Katy Howell 00:11 Hello, hello, hello. It’s me again. I’m Katy Howell, CEO at a media future and I’m you know, for anybody else in the UK who’s watching, Isn’t it lovely? Look at the sun on me. It’s glorious sunshine. We’ve forgotten what you are. So today I’m really excited. This is part of our series, which is we don’t have time for this, which is for all of us who are just running around at hyper speed these days, because somehow, marketing has got so busy. And for those that feel that they’ve bought AI and somehow ended up with a kind of they’ve got the tool, but they don’t, it just sort of sits on the side, or, more importantly, they’re using it for really basic things. And it’s not somehow ended up as a useful thing. He’s ended up with more tabs, more drafts and more opinions and well, basically, we’re not alone. Okay? It’s been a real steep learning curve, and it’s really interesting that Gartner says 65% of CMOS think AI will dramatically transform their role, hopefully saving us time. But only 5% of marketing leaders say they’re using Gen I as a tool that is showing significant gains in business outcomes. So, in other words, we’ve got the tools, but they’re not actually delivering or supporting us quite the way we want them to. And this gap is why I wanted to do this series, but also because, in reality, I want to make life a lot easier for those of us in marketing. And in particular, I want to talk about AI where we’re not just kind of getting into the exciting bit about the technology but actually talk about it in a way that says, how do we give ourselves time back, time back. You know, how do we operationalize planning, reporting, production, all the things that are just taking us forever to do. So, I’m really pleased, because today’s guest is.
02:18 Hi Katy. Thank you for having me.
Katy Howell 02:20 Oh, it’s a pleasure. Well, you and I met at the FinTech Community Roundtable. And it was, it was, you know, I’ve been speaking to a lot of people about AI for quite some time, and it felt like you were one of the very few people I’ve spoken to who has been in the trenches with it and actually made it work. And so, head and shoulders above anybody else I was really talking to, you know, talking in a very pragmatic way. So, this is where I think, you know, you’ve been there, done that. You’ve done it all in a corporate enterprise. So overcame those hurdles, because for many it’s like, oh, you can use AI to do this. Well, it’s fine if it’s just you on your own. If you’ve got 30,000 people to get on board, it’s quite tough. So, Jack you need marketing operations and accountability in the financial services company Rathbone’s, but you also have much wider remit, lots more exciting projects that you’ve also done. So, there’s it’s got a nice balance, and I’m expecting practical clarity from you just so little meat has just decided, right? So, like I said, you’re ahead, Jack, and geez, really, what is it? Most teams really have struggled with working out where the drag is and not get how have you, how have you worked that out? Really excited about all the sparkly, shiny stuff. Yeah.
Jack 03:57 I mean, I’ll start off by saying that I’m not, you know, whilst I’ve had some really great experience with AI, I think it’s very hard to ever really feel like you’re ahead or on top of any of this. But I appreciate that there’s a lot of marketers that are going through some very similar challenges on this front. And AI, I think, has had a lot of FAD and a lot is really starting to get a lot of enthusiasm, if it hasn’t already. And the narrative really is just getting AI in at all costs to save time, without necessarily thinking about what the big bottlenecks or what the big challenges are for marketers and their respective teams. And, you know, I think, I think a lot of marketers go and joke around, you know, got to do the AI or get the AI to do your job. And it’s really not as simple as that. And for me, it’s really about. How focusing on that self-assessment point and ensuring that those processes are, you know, looking at the processes that you’ve got in play and the capabilities that you’ve got in house, and really working backwards from there to say, All right, well, how can AI help me with these particular processes or particular challenges or and build out problem statements in line with those.
Katy Howell 05:24 Yeah, and I think it’s, I went to a really interesting conference, and one of the things they said there was, you know, the first thing you need to do is map out what you actually want to do with AI, where it is going to save you time or whatever. Because if you don’t do that first, what you tend to do is run off down rabbit holes. So, I think it, you know, it’s, it’s, what was the first thing that you fixed, that you felt this is going to give us time back.
Jack 05:51 I think it’s, you know, we looked at, what are the things that are causing us time, you know, to really focus on. And a lot of the areas really that we’re trying to focus to focus on at the moment, and we’re continuing to improve on, is really that inquiry section of how we operate. And suppose a big part of what we do in the operations team is that we’re there to enable marketing, which is an enabling function within itself as well. So, a lot of what we’re trying to do is to help the team be pointed in the right direction, towards the right teams to help solve their problems, and so really mapping out those areas that we saw as opportunities to scale back on the number of inquiries that were coming to us. And some of the ones that were, you know, we have a kind of templated answer for we have a process in play and really focusing on those areas. And we built, or we’re in the process of, and still testing an agent we’re building in house, which is great. And I’ve actually spent some time this morning on a Microsoft sponsored AI course, which has been really insightful, because you can really see the power of how these agents are really enabling teams, not just in marketing and not just in companies the size of rough bones, but to really start automating things or providing the answers to people without having to read through a horrendously formatted and really long document to get there?
Katy Howell 07:30 Yeah, absolutely. And it’s actually some of the very basic things that have freed up. What I think is the ideal is it frees up time for you to think as a marketeer, and we have so little thinking time that little bits like, you know, back in the day as an agency, you were forever writing up notes, you know, you had a call, you had a conversation, you wrote up the notes. You then wrote up the summary of the notes to send in an email. That bit that took you suddenly get back. And I think that’s where, for me, there’s a really quick win. But what, what changes to pro or are there changes to process and ownership to make, you know, go from the individual to the corporate to the wider world. What processes do you need in place?
Jack 08:23 I think AI, I mean, ultimately AI magnifies everything that’s already in play within a business, right? So if you’ve got really strong and diligent processes in play, and you bring AI in to complement those, then you will be saving that time and kind of to the example that you pointed out there with note taking, you’ve got to have the right tech, you’ve got to have the right channels, and you’ve got to have the right resources in play to make that work with some of the more complex demands of artificial intelligence. What I’m seeing is that people need to put in the legwork, and often don’t realise that they have to do that to really make a success of it, because otherwise you just, as you say, you end up bringing something in play which can cost a lot of money, which can, you know, take a lot of time to implement, and isn’t always necessarily enabled by the baseline infrastructure of you know, what do we do? How do we do it, and why do we do it as well, importantly. And I think understanding what your strategy is top down and really being able to feed that into your AI strategy, or just your structure for whatever tooling you’re bringing in is really important.
Katy Howell 09:37 And how do you So, what do you recommend? You know, standardising one of the biggest challenges that we have as organisations the AI, is that where there’s quite a lot of fear around it, pumping out something that just either isn’t true or is is it’s not something we’re very comfortable with as an organisation. So how do you how. Do you kind of, you know, standardise the AI output to stop the fake quotes and the mobile ugly hallucination?
Jack 10:10 Yeah, and that’s a really interesting point, because I think this feeds into quite a narrative of jobs being taken by AI. And I think that particular use case just shows that that’s really not the case. The more important thing is that people need to get on board with AI to avoid having their jobs being taken by something else, or by AI or by a specific piece of tooling, because that is really the focus of being able to do more with less. And you know, with the example that you mentioned there, you know, we’ve seen ads go out with six fingers on from Ai generated imagery. We’ve seen all sorts of nonsense kind of trawled over the internet. And I think that, you know, if you weren’t using AI for the same sort of initiatives, you’d still have to do your due diligence and fact checking on those fronts. And, you know, the AI systems are getting better, and there are, you know, you can almost compete different AI tools against one another as well. You know, we mentioned Claude. You’ve got Gemini now, which is really, you know, a fast-paced co-pilot if you’re in with Microsoft. And you know, using those channels and making sure that they are doing what you’re asking them to do, and that the briefings are right, and that the prompts are clear, and also that, you know, there is that human element of fact checking and really ensuring that what is being put out into the public domain is has gone through the Right due diligence, especially in a regulated environment when you know financial promotions and consumer understanding, it really kind of come into play in the financial services world anyway. But the AI is not the solution to everything, but it is. It can really accelerate a lot of the legwork with a lot of the things like the content, like the image generation and other elements like that.
Katy Howell 12:08 I always think it’s AI can get you, sometimes 60 to 70% there and take all the really boring grunt work out of it. But you’re right. You do have to. I mean, governance around AI is really important, from my perspective, which is understanding that you know, even little things that AI just doesn’t it, you know or forget things you know, you’ll say, here are all the standards, and it forgets it, and it doesn’t always behave the way you want it to behave. And if you write, I mean, God forbid write me a blog on the topic of AI, you know, it’s the usual, you know, inference, garbage in garbage out. The truth of the matter is, you need to be really focused. I mean, some of them, I don’t know about you, but some of my prompts run to pages, you know. I mean, they are full of detail and what my angle is, and blah, blah, blah, and I just want to help in structuring it. I don’t want it to write it for me. I want, I wanted to get all my messy thoughts out of my head and into a structure, but just even in simply understanding that and how that impacts your job, and therefore how you make sure that you don’t find yourself redundant in your field of expertise. Is the bit that, I think, is the bridge we need to cross this year, and training is part of that, is understanding what an LLM actually is and how it works without all the technical thing that everybody goes on about so, you know, how are you helping your own team really forget the wider company, even understand what works, what doesn’t work?
Jack 13:53 Yeah, I’m it’s not even something that I feel like I’m having to do at the moment in the scope of my role. Because whilst I’m passionate about it. It’s, it’s not within the scope of my immediate responsibilities to, you know, enforce it. You know, I certainly champion it, and I’m part of internal programmes like the Digital Champions, which is great. I think beyond that, it’s, it is just trial and error. And you know, if you’re nervous about anything, it’s really about building out the right structures in place, that nothing is going out without the right diligence being put into play. And you know, a lot of these systems, you can do a lot, especially if you’re in a corporate environment most of the time, or the advice, I’m sure, but that most InfoSec teams would provide is that these things are gated and that they’re not going into the public domain, and that you have that opportunity to really, you know, play with fire as much as you want, without there being too many consequences of it. And it’s, it’s really about pushing the boundaries for me, and I think this is. What people are trying to do in the next or will be trying to do over the next, kind of well into 2026 2027 because, you know, getting an AI tool to take notes or to write emails is really the tip of the iceberg of what the capabilities of these tooling is really starting to look at. And, you know, the business Rathbones Anyway, and I’m sure many other places should are encouraged, and should be encouraged, to try and find ways in which AI can help them do their jobs and move forward from there.
Katy Howell 15:34 And I think, you know, we’ve got some questions I can’t have. I have to add that the part that’s joyous for me, having, you know, a more scientific background, and my obsession with behavioural science and why people do things means that I spend all my life data crunching and have done through my marketing career, and that means I do know my way around an Excel spreadsheet and how to do conditional formatting. We don’t have to do it anymore. Just I know that I can throw a lot of messy detail now. I have to ask the right questions, and I think this is the key bar. I have to write the questions that are the questions an analyst and a strategy and a planner would ask. I can’t just throw it all in there and expect it.
Jack 16:21 You’ve got to contextualise things right? Because, you know, to your example there with Excel, you know, you might have data in a format that an AI tool hasn’t been trained to process, either in that order or in that format. And as you say, you know, really kind of getting ultimately, you can train these tools, right? These are things that cost a lot of money and take a lot of time to set up, but, but I think people need to start looking at these things like they are part of the team. They are like new hires. And, I mean, you know, I’m sure everyone will have spent a lot of time, you know, nurturing new employees or graduates coming out and into their jobs. And look, you know, AI, when you buy it off the shelf is, is no different, really. You know that it can do a lot of things, and it’s it can help you and your team, but, but it’s not always going to have the right context or the right understanding of the immediate needs of the business, the team, or how you like to operate. So that legwork, again, it always comes back to that preparation and that emphasis on really wanting to, you know, put in the effort to make this work. Because once you build those foundations, actually nurturing them thereafter is a considerably easier job than actually having to start from scratch every time because you’re not doing the right implementation in the first stage.
Katy Howell 17:45 Yeah, absolutely. Treat them like an intern. That’s my view. Exactly. We’ve got some questions here. Gemma’s on. Put the glasses on so I can see them, because it’s very tiny. On why? So, wants to talk about governance. So, Gemma is asking. Really interesting. I totally agree on the governance due diligence. What are your tips for making that argument to someone who thinks AI can truly do everything?
Jack 18:13 This might sound like a bit of a passive aggressive answer, but I think get them to show you, if they’re trying to prove a point, to say that AI can do something that it can’t really challenge them on that really try and get them to showcase because, look, I mean, anyone that’s listening to this will be in marketing, and everyone that works in marketing will know that everyone thinks that they’re a marketer at some point or other, and with these sorts of things, you know, if you are being challenged by other areas of the business to do that, then it’s really kind of fighting that similar battle that I’m sure many of us face before to say, look, these the boundaries of where these things can sit, or really emphasising, these are the boundaries that we’re comfortable using this tool With, right? And, you know, and these are the risks that we’re doing, and sometimes documenting the risks of AI and those really setting those boundaries very clear. You know, in my opinion, that maybe isn’t the job of a marketer, but depending on the size of the company in which you sit in, you might feel like you’re having to do that for some of the tools that you own, or the structures that you’re bringing into play around these because, you know, as you said, you know, you’ve compared AI to incredibly smart and info fuelled intern, and you wouldn’t really expect someone that’s new to the business without a core, you know, training period or implementation period, to have all the answers, or to be able to go off and do everything and again, outside of that, you know, a lot of these AI tools are specialists, right? You know, things like Canva has a have loads of AI tools, Adobe, a lot of these kind of design focused element state. They’re great at doing what they do. Doing, but you don’t want them to write your emails for you, right? And you don’t want them to be taking notes on a call simply because they can’t. And it is really it comes, always comes back to me around mapping and making sure things are documented and that things are clear and that things are outlined in as much detail as you can possibly bring yourself to write down to make sure that you’re covering your own, your own ass, essentially, because other because otherwise you know you do end up in a situation where people are forcing you to use something that you don’t feel comfortable with, and then you have an ad with someone with seven fingers out in the public domain, and that’s no fun for anyone involved.
Katy Howell 20:42 No. And you hear the horror stories again. And sometimes, you know, for those of us, like myself, often have that, oh, AI from brands and we’re agency, and I, you know, I will often say, Yeah, I wouldn’t get it to write your post. And they still go ahead and do it is you also act like any, anything. You have to let people fail at it first. You know, so. But you got a great question here from George, which I just want to put up. So, Jack, what would you describe as the biggest blocker for implementing practical AI tools? Considering, I think this is a really good.
Jack 21:23 yeah, it’s the blockers. The blockers there are. There are many. And I think the way, I think the geopolitical situation doesn’t help at the moment, with a lot of the AI tooling being based in America, and I think a lot of the regulate, the regulatory requirements that companies have to work around, or ensure that their data is protected, and that that is a is a big challenge. But I think what we’re seeing that that isn’t just a challenge for the end clients, is a challenge for those AI providers as well, because I’m sure that those big companies and the you know, the size of Microsoft, and even, you know, going lower down into the Adobe’s and the canvas and lots of other companies that offer AI tooling, they will want to be able to offer tooling of this nature to The right organisations, and be able to provide the right, you know, ensure that data isn’t going to be captured by God knows who. And really ensure that, you know, the ISO certifications and all the InfoSec requirements are really in play. It’s not something that I would necessarily THINK, THINK sits within the marketing function. But, you know, I think getting on board with through a really strong procurement process and a supply management process is really key to that. And those depend, those are key dependencies for ensuring that any AI tooling that’s not built in house is it is used in the right way and doesn’t really push the boundaries of those InfoSec requirements.
Katy Howell 23:12 I think also there’s the other side of it. There’s the privacy, as you say, and what it’s turned out, but there’s also internal governance, and you know, which is nothing leaves the building, nothing moves from department unless it’s had. You know, oversight from would normally do from compliance, or from blah, blah, blah, all the usual things still need to sit in place, and that’s why humans are not really being excluded at this stage. It can do the base level. It can suggest it. I mean, I know someone who works at the European Commission on the more legal side of things. And of course, the legal workforce has found themselves in the same place, which is AI is saying it can do it, but it always needs lawyers eye over it, and it always needs who have been there and lived it to be able to go, Oh, hold on a minute. That might be technically right, but if we put that in there, it’s going to be an absolute mess afterwards, because we’ve been so, I think you know, assuming that AI is just going to we’re going to be just having a staff of a whole load of robots churning things out, speaking to other robots who are also churning things. Just that is not going to happen, no?
Jack 24:23 And I think you know compliance teams, you know if through, like financial promotions, consumer understanding, consumer duty and so on, a lot of those teams, again, much like marketers should be going to embrace AI and understand they can support them in what they’re being asked to do. Right? It’s no, no real different for you know, especially from an operational standpoint of marketers will use it differently, but it’s really enabling those teams to have the right the right structures in place, to use it for their particular use cases in their problem statement. That they’re finding because, you know, they might feel that they want to review things in a in a strong way, and that an AI might point out things that they’re recommending to kind of jump through. But you know, as you say, it’s always come back to those kind of processes and that diligence really, that’s required to really enable these things to operate effectively.
Katy Howell 25:22 So we have one more question from Tom, who works with me, so but this, this is very pertinent at the moment, content generation can be useful, but do businesses need to focus on the marketing tools that help link that content performance to the sales funnel? A lot of focus seems to be on generating more content, rather than focusing on what actually the content is doing and rehashing what does.
Jack 25:48 Well, yeah, it’s a really, it’s a really good question. And I think AI is, is a form of tooling in a way I think, you know, we need to not distinguish the two too much. I think it really depends on the on a business’s needs and what they’re seeing work as well. Because, you know, the term, you know, content is king. I think still applies a lot. I think it varies depending on the channels that you’re using, and I think that you don’t just want to churn out content for content’s sake, right? That’s not it needs to be strategic, and it needs to be focused on, on providing insight to your prospects and your clients that they wouldn’t otherwise be able to get elsewhere. That that really is the primary objective for me. But I think the key thing here, really is if you can, if you can have tooling that uses AI or use AI outside of your immediate tooling that can enable you to do that in a, really, in a much, you know, if you’re saving yourself 50% of your time compared to what you were doing before, by using those tooling’s and being able to track that performance in a way that really does highlight to you, and again, using that data with AI for it to kind of tell you what’s working well, you know, you use the example of Excel there. You know, all of these things need to come into play and complement each other, and AI can help at every step of the process, but it really is about those individual use cases and ensuring that it things are targeted. Is it things are strategic and things aren’t just, you know, copying an article into chat GPT and asking it to rewrite it and sticking it on your website or on your socials, because, you know, you might have success with that in small circumstances, but it’s like anyone saying, oh, we need this to go viral. There’s no real recipe for making that happen. And you know, it needs to be really focused on data, in my opinion, on that one, yeah.
Katy Howell 28:01 and I think there’s another, you know, it’s a common question we get asked, apart from the can we make it go viral? Is, how many times should I post on that channel? And that’s really how AI will behave. It will it will behave like, how many times should I post? Well, three is the norm, but actually it has no context, your audience, or your business, or what you’re trying to achieve, or what campaigns you’re trying to get across, or anything, no context. So unfortunately, you can end up with, you know, a lot of slop. And we see it again, again in social particularly it’s, it’s, I can, I guess, I don’t know if you’re the same, but you spend so much time in AI. I know when AI has written something I could just see, but I think, I think clever and taken out the M dashes, I can see it.
Jack 28:56 I know, but I think you can see the, you know, I I’ve been lucky enough to see some fantastic tooling, you know, the past year, a year or two. And, I mean, some of the stuff can really, is really exciting, because it can provide that emphasis on giving you a performance rating before something is out there and in the open. And I think that’s where, again, you don’t just need to use AI to generate content or generate imagery or generate, you know, whatever you’re going to be posting into the public domain. You need to use AI to optimise that content and really ensure that if it’s telling you, and these AI tools can learn these algorithms like you know, far quicker than any human can read through them, you know. So, there are, there is some fantastic tooling out there to really enable that optimization and ensure that things happen effectively outside of just the. Generation point, which, which I think really is underutilised a lot, and really does require marketers to have quite a mature tech stack and AI strategy, really, to implement those.
Katy Howell 30:12 kind of brings nicely on to Darren’s question, which is, what tools are we using in the last three to four months that you weren’t using before?
J Jack 30:23 It’s a really good question. I wouldn’t necessarily comment for the use cases that we’ve got a Rathbones initially. I mean, we use copilot quite a lot, and I think that’s something that we’ve used immensely more. I’d say, beyond that, you know, you’re seeing a lot of these tooling’s like Claude and Gemini really compete with chat GPT now, and chat GPT is losing a considerable portion of this market share. And you know, Claude’s push for market share at the moment is really around. You know, they know ads are coming, and they are saying that ads aren’t going to be moving forward on this. You know, I wouldn’t necessarily want to advocate for any specific tooling myself. I think, I think it really does depend on the circumstances that people are experiencing and, you know, there’s a, there’s a great website called chief Martech, which really kind of breaks down a lot of the AI tooling based on what it can do for you and how it can work for you. That’s definitely something to go and check out. And then it is a case of doing some discovery, right? People can get really overwhelmed by a lot of the options out there and the tech available, and I don’t, I can appreciate that that is is challenging to navigate. But you know, you can’t focus around what’s available out there in the wide world. You need to focus on, on what’s happening within, within your reach, and within what you can see, and then really, really focus on those elements and work backwards from there as to how, what can be a solution for these problems, things we’ve outlined.
Katy Howell 32:08 And also, I totally agree. I think we can get again, you know. And I know you, Darren, so you won’t, you won’t think I’ve been rude, but we get very distracted by the new and shiny. And actually, there are two elements to this. The first is, well, three. Sometimes sticking with the one you’ve got can actually help, because you it grows with you. Whatever tool it is you’re using begins to understand you and your business, and you can start to put instructions in there that become shape, become the shape of the way it performs. One of the challenges is in writing the prompt, because you don’t really know what you need to prompt for till you start experimenting, you know. So, I think there’s, there’s something to be said for sometimes hanging in there with what you’ve chosen. The second is, I think that customising, and I’d be really interested Jack, to see what you think about this, which is creating custom GPT’s of your own, you know, are really valuable, and of course, you can then wall them away from I think PWT has a version of its own GPT that is walled away. And I think the final one is, don’t forget about, you’ve talked about tuning, but don’t forget about the tools that sit in the products we already use so GWI, for instance, which is doing loads of insights, you know, tells you, you know, if you were looking up IT directors, or finance, purchases or whatever it is, it will tell you what their behaviours and everything are. They’ve just launched within their own tool, an AI that has taken some time to get there, called something spark. Can’t think of it now, but it’s really terrific. And what used to take ages now takes you, particularly if you just want that one bit of insight, you know, what are the priority channels for this kind of buyer or this kind of consumer? It’s really worth it. But you know, are you experimenting with more customised AI.
Jack 34:07 not necessarily customised tooling we’re looking or something that I enjoy playing around with, is the building out custom agents based on existing tech? So really kind of training, an AI tool for a specific use case. And I think that that comes back to the point that you made earlier, that at the end of the day, it’s horses for courses, for these sorts of things, right? You know, there’s, there’s so much out there, and, you know, there’s only so much budget that you can spend on this, right? That’s another kind of challenge that I’m sure all marketers will relate to there. And you know, you’ve got to be selective as to kind of what the really key points are and how, you know, how do you want to address those? What are your priorities? What are the ones? What is the tooling out there that’s going to save you? To 10 20% compared to the two or 3% that you’re currently getting now with, you know, it writing you an email, or, you know, giving you some time back from, from taking notes, you know that the automation opportunities there are incredible, and I’m, I’m trying to educate myself on that front, it really does take a lot of work to get to that point. But look, you know, it’s an education process for everyone. And I think, you know, we’ve spoken about the idea that people need to kind of go out and learn AI or, you know, or else, and that can be perceived as harsh, but I think everyone needs to kind of take a breath and realise that, you know, there’s so few people that are actually in play and using it, using AI, to its full capabilities. I mean, I’d go as far to say that I don’t think anyone is probably using it to its full capabilities. Yeah, we are scratching the surface. So, you know that there’s a lot going on, and I think getting an edge on it is going to be a massive competitive advantage. And you know, you touched on it there. And I think a lot of these AI tools, they, they grow with you, right? They, they are becoming hyper personalised and hyper focused on the way teams operate, and the language that’s used, even in the prompts these tools pick up on these things. And I think a little bit off topic, but I think a really interesting dynamic that I think we’ll see over the next five years or so is that people may feel to feel like, you know, do I want to move jobs? You know, they might think twice around those things because they’ll have to restart all over again on their AI stack. And, you know, they’re the relationship that they’ve built with their own, you know, co-pilot, for example, you know, and how co-pilot responds and interacts with their work life, and, you know, we are at that point now, but it does take time to get
Katy Howell 37:07 I’ve never even thought about that. But yes, yes, as I said to you earlier, we’re trying to migrate out of GPT at the moment because of its current alignment. It’s, you know, because we don’t want to, we don’t want to take a risk that our data is going somewhere else, even if it is, you know, just our data, not our clients, and it’s just, it’s, it’s that kind of thing as well. So, we’ve got a very fast evolving space. We’re having to think about it, and yet we have very little time to do so. So, I’d say, how would you if you were starting from scratch? Where would you start?
Jack 37:49 if you were starting from scratch, I would get your team in a room for three hours or half a day, however long you feel like is relevant, and I would give them carte blanche to go and just rant and tell them to tell them to tell you what their pain points are, what their frustrations are, what slows them down. How much faster could they be, you know? Or what are they hearing from the rest of the industry? And really start building out that conversation of transparency to be able to say, look, we’ve actually banged our heads together here, and we’ve had, we’ve had some thought on, you know, what we think AI can do for us? And you know, we still need to kind of have a think about these things, and we need to kind of see what tech is available and who we’d want to invite to an RFP, and you know, how much budget we can actually get, but, you know, really understanding your own situations, I think, is that is the first starting point for not just AI, but for any piece of tech. And it’s so, as we said at the start, you know, people just want to bring in AI for AI sake, to basically have a bit of a tick box to say that they’re using it rather than actually bringing in something that’s going to work for them. And, you know, you’ve got to really take that inwards, you know, look and observation and do that self-assessment to really get the best out of this tooling. I don’t think there’s any other way. And you know, I’m sure you could pay a consultant a small fortune to do that for you, but you know, I think just really enabling people to bring their own opinions and their own frustrations to the table is a great starting point, because probably a consultant will end up doing that anyway. And you know, then, if you need support going out and getting the tech, and that’s a different thing. But you know, it’s really about, you know, you’re the only people in the business that can actually understand what you’re going through better than any. Anyone else, at least, and so really focusing those elements is key.
Katy Howell 40:04 yeah, and I think it’s as a marketeer, it’s an exciting space. I mean so much to think about with AI, because obviously it’s not just affecting us, but it’s affecting our audiences as well. So, but I do think that experimentation and the freedom to experiment really adds value and that element of learning together, it’s quite bonding, really, isn’t it? It’s kind of like, right this, let’s go with this. But I do. I’m totally with you. I think the first part is find the pain that’s sitting in your organisation. What is holding up your teams so that they, you know, we’re all trying to do more less. So, what is holding up the team? What is stopping them from being able to do the things they love doing as well, as, you know? So, get rid of all the more administrative things, I would say, the basics. But there’s some lovely stuff that you can start to add on, like, you know, it can really help with decision making, because suddenly at our fingertips, we can throw data together that would have been awkward for us as marketeers, but, you know, it could be, you know, calls customer service, calls, you know, and putting that data into a machine that then looks because that’s what elements are so good at, is finding the pattern. Is finding the patterns. Ask it, what’s unusual, what’s weird, what’s changed from last month? You know, all those sorts of questions really can support. And one of my big bug bears is, I don’t think this is the job for the intern. I think this is a job for leadership, and leadership needs to carve it. I mean, what? What are your thoughts on that, you know, who should take responsibility for this?
Jack 41:47 I yeah, I mean, the implementation needs to be led top down. For me, I think, I think that’s, that’s clear. I think where I’ve seen Not, not so much, not so much of AI, but the best use cases for successful technology being implemented is that an idea comes up from someone that’s in a junior position and then gets seriously evaluated by those leadership teams. And I think that’s a great way to do it, but it needs to be championed centrally. It needs to be managed centrally. And I think, as you say, those opportunities really there are boundless and if any leadership team can’t see the value in it, then try and get an hour in their diaries and just show them what it can do. Because it is, it is outstanding, really, the information that is available at our fingertips, and that can be formatted in a way that is completely customised. And it’s, it is really that, you know, you need to blow someone’s socks off, essentially, if they don’t buy into it, because that’s, that’s where we are, and it can do it.
Katy Howell 43:00 I love that. It’s a great way to let’s go around blowing people’s socks off. Terrific. Thank you, Jack. Do you know what’s heartwarming, but also, it’s interesting, because I think we’re all on this same journey, particularly those of us in in larger businesses, is that we’re on this journey of we’re using it. We’re trialling it, we’re learning with everybody else, and we’re bringing everybody with us. But there is real value in saving us time that sits within this that we can start to use to learn how to use these tools even better. Have you got a passing thought for our fellow marketeers in the same place.
Jack 43:43 I mean, yeah. I mean, you know the phrase all the gear, no idea comes to mind. And I think it sometimes is getting the right gear and getting the right ideas, really, that’s all it comes down to at the end of the day and making sure that those complement each other.
Katy Howell 44:00 And as they say. JFDI, I’m not going to spell that out in case this goes out on audio. Thank you everyone. Thank you for all the comments and the questions, and we can hang around afterwards in in the comments section on here. So, if you’ve got further questions, you just, just let us know. Thank you again, Jack and thanks Katy, see you all in a few weeks. Bye, everyone. Bye. You.