure you've moved beyond prompt. And I think that's exactly the point of the depth of this vertical, which is where is this? Where am I? And perhaps we may find that we're an L5 content creator from the standpoint of copywriting, but we find that we're an L2, touch point for AI integration.

And that gap between the L2 and the L5, the question becomes, well, how do I bridge that and how are other people bridging that? How do I have a meaningful conversation with colleagues about that? And how do I discover, right, how other people are bridging this gap? And I think that gives a sense of peace. Why? Because we've taken the intangible and we've made it just a little bit more tangible and practical.

Olly Veysey (14:56)
100%. And I think that finding those gaps and how to move up the levels in the areas that you need to is why it becomes so useful. Prateek, how are you, you've talked about AI fluency and as a start point, and we talked about AI fluency on the last week's episode, actually. And this is a really nice place to start. How are you?

Prateek Jain (15:08)
Ha!

Olly Veysey (15:22)
How are you thinking about this or implementing it in your own work?

Prateek Jain (15:26)
Yeah, so before I say that, I will offend engineers and all technologists if I say we are not as creative as marketing folks are. It's kind of a very similar feeling when it comes on the engineering side as well. Like a lot of developers and technologies I spoke with, right? And they were like, hey, I have to protect my code. I don't feel good about somebody writing code for me. And it's exactly what you said, Olly, right? When an expert level writer is a creative writer.

Nathan Roach - Axelerant (15:33)
Good.

Olly Veysey (15:38)
I'm glad you said that.

Prateek Jain (15:55)
Somebody is a creative designer, right? I mean, it feels the same. And the feeling is true. But what I learned over the period of time, and then I worked closely with Nathan, I'm not a marketeer, but then working closely with marketeers like Nathan and other awesome marketeers like Axelerant the way you use it kind of makes a lot of difference, right? So I like to see it as like AI not being replacing anyone, neither a skill, but rather amplifying it. So can AI amplify your writing skills? So if we are doing an analysis, right? AI can do a lot of research on the data, get you the insights and how you act upon it is still human. So your creativity, your expertise is still applicable, but then AI can act on your behalf. It can give you the drafts for sure. Can probably hundreds of drafts, but then choosing the right draft, giving it a direction and identifying the strategic value, right? I mean, out of it and the direction that you need. the storytelling, right? So one other example that I have is I work a lot with the solutioning team who helps out with the pre-sales and we write lot of RFPs or rather proposals to the RFPs, I just want to go there. Trust me, engineers don't like to write. And they're like, hey, I can write bullet points. These are the four steps. I don't know how to turn it into a paragraph. And using AI, we were able to amplify that. We were able to bridge that gap. So that's how I see it. I mean, it's not replacing engineer. It's not like a non-engineer is writing that proposal. It's just that the way to represent has evolved.

And what they can do on their own has amplified over the period of time. And this is to like cutting across, knowing the proposals, writing, designing, quality assurance, and to various other streams. So when Nathan brought up this idea of the T-shaped marketeer, I commented to Nathan, why only marketeer? Why can't we do it as a T-shaped organisation? Like which department within the organisation is adopting AI better and where, right? Hey, we are doing it better in the quality assurance. We are doing better in the HR department or...or people care department, right? I mean, and that's where it kind of evolved. And I thought it would be a good discussion topic to even bring it over here.

Olly Veysey (17:52)
Yeah, absolutely. It's relevant across, as we said, at the top, all skills. Lisa Talia, what's going on in that mind of yours?

Lisa Talia Moretti (18:03)
There's been so much good stuff said. I wanted to come back to a point that Nathan made about identifying the gaps. And I think there's something else that we need to talk about when we think talk about skills, and that's about the tasks that we are applying the skills to. And I'm going to reiterate or repeat something that Siobhan Savage, CEO of Reejig, said, and she always says that...that we automate tasks, not skills. And so when we talk about skills and the way that AI is kind of influencing that, it's really important for us to not want to throw the baby out of the bath water. So really acknowledging that all of the skills that...

All professionals have collected up to date are still valid and still important, but may need to be redirected into a different way. And, you know, one of the examples I kind of wanted to give was thinking a little bit about like, like prompt engineering, right? Or when you're like putting in these prompts in generative AI tools, it's akin to a brief, right? Which clearly communicates to a machine a communication direction. And it provides that with the necessary context and the creative guidelines and the constraints. And so just by doing that, that requires skills that stretch across the breadth of marketing fundamentals, like analytical and strategic thinking. You have to have like some creative nowse, right? Of course, along with that. And you have to have some kind of like technical and data expertise to know that this is the kind of tool that you need to be using to answer the job and then understanding what it's going to give back.

So when we're thinking about these things, I think it's so important like that. That points around like cutting across, right? Cutting across all skills and identifying what your learning level is, but not feeling that you have to throw everything out and start over. It's always about like building and progress, right? I think that's a really important kind of message just for everyone to take a collective breath and say everything you've learned up until now is not useless. It is so important if anything, it's going to really be the fundamentals, the...the springboard from which you leap into your future.

Nathan Roach - Axelerant (20:06)
I completely agree, Lisa. One of the things that you said that really stuck out to me during the last episode was about the focus on the problem being solved.

You put an emphasis on AI helping people to solve problems. Did I get that right? That was one of the sort of the overture of your point. And I think this task-oriented problem solving, how do I bridge this gap? I think as we use these tools and as we integrate them more, we're going to get better and better at using them. And I think our strategic approach to using them, how we approach a task and where we bring, let's say, an AI level or integration

Lisa Talia Moretti (20:22)
Yeah, that was spot on.

Nathan Roach - Axelerant (20:44)
into that. I think that's precisely where the touch point has to live. And I think your bifurcation between task-based use and skills, think that's spot on. They certainly overlap, but they are different things, aren't they? It's whether or not, let's say, AI integrated in this particular skill set. If it's something that I can advance on, do it better next time. And that's something that we learn. These are skills that we apply. But it's focused on solving a problem.

So I do think those two things, they overlap, but they are different.

Olly Veysey (21:15)
What I like so much about what you're proposing in this conversation is we're starting to move past the human versus the robot war towards you know how do we solve problems with using our human skills and finding the gaps to help us approach those tasks and those problems in ways that we can now level up, as you say.

So that's one thing that I really love. I have a concern. And then Nathan, I'll come to you for sort of some final words and maybe how you've seen this in action or whatever you want to share. But my sort of note of caution is really around, I suppose the loss of that depth, the vertical.

on the T and whether we risk becoming sort of caterpillar shaped instead with like, you know, a lot of breadth and then just not a whole lot of depth. And that's just a watch out for me as we adopt these tools, I think, and for marketers and certainly for writers that we don't have this mirage of knowledge without really understanding or real depth of skill. How do you respond to that?

Nathan Roach - Axelerant (22:23)
I think there are incredible dangers of unearned Unearned knowledge. A response to a prompt say that we put in a custom GPT, it is our responsibility to own that knowledge and to understand and to treat it say as a peer and not as a proxy for our own experience and intellect. So I completely agree and I think there is a risk of being a jack-of-all-trades and a master of none and then having AI serve as a proxy in the depth of those verticals. So I would double down on your your note of caution. think and as a great writer of your country, Olly GK Chesterton once said, we have to keep an open mind but not so open that our brains fall out.

And I think with AI integration and adoption, that is absolutely appropriate. So I would agree with that. I think there is a risk, of course, in not using some type of framework to identify the intersection of this incredible technology. We have a responsibility to do that as well.

Olly Veysey (23:31)
Yes, Prateek, do you want to share some final thoughts and then Lisa, Talia, and then I'll come back to you, Nathan, just to ask where we can access this framework and learn more about it. But first to you, Prateek.

Prateek Jain (23:44)
Yeah, I completely agree with what Nathan said over here, right? And then what you, the analogy used by you early on the caterpillar side, it's important to have the depth as well. But then at the same time, the problems are also kind of getting redefined. It's not the same problem. The tasks may have changed at all. So we can't just look at the task in the same way as it was before with the technology evolving. Those tasks also evolve. So, but yeah, keeping it an open mind in both ways, right? It's really important.

And the way I see this TXs at an organisation, let's say like us or others, right? I mean, they can help visualize where there is actual AI fluency versus where it is still at the experimentation stage. And just knowing that is incredible. Just knowing that can enable us to do so many things, being more pragmatic about what to do with it and not getting into it. Hey, use AI everywhere or not use it at all. Right? I mean, so having that practical insight, it's really helpful. And that's what this framework brings.

Nathan Roach - Axelerant (24:39)
I invite people to connect with me if they found any of this interesting or they'd like the template. We've created a basic Google Sheets template with conditional formatting, that actually helps to generate a prototype of the T-shaped framework with the ⁓ AI touch points, these intersections in the vertical. So we will see. And as I ended my article, not all decent ideas can scale. Is it a decent idea? Perhaps. Is it scalable? That's to be seen.

Olly Veysey (25:07)
I will definitely be tuning in for the results and calling upon the framework myself. LT, are you going to audit where you're at with the framework?

Lisa Talia Moretti (25:17)
Yeah, so I think what we could do is one of the things I'd like to share to everyone is think about the tasks that you currently have at hand and also the tasks that you would like to be doing in the future and think about doing your own skills assessment. So what skills do you need now? What could you be doing differently and what skills might you need in the future? And have a look at the framework for sure and then start to draw a line across those skills, either the ones you have now or the ones that you desire in the future.

And start thinking about those learning levels, where you're at and where those gaps might exist for you. But I would recommend, my recommendation would be to start with your tasks. And I think you might find that that's even more helpful.

Olly Veysey (25:59)
Brilliant. Thank you. Well, I feel heartened. There's, ⁓ places to start and you don't get anywhere if you don't start. I wish I had a something smarter than that, but, as we try to get through the fog and put one foot in front of the other, I really appreciate you bringing that today, Nathan and Prateek.

Nathan Roach - Axelerant (26:04)
You

Olly Veysey (26:16)
And as always, Lisa Talia thank you for your insights.

Lisa Talia Moretti (26:20)
Thanks so much Olly. Thanks Nathan. Thanks Prateek. Great to have you here.

Prateek Jain (26:20)
Thank you.

Nathan Roach - Axelerant (26:23)
Thanks so much for having me.