Alter Everything Podcast
Episode 205 - Get It to 80%: What AI Actually Changes for Marketing Teams
Episode Chapters
0:00 AI meets real marketing teams
1:35 What inbound marketing means
4:08 Where AI in marketing stands today
7:11 Adoption challenges: tools, workflows, and mindset
12:00 The 80/20 shift for AI work
15:50 Copywriting, brand voice, and human editing
22:37 AI, design, and human creativity
27:48 Marketing tech stacks and AI literacy
34:04 Governance, security, and shadow AI
40:32 What AI-first marketing teams may look like
45:32 Lightning round: tools, skills, and mistakes
51:18 Closing reflections
Joshua Burkhow (00:03)
Welcome to Alter Everything, a podcast about AI analytics and the future of work. I'm your host, Joshua Burkhow. Marketing has always been about staying ahead of what's next. And right now that next it's AI. But the reality inside most teams isn't transformation. It's actually a lot of confusion. There's too many tools, too many experiments, not enough clarity on what actually works.
And the question isn't whether AI will change marketing. You should be clear that it will. It's where does it exactly and actually help? Where does it break? And today's conversation is about what happens when AI meets real marketing teams. You know, there's no shortage of content about AI and marketing, but most of it focuses only on what's possible, not what actually happens when teams try to implement it.
My guest today, Martin Broadhurst, founder of Broadhurst Digital, works directly with companies trying to figure out this exact problem in real time. So today we're going to focus on a few things. One, what actually happens when marketing teams adopt AI? How marketing work is changing at a practical level? And lastly, what still requires a human? Even
in this AI-first world. Let's jump into it.
Joshua Burkhow (01:35)
Martin, welcome. You've been working in inbound marketing since 2012, it sounds like, and now you're helping companies integrate AI into their marketing workflows and tech stacks. And am going to love this episode. I already know because first of all, I need to know everything there is about marketing. So hook a brother up. but also marketing is one of those areas in AI that sort of
led the pack and jumped out in front from social media and content development and all these other things. And I think it'd be, it's going to be a great conversation. Welcome. love for you to briefly sort of explain what you think inbound marketing is from your words for our non-marketing folks
I'll give you an easy one to start and then we'll get into the hard stuff. Sound good?
Martin Broadhurst (02:25)
Sounds good. Yeah. Cheers I appreciate the soft inbound marketing question. Well, inbound marketing for the non-marketing listeners. It was a phrase coined the founders of HubSpot, Dharmesh Shah and Brian Halligan in the late noughties and kind of became very prominent through the 2010s.
And it was really about using content marketing. was originally how you used SEO and social media to build audience, attract people to your own media channels, generate comments, replies, all of that kind of engagement. How do you then convert them into leads and how do you close them into customers and turn them into evangelists? it was the playbook for,
the 2010s for most tech companies. And it's still a playbook that many are trying today, but it's interesting that this year we're seeing shift, a shift from HubSpot in particular, who coined the phrase, as their inbound conference is now becoming unbound. And that is largely driven to the changes that we're seeing in the way and buyers are consuming marketing content.
Joshua Burkhow (03:15)
Yeah.
Thank you. Before we get into the weeds, I like to sort of start high level because a lot of times conversations get started in the weeds and there's no context. And I think if you could sort of give your take on marketing and AI and more specifically, wasn't born yesterday, but it hasn't been around forever. And it's sort of this,
fast growing thing. Where does it stand today? And then what are some of the challenges when companies try to introduce AI into their marketing teams?
Martin Broadhurst (04:08)
Yeah, I think that's an interesting question when we think about what we are considering in that bucket of AI. Marketing, you're right, has been kind of at the forefront of using AI for a long time. We've used it for, the P's of marketing, the four P's of marketing, product price, promotion, place. These have been used for things like dynamic pricing, which has been algorithmic for a long time. We've had
recommendation engines that have been AI-driven. Now they're not generative AI forms, but they've been marketing applications of artificial intelligence that have been around a very long time. Where it stands today through generative AI is obviously a very different landscape. I think the launch of the GPTs and large language models has obviously changed that. It's interesting you've mentioned in the intro.
that marketers have been using AI, they were early on the bandwagon there, and I think they really were. Marketers are always looking to get that next competitive edge, I think the language models, the early language models really lent themselves to marketing, because so much of what marketers do involves copy.
For example, we talk about inbound marketing a moment ago, that's lots of blogs for ranking in search, it's writing ad copy, it's writing ad headlines, it's writing email marketing, communications, it's writing press releases, etc, etc. And what we saw with generative AI was pre-GPT, so when large language models were really still kind of a niche technology, they were being used
Joshua Burkhow (05:37)
Yeah.
Martin Broadhurst (05:54)
by marketers with tools like Jasper and Copy.ai and lots of AI-powered copywriting SaaS platforms basically did that piece of the marketing journey. Now obviously that's changed a great deal. We now large language models like Claude Opus 4.7 that are doing agentic coding. We've got Codex from
ChatGPT, we've got models that are capable of more long-horizon reasoning tasks and research agents and agentic behaviors, all of these capabilities that have been unlocked far beyond just write me a clever subject line for my email, which is certainly where we were a few years ago. And I think now where marketers are,
is they're in an interesting space. I think there's a lot of marketers and marketing teams that are just kind of getting to grips with this technology to understand, to understand where it's at. And there are still some that are maybe using ChatGPT to write them some emails and they're at the, I would say they're kind of laggard territory.
Joshua Burkhow (06:54)
Still catching them. Yeah. Yeah.
Martin Broadhurst (07:01)
And then you've got people doing it with automated content campaign testing. think seeing people use AI-generated content for good or for ill on platforms like LinkedIn to mixed effect. And it's a very mixed landscape out there.
Joshua Burkhow (07:11)
Yeah.
I, it's interesting. There's sort of two things I took away so far it's fair to say that marketing teams are probably a lot like any other finance sales teams in that there are some that are really pushing the gamut and doing advanced applications, getting into agentic AI and marketing. But you sort of hinted at like there's marketers who are still learning how to spell GPT and
get started try to find applications outside of the where do you think the teams are struggling the most? Is it the tools? Is it just learning the different applications and
LLMs and all that. Is it building out essentially workflows. Is it a mindset challenge? Like where do you think the challenge lies for marketing specific?
Martin Broadhurst (08:09)
Tools, workflows, mindset, I think it's a little bit of all three to be perfectly honest. There's definitely AI literacy piece that I think the people that get get it, they throw themselves into it and they just get started and like, right, this is amazing. still working with lots of organizations where most people don't have a paid subscription to a
GPT or Claude, Codex, Copilot, whatever. They're operating on the free version of Microsoft Copilot, which is the kind of IT-approved safe version.
Joshua Burkhow (08:33)
Something.
Martin Broadhurst (08:42)
But actually if you've got a Copilot Pro license, and it's actually really quite powerful when you use the Frontier agent, when you use the Analyst agent, and you start stringing together some of the more interesting things you can do with it once it's embedded into your SharePoint directories and what have you. But that isn't the version that most people are getting. So there's a tooling version, I don't think the teams are being given
Joshua Burkhow (08:45)
That's right. Sure.
Right.
So.
Martin Broadhurst (09:05)
The right tools for the job. If they are, are they being supported with training? I, you know,
the IT team will send out a couple of newsletters maybe forward on the latest Microsoft Copilot eShot that they've received and expect teams to figure it out themselves.
Joshua Burkhow (09:17)
Yeah, just
Martin Broadhurst (09:20)
So that workflow piece comes into it as well. No one's helping them build the workflows. No one's telling them what the difference between agentic assistant or a custom agent like a Copilot agent, what that can do versus an automated Power Automate workflow with some AI prompt steps in the middle of it and how that could completely reshape.
Joshua Burkhow (09:32)
Yeah.
Sure.
Martin Broadhurst (09:43)
the way that a team works and certain tasks within a team.
Joshua Burkhow (09:43)
Yeah, absolutely.
So I have personally three different subscriptions. And then on top of that, I have two at work. so obviously, I spend a lot of time doing this, but there are people who to your point don't have a subscription yet. And so they're not hands-on.
How do you get them engaged? How do you get them up to speed? corporations are still figuring this out. Like, how do I, deploy this across the entire company and keep our governance, keep our security,
make sure that it's actually being utilized. know, we're not, money's not going to waste per se.
From your point of view, when you walk in to a and you're tasked with helping them, on to AI, make some progress, what looks easy from the outside? But once you talk to them, you're like, that isn't as easy as people think of it on the outside.
Do you have any thoughts on that?
Martin Broadhurst (10:42)
Yeah, I think AI adoption, where it falls down is often people overestimating what's involved in, they hear that AI is coming for jobs and it's this amazing thing and then it can do anything. And then you get in a room with people and they go, right, well, we've got a Copilot license or I'm using Copilot as an example, but it could be, could be any of the others. And I've got this deck that I need to put together every month for.
Joshua Burkhow (10:52)
Right.
Yeah.
Martin Broadhurst (11:07)
C-suite, whatever it is. And it takes me all weekend. And if I could get my weekend back, can I just throw it in with a couple of prompts and a couple of slides and be like, yeah, I'm done with then you work out that when you get into the weeds on it a little bit, actually that particular task that they've said, I've got these slides, it's a much deeper task. There's fetching data from messy situations. There's like gathering from...
Joshua Burkhow (11:29)
That's right.
Martin Broadhurst (11:34)
random Teams chats and telling this person to go on Google Analytics. And what sounds when they say, I just throw together a few slides is actually a much messier And that's where it's going to fall down. So one of the workshop I was doing just last week, It was interesting doing a real exercise with the team to show them the limits of where it can get them. Like it can get you so far.
a lot of the time, for a lot of the tasks, it will get you 75, 80% of the way there, but you as a human need to finesse it at the end, or might even need to do some manual copying and pasting from one system to another, heaven forbid, but a lot of the leg-
Joshua Burkhow (11:58)
That's right.
It's not like you're doing that,
not doing that today. Right. it's this perfect transition to the sort of landing questions I want to get to is really this, this idea that you've talked about before and using AI is to get to the sort of 80% and then focusing human effort on that final 20%. Can you sort of elaborate a little more on that? Just, I want people to really understand this because
i know specifically in my conversations, they sort of approach the table as an all or nothing or, that elevated expectation that, it's, it's so amazing. It's going to do everything. And I think folks like you and I sort of, after we're done cringing and being like, yeah, that's not exactly, but I love your thoughts on, on this is 80 20 split.
Martin Broadhurst (13:01)
Well,
that's certainly true and I think they will get you 80% of the way there and 20% of the polish or the finishing touches come from the human and that takes shape in different ways for different tasks but like the window of what those tasks contains gets wider all the time, right, if you were to speak to me...
Joshua Burkhow (13:17)
That's right. Yep.
Martin Broadhurst (13:18)
Two years ago about what an LLM could do, I would be like, yeah, it'll get you 80% of the way there on this set of tasks, and I might reel off 10 or 15 tasks in marketing that it could do really well. Well, now I'll say it'll get you 80% of the way there in this set of tasks, and that task set is now 30 to 40 tasks long, So the window of its capabilities is expanding, but there is still the in the loop and human oversight,
case in point, Microsoft Researcher Agent. It's a deep researcher tool, much like Claude Research, Gemini Research, what have you. You give it a topic and off it goes. think it's actually pretty
it tends to, from my experience, hallucinate less than some of the others. but in one of them that came back recently with with Copilot,
i'd asked it to research how AI was being used in libraries and public libraries, and I was trying to find some interesting use cases for some work I was doing. It came back with a...
And a case study that was really weak, from the outset, you could just read the description of it. And I thought that just doesn't sound right. the use case, it was almost like it had been written by GPT-3 from years ago, where you might say, give me an example of how AI can help with marketing. And it would say, it can help with improving customer experience and personalization. Like the most generic phrase.
Joshua Burkhow (14:40)
Jennifer, Jenner,
Martin Broadhurst (14:42)
And I researched it and what had happened was this, it had found a citation and a source online but it was basically just a spammy blog, it was a link building spam network someone's trying to sell you some backlinks with all those spammy emails that you get in your inbox, it was one of those
Joshua Burkhow (14:42)
Hmm
yeah.
Martin Broadhurst (15:00)
Blogs that it had cited, and if I hadn't been on my game and checked that and read the report, there is every possibility that I could have included a completely fabricated case study and handed it to a client or used it as part of a report or something like that.
Joshua Burkhow (15:00)
Enough.
Yeah.
Yeah.
Martin Broadhurst (15:20)
Now that's just one example, there's many others, I mean copywriting is a really interesting one, the amount of copywriting that people use AI for these days and they just take it, you can tell they've just copied and pasted it, posted even the most cursory checks and just stylistic changes or I mean how many brands style guide, in-house tone of voice guides have just basically gone out of the window?
Joshua Burkhow (15:31)
Yeah.
Martin Broadhurst (15:46)
Because marketers are just using ChatGPT voice
Joshua Burkhow (15:50)
Yeah, sort of a tougher question. If you're. talking to a marketing analyst right now and they're they're tasked with doing copywriting. Any of these, you know, website copies, a big one. And and they're tasked with using AI in that regard. Is it matter of?
If we're talking within the boundaries of this sort of 80-20 rule, how do you approach it? Do you do all the copy in, say, an LLM? You have Claude write it all out, and then you, as a human, come in and go through it and check it? Are you seeing the best results that way? There's some people I've talked to who they now call themselves purists, but they go out, create all the copy,
their own brain, their own words, their own hard work, and then they use AI to tweak it. Do you have a perspective on each?
Martin Broadhurst (16:44)
Think that these are preferences in style and workflow, to be completely honest, and different people have different takes on this. I think a lot of it depends on the volume as well. If you're writing a kind 20 page brochure site. sure, you want it maybe it's consultancy, you want it to come across as the voice of the consultants, you want it to feel like you're working with real people.
In that case you might handcraft and polish, edit, tweak with the LLM. If you're running a e-commerce store where you're listing hundreds of products and you've got to ensure consistent word counts and bullet points here, 50 word description here and etc etc, you kind of programmatically
Joshua Burkhow (17:05)
Yes.
Yeah.
Yeah, super challenging.
Martin Broadhurst (17:31)
Stick that in, stick a data sheet in and you could blast it through and it becomes a speed and volume So I think it's horses for courses, you have to look at what you're trying to achieve and I can see strengths and weaknesses for both use cases.
Joshua Burkhow (17:39)
Approach.
Yeah. Yeah. It's, super interesting because I, I think this is the sort of big message here that is evolving is there's a lot to learn, covered that. there's a lot for people to get up to speed on. There's a lot of different tools to play with. And then there's a lot of different ways to implement those same tools. Right. And so
as much as I know I'm sort of crazy and hell bent on learning every little corner of AI and all the tools, I do have empathy towards, folks that have been sort of taught one way, taught an angle, and now they're sort of thrust into this new world of just the complexity. so I'm sort of trying to get into the psychology of this.
Push to, let's just AI the hell out of everything, right? Like, you don't need me as a human to do this. I got too much on my plate. Let's just do it all. And I think the sort of on this point, you're really strong about saying, got, especially if you're in, you're in with clients and you're wanting to make sure that your brand is represented well. Like these are all things that still require a human.
They still require the oversight, if at all, just someone to check and make sure that things are being done the right way.
Martin Broadhurst (19:10)
Well, you see
examples of it with some of the big four consultancies landing in hot water with AI-generated reports for clients where they're having to issue refunds because the reports have got fake citations and rubbish in them. It's so basic. That's your product. Your product is your expertise and your consultancy. The idea that you go, well,
Joshua Burkhow (19:16)
Yeah, that's
yeah. Yeah.
Martin Broadhurst (19:37)
We'll just, I mean, how, talk about devaluing your product and your whole positioning. If you just go, well, we're just going to throw it in ChatGPT and it can do it. And we're not even going to check it.
Joshua Burkhow (19:40)
Yeah, it's exactly right.
Yeah, there's all kinds of horror stories that I think are coming out as fast as the success stories, right? Because people are learning, like it's not a all for nothing. Is there anything in this sort of topic that you think is still a pretty human aspect in the marketing realm?
Is there anything that you just sort of have a stake in the ground and be like, yeah, don't ever, put this out to, to an LLM.
Martin Broadhurst (20:12)
No, there's not. And the reason that there isn't, because I think it varies on circumstance. Different organizations are going to have different expectations and the market will respond in different ways for different things. I was speaking with a client the other day who identified there was something of a bottleneck in some of their, their design team. They were under-resourced for design.
But they were trying out things like Copilot Create, ChatGPT with GPT Image 2, and Nano Banana, and all of these things. They're fun and they're impressive and they can do cool stuff. But they always found that it wasn't quite on brand for things that they wanted. There was always maybe a background texture that wasn't...
Quite as it should be if they gave it to the graphic designer or that little bit of kerning on something was not quite right, whatever it may be. And we had a discussion around it and said well that's... where they left it was maybe, actually what we need to do is rethink how we approach design for different applications and say for a LinkedIn post and you know if it's a
Joshua Burkhow (21:05)
Yeah.
Yeah.
Martin Broadhurst (21:26)
Client testimonial where we are slapping some words on a background, sort of thing that you might churn out in Canva very quickly, use it for something like that, for a piece of content that maybe has a shelf life of 36 hours at most and reach of, sure it's important to get good reach, you don't want to devalue the content, but we're not going to pour our heart and soul into it, but our designers, when we go to our exhibitions, we want to make sure that we've got
the great motion graphics, and we want to make sure that our stand design is amazing. And we want to make sure that that printed collateral that lands on someone's desk, that feels premium. And then the two things can exist in the same world in the same team. On the flip side, there'll be other companies that say, you know what, I'm churning out loads of print collateral, and I'm going to make it in ChatGPT. And well, fact, I go to my local community center, there's
Joshua Burkhow (21:59)
That's right.
Yeah.
Martin Broadhurst (22:21)
Posters on the walls all the time telling me about a yoga class or something, and it's a different application, it's a different market, it's a different use case, right, it's great for that, but would I use it for a high-end premium B2B product? Maybe not.
Joshua Burkhow (22:37)
Especially if you're working in a huge company you know, where there's a pretty substantial marketing team, the idea that that company's brand is tied to the quality of their materials, the quality of their, colors, the quality of,
their design, their quality of that sort of implementation, how the brand shows up. Super important. like you don't want to outsource it. Now this is actually goes back to one of the key things I think marketers really got onto. And I remember this because I have some friends that are artists and artists sort of freaked out when AI came around because they're like.
You know, are we, we done? Is AI gonna, know, mid journey was having his heyday. this sort of conversation around, does, how does AI affect design?
The principles and the elements and the components of it all can be very much ideated via AI. You and I can go to Claude or Gemini or Copilot and get all kinds of crazy ideas. We want this color, we want this statement, we want this font, all of these elements. These two work together great, these two don't. This one conveys solidarity, this one conveys.
Boldness and new ideas, whatever. Yet the componentry, the architecture, the putting all these stuff together in a cohesive manner actually seems pretty human, right? It seems like AI could probably take a pretty good crack at that. I'm not naive to think that AI can make some inroads on that, but there's still something about...
The fact that the branding is influencing humans and that humans portraying that is still the way to go.
Martin Broadhurst (24:31)
Yeah, and I think, yes, yes,
Joshua Burkhow (24:36)
Right.
You are always allowed to disagree. I expect you to.
Martin Broadhurst (24:41)
I really value the craft. my a lot of my initial work in, marketing agencies was within a creative brand agency. they did work that AI is never going to be able to do. Right. And there is, there is a finesse to it. And there was, there was a quality to it that I do not expect.
AI to be matching. There was a price tag attached to that as well. And again, I think we will see that.
Okay so Claude Design just launched recently. Claude Design is what a month or two old now at this point, it's really I mean it's not very old at all as we record this
Joshua Burkhow (25:19)
Very good call
yep. It's pretty, it's pretty new.
Martin Broadhurst (25:28)
And that product from Anthropic isn't at the moment
it's kind of cool. I've had a play with it. gone, I do like this, but I remember when Claude Code launched and I went, this is kind of cool. It can do some interesting things, I'm not going to live in here. I'm not going to all of my time in the CLI interacting with Claude Code.
Joshua Burkhow (25:37)
Mm-hmm.
This is...
Yeah, yeah.
God
no. Yep, 100%.
Martin Broadhurst (25:54)
Now do you know what I do? spend all of my time
in Claude Code right, and the difference, and I think that is because of the model improvements right, so when Claude Code launched it was Opus 4 was it, and I think then Opus 4.5 came out and everyone went oh this is interesting, I think by the time we get to the 5 series of Opus I think Design make people go
Joshua Burkhow (25:59)
That's right.
That's right.
Sounds right.
Martin Broadhurst (26:19)
Maybe these
things that we thought were human domains after all, were not so human, because we've seen it in plenty of other domains so far.
Joshua Burkhow (26:26)
Right.
Totally agree. I think this is for, people that have been doing this, I think this is our default response to these things. Like maybe there is no definitive anymore, right? It's just a matter of time. It's just a matter of time until, you know, Claude or Copilot or Gemini or, or OpenAI gets to that frontier.
As a matter of fact, think OpenAI sponsored something where it sort of has a graph of all the spider chart of all the areas that it's sort of getting into and where it sort of ranks itself on a, I think a scale of zero to five or something like that, which was super interesting. Cause there was a lot of stuff where, you know, it's not going to get into plumbing very soon. It's not going to get into, you know, a lot of these mechanics, right? But you...
You bring in robotics and maybe it's just a matter of time. I think the interesting thing, and I wanna sort of switch gears here, but it's connected, is
in the technology space, is another area. think marketing has sort of been on the forefront of a lot of technology landscapes.
Do you feel like that's still the case? Are they still at the forefront? do you feel like they're starting to need to catch up a little bit?
Martin Broadhurst (27:48)
No, I do think I do think that as well. There is they've been always trying to find the competitive edge, right? So you look at things like search engine optimization gave rise to huge amounts of SEO tools to track your rankings, identify keyword gaps, tell you where your competitors are doing well and give you all those kind of insights. So you suddenly stick that into your tech stack. Then you've got
pPC advertising, so you need the tool to manage your pay-per-click, manage your budgets, to do dynamic bid pricing, to A-B test your copy, so you buy that tech stack because that's integrated into Google Ads, and then you've got your email marketing, you need to manage your database, and, and, and, and. So as channels have become more digital themselves, so have the tooling to go and service those.
Those channels, I think it kind of is a natural extension of that. the rise of digital marketing led to the rise of all of this digital tooling, which led to a lot of marketers being quite digital first. someone's got to manage the website and integrate it with the analytic system, the forms, the CRM, the so on and so forth.
Joshua Burkhow (28:51)
That's it.
Yeah. Although all
the do you, do you think this is the sort of landscape of skills that, that marketers need to be paying attention to? it simply like, Hey, learn everything you can about Claude and Copilot or, is there other skills? Because I've been in some conversations where they're saying, yeah, spend some time in AI, but
the ability to think strategically, for example, is actually more important. Do you have a play on that? how would you, if you got to, had to get me up and running as a hardcore marketing analysts digitally forward, of course, like where would I, where would I put my eggs?
Martin Broadhurst (29:38)
I think there's still the foundations of good marketing principles, the four P's are the, you know, the marketing mix, right? Product price, promotion, place, all of that kind of stuff comes into it. You've still got to have a good product and know who you're selling it to and at what price and how are you going to distribute it and all of that. So that's kind of core. You've got to have that. Beyond that, to skim over that, think that having the general
marketing fundamentals is Beyond that, think the future generations or someone looking to get ahead in marketing now, throw yourself into AI literacy in the round. Play with these tools.
Joshua Burkhow (30:17)
Yes.
Martin Broadhurst (30:19)
I've been speaking to hiring managers at my clients in the past couple of months and in a team with, I was working with a team I think they had around 10 or 15 marketers distributed across a few sites. hiring manager was saying for their next hire, they want someone that's got really good AI literacy and someone that had
Joshua Burkhow (30:41)
AI jobs.
Martin Broadhurst (30:41)
Very good CV, maybe even a better CV on paper than another candidate that had good AI literacy would miss out, because the AI literacy is skill multiplier and it opens up that person's ability to do more. Maybe they can't do data analysis but they can throw a few CSVs into a tool and throw a few charts together and
Joshua Burkhow (30:56)
Absolutely.
Yep. Yep.
Martin Broadhurst (31:08)
Read the charts and go, there's an insight to be gained from that. Maybe they can work quicker, they can iterate, they can ideate, they can proof.
Joshua Burkhow (31:12)
Yeah, totally.
The AI literacy is not just using the tools. You got to learn how to open Claude, write a prompt. Those are all good things, but AI literacy as, you're sort of feeding it and hinting at it is, is understanding why it works the way it does. And that seems.
To some, where that feels overwhelming. But AI literacy is really about understanding all the stuff you and I talked about. Where does it break down? Where is it really useful? Where is it good to use? Where is it bad to use? Where is there legal concerns? Where is there sort of governance concerns, privacy concerns, all these, like that's AI literacy.
Is there anything else you would add that's super important there?
Martin Broadhurst (32:03)
Yeah, I think that's a really critical part of it. The AI literacy is about understanding what it can and can't do from a capability perspective, but also what it can do in terms of risks it might introduce into your business, into expectations you ought to have with its ability to successfully and consistently, consistently being the key word there, perform a task over various time horizons.
Joshua Burkhow (32:16)
Absolutely,
that's right.
Martin Broadhurst (32:30)
Having that understanding of the failure modes is a key part of it, and I think you only get that through experimentation. technology is... I think Excel is a good analogy in so much as it's very very versatile, you go into Excel it's rows and columns and cells.
Joshua Burkhow (32:48)
Seems simple. Everything.
Martin Broadhurst (32:48)
But what do people use Excel for? People use it for financial
planning, for making birthday card lists, for making to-do lists, for booking holidays, for budgeting,
Joshua Burkhow (32:59)
Like building out applications, right?
Martin Broadhurst (33:01)
Yeah,
it's super varied and everybody finds their own use case for it. it's an incredibly versatile technology that you get more from the more you play with it and I think LLMs have that similar capability and if you're coming at it, if you've never put a prompt into a language model
you go in today,
there is a decent amount of catching up to do and I think sometimes if you're in the weeds with it like I am and you are, you might take for granted that they have tool calling now and mean tool calling wasn't a thing when when ChatGPT first launched,
Joshua Burkhow (33:24)
Time.
Yeah.
That's
i think the tool calling is a good one because, I love the look on people's face when I'm like, yeah, it checks my emails. can manage my calendar. Like these, can do these things. but at the end of the day, I understand and I look through and I pay attention to what are the guardrails?
We had a previously, and I have a couple of scheduled that we're talking about governance. We're talking about those things because they are part of this concept of AI literacy.
Martin Broadhurst (34:04)
Where do you
think that sits within an organization? Because I think this, for me this is a really interesting one. IT teams that I'm coming up against aren't all over this. This, a lot of them, is a burden, it's another thing to manage and roll out, and they're not really sure of it themselves, but they know that they've just read headlines about this thing called Mythos, which might be coming down the track that's going to be giving them a cyber security headache.
Joshua Burkhow (34:09)
Yeah.
Yeah.
Yeah.
Yeah.
Yeah.
Martin Broadhurst (34:31)
And
now they've got these people that want a Copilot Pro license or they want a Claude Code deploying into their Microsoft tenant they're scared because their natural position is risk mitigation and minimization a lot of the time. But then you've got the marketing teams or the, obviously this conversation is about marketing, but it could be another department, HR, finance, whatever.
That have seen a demo of it and gone, do you know what, let's get the shadow IT system, let's stick it on our departmental credit card and get ourselves a couple of Anthropic Claude Pro licenses and see what we can do. you're 100% right that governance is a huge part of it, I just think it's a messy world out there right now.
Joshua Burkhow (35:01)
Mm-hmm.
Yeah.
Yeah.
If you've been around 15, 20 years, you know, we, we didn't really get solid into the sort of data governance conversation until then. I mean, we're, still like the idea of true data security and true
iT governance much better than it ever was, but they're, they're still fighting the good fight. Like they're still figuring out new methods, new frameworks, new best practices and that. Data is a very complex thing, but it's a pretty well understood thing. Right? Like we,
we know what a database is. know what a data warehouse is. We know what those technologies do. We know how systems connect to data, how they could be compromised. Like these are all sort of the known knowns versus the unknown unknowns. And literally, one of my other guests said this is like AI governance is not the same as data governance.
It's just because it's got the same word. the concept of it, of being able to manage it effectively is, similar, but it's not a one-to-one. And I think IT teams just either they knew that right off the bat or they're learning very quickly that that it's not a, it's not an easy task. It's, it's absolutely not because there's CIOs in the world that are
spending an exorbitant amount of time and effort and capital on trying to get their teams hard secured, build up their security infrastructure, their capability, they're bringing in the right people. And now you're like, yeah, yeah, yeah, while you got the data governance, let's go, we got a new one for you called AI, good luck with that.
But it's one of those things that has ramifications to our, you know, can bring it back to our point is a single user,
not having the AI literacy, not using AI in the sort of right way can be dangerous. Like it just can't be.
Martin Broadhurst (37:12)
There was a great story, I read it this afternoon before recording this. So the NHS in England, the National Health Service, they've instructed their data and digital team to turn all of their GitHub repos private, and that there should be no public repos.
Except with exceptional requests and use cases. And the reason that they've put that in is because the rapid increase in the use of AI is meaning that people are to repos with vulnerabilities or, you know, they're, leaking API credentials or whatever it may be. And they are introducing all sorts of potential.
Joshua Burkhow (37:51)
That's right.
Martin Broadhurst (37:56)
Risks and the ability of AI to read those repos and identify those risks has gone up tenfold,
and I think that takes
us back to that point about the, so I was talking about the generalist marketer, but I think this is the case for the generalist whatever, right? If you work in HR, if you're a data analyst, if you work in sales, having AI as a skill is gonna be a force multiplier for you. If you've got the ability to use Claude Code or Claude Cowork or Codex or whatever it may be, you are going to be able to get more done. However,
Joshua Burkhow (38:11)
You
sure.
Yeah.
Yeah.
Martin Broadhurst (38:30)
Some point you're probably going to find yourself straying into territory that you're not super familiar with and going, you know, it's that classic with Claude Code, just hit accept, yes, yes, yes, yes, yes. And you're going to commit something to a repo that has your credentials in it, or you are going draft with a clause in it, which is going to come back and bite you in the
Joshua Burkhow (38:38)
Hmm.
Right, right, right.
Martin Broadhurst (38:55)
And you have to be the 20% of the human that still checks and validates and make sure you know what you're talking about.
Joshua Burkhow (38:59)
You got it. That's right.
Yeah, I love it. I think this is the sort of battle that people are going to have because you have the pressure from the company, pressure from the bosses, pressure from, you know, just society in general to perform and get this stuff out the door and ship it. We've always sort of had that. Now it's at a fever pitch.
Be warned. if you're listening to this, Martin has warned you, you have no excuse. He's told you that like this stuff, there's stuff that can happen. There's real consequences and that's something I...
That I tend to think about nearly every day, every time I'm interacting is like having that awareness, the understanding that this stuff can go south, it can hallucinate. Hallucination is still a thing. The other one that I know just getting into the weeds a little bit is just the, it's hallucination, but it's
that confident hallucination. AI will tell you it did something and it absolutely did not. oh yeah, I created a spreadsheet for you. It's got 15 columns and 400 records. And you open it up, there's literally nothing in it. that sort of thing requires you to check it.
You know, requires you to get after it. And so I think, you know, if people are walking away from this podcast, we're advocating for learning AI, we're advocating for literacy and understanding how it works. But I,
i want to sort of get into another section where if we fast forward six to 12 months,
where do you think marketing
Martin Broadhurst (40:40)
I think that's, that's an incredibly broad question just because of how much marketing encapsulates, but I think, I think what we see within teams is, AI-first teams, and by that I mean, teams with real people doing real work that are AI enabled. I think.
they will be moving faster, particularly around areas of research and analysis. This is the biggest win that I see when I go into themes is just showing them how quick they can move and how quick they can present. I've done workshops with teams where in the space of two hours, we've from start to finish kind of done some research, built some interactive dashboards or portals and
had something that they felt that they would take to another stakeholder that would previously have taken them a week or more to pull together. that is a huge quick win. So I think that's a big part of it. I think the other part is on the technology side itself. Yes, there'll be more people doing more with the likes of Claude Cowork and Codex, which can operate within the computer use space. So for listeners that aren't all over and it's
Joshua Burkhow (41:30)
Yeah.
From
Martin Broadhurst (41:48)
this and in the weeds. Computer uses the ability of an AI to actually use its own computer or maybe use your computer to do tasks, open files, copy files, click around, do stuff. And this is one of the areas where language models are getting a real focus at the moment. They're getting a big development boost at the minute.
Joshua Burkhow (42:01)
Sites.
That's right.
Martin Broadhurst (42:10)
I think this is going to do more tasks, more really simple tasks, I think people will be elevated, will posit it like this, they'll be elevated away from some of the more mundane tasks that they do.
Joshua Burkhow (42:13)
Right. Yeah.
That's right.
Martin Broadhurst (42:22)
But then in terms of the technology, like the MarTech stack specifically, now I'm a HubSpot partner I've been working with and reselling HubSpot since 2012, but if I look away from HubSpot and into the general stack, agentic use within the platform of choice is going to be massive and I think we're going to see this with
Joshua Burkhow (42:41)
Mm-hmm. Yeah.
Martin Broadhurst (42:44)
HubSpot have a thing called customer agents, they've got prospecting agents, we've got, I wouldn't be surprised to see similar agentic campaign development and creation coming out in the likes of MailChimp. Manus from Meta, or Manus which was acquired by Meta, has a Meta ads agent management tool now, so it integrates with your.
Joshua Burkhow (42:48)
Right
yeah.
Martin Broadhurst (43:08)
Meta ads platform and it will do campaign optimization. It will do end to end management of it. I think we're going to see a lot more of, of that. And that's probably in the six month timescale. I'd go to the end of 2026 beyond that. Who knows? I mean, we could have models that are brand new with whole new capabilities by that point.
Joshua Burkhow (43:23)
Right.
Martin Broadhurst (43:28)
I think in-house teams, this is another interesting shift, in-house teams will be able to, with tooling, some things in-house that were previously outsourced to specialist agencies. So if you've used a PPC agency, I think PPC agencies are going come up against it, what do they charge on? They have domain expertise of the channels with...
Joshua Burkhow (43:31)
Mmm.
Yeah.
That's...
Yep.
Martin Broadhurst (43:53)
Budget allocation and bid optimization and things like that. And then they know how to navigate the Google Ads platform or whatever it may be, you know, the programmatic platforms. feels comfortably within the computer use space for me. That feels pretty
Joshua Burkhow (44:06)
Yeah.
Sure, sure, And probably
anything that requires a distinct level of knowledge the power of the person knowing a thing sort of being undercut.
it just is. It's the ability for an AI system to learn that thing.
Me personally, I sort of stepped back from like, oh, this is definitely gonna happen and this is definitely gonna happen. And these people are definitely gonna be impacted because you even said to yourself, outside of six months, who knows? I do like being a sort of futurist and
imagining what five years out will be and how big my house on Mars is going to be. But like at one point you're like, I have no freaking clue. this stuff is moving. So the models are moving fast. Software that is built on the models is moving fast. The capabilities are fast. New technology is coming out or like good luck. Good luck. right. So
has been easy so far, but we got what I call lightning round. I think I have five questions for you, but they have to be first response, quick instinctive answers. no, it depends or sugar coating it or it could be this, this and that. It's like, what your gut reaction?
Martin Broadhurst (45:32)
Are they yes or
no or am I allowed a small expansion upon? Okay.
Joshua Burkhow (45:34)
You can elaborate, you can elaborate,
but it can't be a flimsy answer. It has to be sort of stake in the ground piece and we'll keep it brief and quick. There you go. Good. See, smart. You're smart. Spoken like a marketing person. right. So the first one, I'm going to go slow and then speed up, but one task AI should...
Martin Broadhurst (45:42)
Okay, okay, well I'll caveat all of my answers now with a, this might not be my actual position if you want new ones come and speak to me on LinkedIn.
Joshua Burkhow (46:02)
Absolutely own in marketing.
Martin Broadhurst (46:05)
Right now, for me, it's research for nearly every client.
Joshua Burkhow (46:05)
That's like.
Research. Got it.
One task that must stay human.
Martin Broadhurst (46:17)
One task that must stay human. Editing.
Joshua Burkhow (46:20)
Good, yep, we talked about that. skill marketers need to develop right now. Sort of talked about it, but what one skill specifically.
Martin Broadhurst (46:30)
I would say so I don't want to talk about just prompt engineering or something like that that kind of feels table stakes
i think the understanding agentic and getting familiar with that. So for me, that would look like dipping your toe in first with building Copilot agents or you even even like for real basic stuff, like get familiar with ChatGPT projects or Claude projects or Gemini gems. They're a really easy entry point, but do it.
Joshua Burkhow (46:43)
I was hoping you'd say that.
Yeah. Yep. That's right. Yeah.
I, so what I do is I, and maybe this helps folks on the call is if you get into Claude Cowork Claude Cowork is, I think of it as the mashup between the sort Claude that you would prompt and Claude Code that you would, you know, build out applications. It's sort of the middle ground there, but very prompt friendly, literally write a task.
say, hey, I want you to create this Excel sheet, but tell it to use an agent, tell it to say, Hey, I want you to deploy three agents to research these three different tasks and bring it back as one paper, one PDF that is well structured, formatted, blah, blah. And you'll start to, it is not what it is agentic, but it's not like when
sort of advanced practice of agentic AI, but it gets you to understand that you're now deploying one prompt, seeing three different bots go out and do these things, come back, and you're going to see the nuances. You're going to see if they all wrote exactly the same thing, different things, all that. Cool. Next one, we've got a couple more. One AI tool or trend you're and I would even add
You're cautiously optimistic.
Martin Broadhurst (48:21)
AI voice agents is definitely the one.
Joshua Burkhow (48:23)
Yes.
Yes, absolutely. That's a, that's always a big topic of conversation. All right. Last one. One mistake that you think most marketing teams are making
Martin Broadhurst (48:34)
I'm going to expand that, so I think one mistake that I think most AI users are still making is they are not being deliberate in their use of reasoning and thinking models.
Joshua Burkhow (48:37)
All right, good.
Mm-hmm.
Ooh, there you go. Can you...
Martin Broadhurst (48:53)
I think most people are using
Copilot with auto mode turned on, or they don't even know what extended thinking or reasoning mode is. And if that's it.
Joshua Burkhow (48:58)
Yeah.
So
Absolutely. Yeah. Tell just we have a bit like give me 30 seconds of why that's why would you say that? Why is it
Martin Broadhurst (49:11)
If you're unfamiliar with this instant mode in a language model is where it gives a response straight away and it's what's going on under the hood next token prediction is happening immediately and it's a bit like I say to you what's 956 divided by 72 go give me an answer and you've just got to say a number as quickly as you can. You might get in the ballpark of that, but
if you really want to work it out, you need to sit down and write out the steps involved and do the maths. extended thinking or reasoning mode, is it doing the thinking beforehand? So you can give it a tough question and it will go away and think and it can think for a few minutes, 20 minutes. mean, I've had it, the longest one I've ever had was 55 minutes where it was
going away and doing one particular task, which was crazy. And this is before it gives a response. And the quality of the output is night and day. I liken it to instant mode is kind of clever guessing, and reasoning mode is like your well-informed, well-read friend taking their time to carefully consider their response to you.
Joshua Burkhow (50:09)
Yeah.
Yeah, so good. Yeah. So the message being spend some time in understanding these different modes. And every model has sort of, most of them have extended thinking instant, but there's, know, different models that have different capabilities. And I think I probably have to have a whole new episode on, just token utilization and understanding the use of tokens. That's
That's a hot topic everywhere I go. But Martin, thank you so much. I absolutely love that you were able to really open this window from the marketing world and AI. Like that's super interesting, super fun. I'm going to share this with all the marketers that I know. Thanks again. I appreciate your time.
Martin Broadhurst (51:14)
Thank you for having me.
Joshua Burkhow (51:15)
Absolutely.
Joshua Burkhow (51:18)
I loved speaking with Martin. What stood out is how honest he was about the state of things. Most marketing teams are not in the middle of some clean AI transformation. They're dealing with too many tools, half rolled out, Copilot, Claude, Gemini, pick your flavor licenses. There's not a whole lot of real training out there yet. And there's no clear ownership of who governs
what? And he kept coming back to this idea that people getting real value out of AI are not the ones with the fanciest tools. They're the ones who actually understands where it works, where it breaks, and where a human still has to step in. And that framing sort of reset how I think about AI adoption inside of teams, especially teams that are not exactly built for fast change.
We spent some time and dug into the 80-20 rule. A lot of different variations of this, but for this one, it's where AI gets you most of the way there. But the last 20% still needs a human. We talked about hallucinations and the gap between real, true AI literacy and just basic prompting. They're different. We talked about governance. And we also talked about why editing and brand-level design still belong to the people.
We also looked ahead at agentic tools, things like computer use and how in-house teams are pulling work back from agencies. So please do me a favor. If you like this conversation, Alter Everything wherever you listen. We're on Apple Podcasts, Spotify, YouTube, and I don't want you to miss the next one. We got a lot to talk about. Thank you for listening.
