In this episode, we explore how AI is transforming creative workflows, from speeding up mood boards to automating repetitive tasks. Our experts discuss the balance between human creativity and AI tools, and how the right blend can unlock massive productivity gains. Whether you’re curious about AI’s role in ideation, content creation, or customer service, this is a conversation packed with insights to help your team work smarter and faster.

Full Transcript:

CJ: Hello and welcome. I am not Katy Howell, as I’m sure many of you were hoping to see today. Katy, unfortunately, she has Covid. She is very ill. Anyone that knows her will know that if a virus comes her way, she normally absolutely kicks the backside out of it and plows on with work. But this one has knocked her sideways. So rather than you having to listen to her cough and splutter, she’s asked me to step in, which is a real shame because we’re talking about a topic that is really, really close to her heart. She would say she moans a lot about it. I actually think she talks a lot of sense about the topic. We are going to talk all things AI and as you’ve picked up from the title, we want to cut through some of the B.S and we want to find out whether it really is brilliant or total bull. And to help answer that, I’m genuinely delighted that we’ve got an absolute brilliant person joining us today, Tom Harris, co-founder of G3NR8, a leader in helping global brands unlock the power of AI. Tom, thank you for coming and chatting to us.

TH: CJ

CJ: Good morning.

TH: Hi. I don’t know whether it’s just me. I was having a couple of sound issues there. I could just about hear some of that, but not all of it. Can you hear me, okay?

CJ: Yeah, we can hear you. It may have been because you’re in the back of the studio, and you’re coming through loud and clear.

CJ: Let’s talk about AI and put some context around what we’re talking about. Because AI is no longer really optional for B2B brands. I think we all know it’s here to stay. It’s being used, but we want to know if is that a good thing? The journey to successful AI implementing is filled with a myriad of challenges from data management to technical infrastructure. That’s before we’ve even looked at the legal and ethical concerns that come with it. To start, I want to pull out a stat. Katy dug up a report that was from Deloitte, that found that 94% of businesses who surveyed their leaders, believed AI is essential for the success of their business in the next five years. Quite a compelling stat – 94%. I want to delve into some of the challenges and explore some of the more practical strategies to help overcome them. So, let’s start. Tom, give us some background about your journey into AI first and why you are the man to help us answer all of this today.

TH: All right. Well, my journey into AI started about 18 months ago properly and it was because I was working on launching a new brand for a client. And as part of the brand launch, they were running a series of new campaigns, and they could not get the shots that they wanted for this specific campaign idea. And so, the team I was sort of leading and working within, we had started playing around with Midjourney, and it was on version 3 or 4 at the time, I think. And we managed to create this campaign for them that, you know, I mean, we’ve all worked on different campaigns. It would have gone into, I reckon, six figures had you try to do this without AI, right? We were trying to create this crazy sort of retro, 80s-based hype campaign and the tone and the assets needed to be a certain way. You would need actors, you would need studios. You would need to shoot. You wouldn’t get it through stock photography. We used AI and what we did, we were blown away by and the client ended up using it. And that was the very beginning where I thought this has got so much potential, you know, and at the time that was in marketing and now where we work, in G3NR8 as we work across, you know, a whole range of different areas, marketing being one, operational efficiency being another, data being another. But that leading to being able to take and use some of these tools to deliver stuff that could be used out in the real world was what started my journey into it.

CJ: Amazing. Let’s start with some of the basics. You’ve given a brilliant example there already, and I’m sure people are looking at it thinking, that’s awesome! I’m sure some actors out there are probably thinking, that’s not so awesome. We will get to that in due course. Let’s start with the basics. What is AI good for, Tom?

TH: Right today it’s good for, you know, quite a few different things, but they tend to be sort of slightly narrower use cases. What you would believe, and you know, let’s say we’re all in marketing right. So, we know how to promote ourselves in a product or at least, you know, if you are in marketing, you know, that. AI marketing would have you believed that where we are today is it could solve every single problem under the sun. The reality is that’s not the case. And I don’t think we would want that anyway. Right? We’ll get into the whole balance of people and technology and where it fits and where it works well and where it doesn’t work well. But today, the really good use cases for AI, are of course, things like ideation and content creation. And again, how you go about that determines how good the output is. So, ideation, content creation, very, very good. Repetitive tasks – we see the huge increase now in our clients really getting on and being able to start to automate some of the more mundane, repetitive tasks that they do again and again to free up little bits of time for them to be more strategic or to have more time to think. We see it being using data where, you know, we’ve had this thing of data is the new oil or the new gold or the new whatever. For a while, data is really key. We know that. It’s actually really key in the world of AI, but we’re sort of swamped with data. Especially if you’re working in strategy or marketing or in those fields, you’ve got platforms or producing data, really hard to get a hold of. We’ve seen a really good use cases to be able to simplify and understand trends in data. And then the big leap is crossing the so what chasm, which is what we call it, which is okay, we’ve got this data and insight. So, what do we do with it? And generative AI is brilliant for that as well. It taking us that over that chasm and into actually delivering on the back of it. So, there’s some of the things that it’s really good for today.

CJ: I’m interested to talk about mood boards for a second because I agree with everything. Well, as an agency, we would have agreed with everything you’ve been saying. I think one of the things that we’ve had to understand at IF are the smart ways to use AI and where it has a role, and equally where you need to bring that human touch in to make sure that it’s right and got obviously good prompts in, good information out and all that. I’ve recently used it for a mood board or in fact, let me rephrase that because I’m taking her glory. Katy recently used it on a mood board for me and the output, she’ll be laughing because she won’t be watching this at home, and she will know exactly what I’m talking about. We ended up with what looked like clipart outputs. It just wasn’t right. So, I found myself going and manually creating the mood board. So, I’m interested to see and hear from you about where it’s worked in some of those creative scenarios, and equally where it has not, and the more traditional old school resources and people where we have to be for, where do you think that balancing act is, Tom?

TH: Well, mood boards, I like that great example of where AI is super strong, and you know, the old where mood boarding to a large degree was looking at stock photography and trying to find the right image, which takes ages. And sometimes you can’t get the right imagery. Mood boarding is a really, really good example where you can rapidly find or create the right images for a mood board to put it together. Now, does that mean that anybody can do that? No. Right? Because number one, you’ve got to understand the brand and the message and the tone and what you’re attempting to do. You know, if the mood board was leading into a campaign, you have to have an understanding of those things otherwise you’re just going to, you know, you can get very good at creating lots of random imagery otherwise. So, you still have to have somebody’s skill going into it. There is also the skill on the tool, right? It’s not just as easy as a simple prompt to get in there. Some of our creators that work in our team, I mean, but for the last project they worked on, they produced over 4000 images and to refine, to get down to final output. Right? So, the road time is needed to get to this point. But you know, if you want to have a look now, Midjourney is a good example. It’s not the only image tool out there, but it’s one of our favourites. You can go to media, and it’s got a web interface now. Used to be on Discord, which was terrible interface, and hard to get on. It’s got a web interface. You’ve got an explore category, which is like sort of like a Pinterest explore option. And you can go through and search for all images that have been created. You can find the ones that you like. You can auto generate prompts to recreate similar images. You can even train it on images that you really like within a specific area, and then create more like it. And so, with the tools, enhancing in terms of the functionality and what we’re able to do with them. But move boards are a great example. We’ve also helped the client with storyboarding. They used to storyboard, sketching everything out. We didn’t want to take all sketching away because actually it’s a good skill and everything else. But what we could do is we could take one of their sketches and we can create ten new versions of it using Midjourney. And so, we’re not trying to totally replace the person who’s doing the mood boarding and sketching these things out, but we can accelerate what they can do with AI with, you know, working with the tool. So, some really interesting areas.

CJ: Love hearing you say that because one of the things I still love, when we go in a creative tissue session, I’m a proper old school. I love taking key line drawings of a concept, Tom, because the people can visualise what they want to see it is coming to life. So, I’m delighted to hear that sketches are still prevalent in the process.

TH: Totally. So, on that, just a quick one that’s like, you know, I mean AI the whole time, I use lots of AI tools, I still write notes in my book because the process of writing notes that my ideas down helps me formulate them in my mind and helps me understand stuff. So even though I’m insanely enabled with technology and AI, writing my thoughts or ideas or sketching stuff out, I still do it on a pad every now and then because you need that as a process, right? And so exactly that is understanding why things work. Well, I’m not trying to replace everything.

CJ: We kind of answer the next question. I wanted to delve in from a strategic perspective. Who’s really calling the shots? The human brain or AI? You’ve already alluded to it. It’s got to be the human with putting the right prompts in, the right instructions, the right direction into the tool to get the good information out. Right?

TH: Yeah, yeah, totally. I mean, you know, what we had with AI was this massively leap forward in terms of technology. And when we first used ChatGPT, when it came out, the writing was incredible, like mind blowing, right? It was like, this is a new leap forward. But for most of us, when you used it for 2 or 3 weeks, you would look at the writing and you go, I never use that. I never use what it’s giving me as an output because it doesn’t sound like me or it’s not in our brand tone of voice. So, it’s not the way I want it. And so, to get to higher quality outputs, totally. It’s the teams and the people leading the technology. And that’s also super important because if it isn’t what we know as well, AI is good for us, it’s really good at being super confident when it’s wrong. So, you know, you are also in that area whereby if you don’t know your stuff and you’re relying on AI to tell you it. Well, we’ve had a catalogue of errors happen off the back of this. We’ve had a lawyer in the States put a case together with court cases that were all made up, and he didn’t check them and obviously he then went to court because he used ChatGPT to build his case. So, you know, we have this area where, of course, we are going to have people using it in that way. But the risk is obviously on one end, quite serious brand damage. And on the other end, it’s just that you will sound like everybody else, you know, you’re not driving the tools.

CJ: I guess the people are going to fall into that category are those have probably misunderstood it, just using it for speed benefit rather than what are we getting right quality. Are we getting the right material to take forward? I want talk customer service as this has come up a lot with AI. Good for customer service, bad for customer service? Does it have a certain role? What do you think, Tom? 


TH: Yeah, it has got a massive role in customer service, and we’ve seen the good in the bad of that already, right. So, there’s a great example of an AI customer service stroke sales tool that launched and the marketing for it was brilliant. Because the marketing was a video of somebody, it was just an audio clip, but it was made into a video. Somebody ringing up Tesla to book a test drive. And the marketing was, watch AI handle this customer inquiry amazingly, right? You listen to it, you think, okay, that’s that is really, really impressive. Well, the tool, somebody took it and tested it and they called people with it, and they looked at what it was like, and it was an absolute car crash, like, excuse the pun, to read. It was absolute a car crash, right? People asked it at one point, this sounds a bit weird – are you an AI? And they outright lied and told them no, it was a human.

CJ: Wow.

TH: It went off pace so many times and so, you know, again, we’re back to the point of a couple of things here. One is marketing demos are marketing demos for products. We know that. The gap to what reality is that there is always a gap. You need to know how big it is. And two AI is not right across the board for customer service, right. The Tesla example was a great one of if you were a car company or any company you spend millions, if not billions of pounds getting somebody to call you. Do not put an AI there, put a human being there who could talk to them. Right? There’s no way you use AI, use AI in the processing parts to get them there. But don’t put AI right at the point, you know where you could get insight, you need somebody to talk, somebody. So, I think we’re going to see massively forward in customer service and we’re going to see where this goes wrong. And this is all about being thoughtful and strategic and using it in the right area. You can totally optimise a lot of stuff, right? I don’t need to talk to somebody to find out the process or the status of my order, but if I’ve got something more complex, or if there’s an opportunity for me as a company to get real insight from my customers, don’t automate that. Right? We should be putting people in there and we should. We should be using the time we get back elsewhere to put more people into those areas.

CJ: It’s really interesting is that fear that’s prevalent in jobs being replaced. I mwan, remember back when it was machine to machine, M2M technology, I’m showing my age in the industry now. There was Vodafone, and the rise of the robots and everyone genuinely thought Terminator was going to live out in our everyday life. It’s probably become more prevalent today with the evolution of AI but using it to unlock the power of your people and then give them the really smart stuff and challenging stuff to be working on. That test, for example, is it just underlines why that’s what you should be doing with your people and how you’re using AI, right?

TH: Yeah.

CJ: Katy, I mean she’s so into data and she reads reports, and she pours over listening like nobody I’ve ever met in industry. She’s almost like the modern day John Motson of the sports world. He she is a proper statistician. She came up with a stat that says somewhere between 72% and 48% of B2B marketers say they’re using AI for content creation. Are you shocked by that, Tom? Or do you think that’s going to go up again? It’s too high. What are your thoughts?

TH: No, no, I’m not shocked by it because I think marketers in general and I, you know, put myself in this category. I’ve always had one foot in marketing, like, you know, we’re quick to jump on things, try stuff out, right? And what we’ve seen at G3NR8 working with clients. We’ve worked multiple different departments. We’ve worked with HR, we’ve worked with LMD, we’ve worked with tech teams and CTOs and CIOs. We’ve worked with marketing teams. The market is adopting this stuff far quicker than anybody else. They leap into it and we’ll try stuff out and they’re way ahead of other things, way, way ahead in general. So that doesn’t surprise me. What we’ve seen is that there’s a high individual adoption generally, particularly in marketing, but there’s quite high individual adoption. But there’s a much, much lower, organisational adoption today, a much lower joined up organisational adoption. And so, what we tend to see when we go into teams is, even companies, by the way, where they’ve got a directive that nobody can use AI. And we go in and we, we survey teams to, to get the lay of the land and find out what’s going on. We find huge numbers of people using AI in their own personal, accounts. So, it doesn’t surprise me. I think they tend to be the much more the trailblazers in that area and jump on things and test and iterate. So, but I think there’s a big lag elsewhere in organisations. It wouldn’t be that high, anywhere near that high. When you go across different job roles and different departments.

CJ: Really interesting question that was crafted for the B2B marketers who were using AI. Did do you think they’re trying to use it as a Swiss Army knife, being that solution to so many different things, almost like they’re their single tool for seven, eight, nine different jobs? Are we using it correctly? Does it need to be adaptation?

TH: I think. Yeah. I mean, yes and no. I think, you definitely got people use it for a lot of different things. Right? And an interesting is about what you see behind that is you see a mix where you’ve got some people who are adopting it quick, but they don’t want to tell anyone about it because, you know, there is a thought of horror. If I figured out these things and I can now do stuff or output stuff quicker and better, and other people don’t know I’m using it, this looks really good for me, right? And if I tell people I’m using AI new tools, will that take away from what I’m doing? So, there’s some interesting play going on behind that as well, from a, sort of psychological perspective. But yeah, I think you get a mix of people, you get some people that use it very narrow and some people that use it more broadly. You know, I think what it works really well is, it’s like it’s quite good broadly is your assistant through the day. You know, that’s where it’s particularly strong probably for a lot of us. You know a lot of people are listening. You’re diving in and out of ChatGPT every day checking things. You know, I’m in and out of it the whole time. I’m asking questions. I’m asking it to describe things in different ways for me so I can really understand it. Or I’m asking to shorten stuff I’ve written, or I’m asking it to extend stuff, or I’m going in and I’m trying to help it now find research for me, now that GPT 4 has internet access or I’m on perplexity trying to do some research. So, I’m dipping in and out of it. So, I’ve got broad usage helping me do my role day to day. What we see in businesses and across teams is where you get the real benefit is where you’ve homed in on a number of smaller use cases and double down on them to see big, big improvements. And so, there’s different things. So, I think in general, we’re quite far ahead in terms of personal usage, and organisations are lagging a bit in terms of the joined up nature and being able to use it effectively.

CJ: It’s been a couple of comments and for disclosure these have come from staff at immediate future. So, it’s lovely to know that they are watching this and not just leaving you and I chatting into. So, Anna who is one of our designers, really interesting absolutely agrees with what you were saying, that AI is a great tool for mood boards. And then Tom, who’s, one of our senior account directors, brands perhaps don’t have confidence in investing heavily in and for marketing. There is hesitancy, for sure. I’m guessing you would agree with that then, Tom, given what you’ve been saying.

TH: Yeah, I think so. I think there’s, you know, there’s a number of reasons as hesitancy in terms of, investing heavily. I think one is there’s a big knowledge gap today that exists. And, you know, trying to invest in something you, you really don’t have enough knowledge about is very difficult. So, and we see that out there in the, in the market. So, you know, there’s training that and education that needs to happen for that to catch up. There’s also just the evolution of the technology. Right? You know and we see this as well and we make sure that we not, you know, clients aren’t going down a route of investing heavily in an area that could be displaced by the next version of ChatGPT, right? So, you have to think about where you are putting your money in your time. However, saying that, there are a whole myriad of ways that you can use AI in your team. Everything that we’ve seen from, you know, larger creative teams where they’re working across brands, and they need access to the right brand guidelines and logo files and tone of voice and everything else quickly. One of the most asked questions in in larger creative teams is where’s the logo? Right? Well, you can start to solve some of these most of questions really easily by providing access through really simple interfaces to the right areas. And in marketing we’ve got a whole load of stuff we do every single week from analysing data to uploading assets to different platforms to resizing assets. And now we can start to build really interesting automation flows that, okay, maybe they don’t do 100% of what we’re doing in that area, but they take three, 4 or 5 steps away from the team of having to do that. And that really adds up over time. So, yeah, I mean, I think, I think the biggest lag is probably knowledge. And that will catch up over time. Obviously.

CJ: Do you think that there is a barrier at the moment around the ethics and the bias in AI? For the bigger enterprises out there are legal teams hesitant to sign off on it because of the unknown, that lack of knowledge. Or is this still a CXO problem? And know I have to caveat that. I’m all too often, whenever I’m doing interviews talking about digital transformation, I’m forever calling out CEO, saying you need to be closer to the CTO, and they must all hate me for saying it’s not personal, but is there a lack of knowledge at CXO level, that’s causing? The reason I asked that was a comment by Edward just now believing that it’s down to a lack of overarching strategy that comes from CXO, does it not?

TH: Yeah. Yeah. Well, I mean, this is a really good point because there is today a widely defined role that owns AI in businesses. Of course, we’ve had the discussions and semi rise of the Chief AI Officer, I would say and that has certainly some companies have brought on people in that role. But outside of that, we’re seeing in some cases marketing, leading the charge on it with sometimes seeing tech teams. So it might be the CTO, it might be a technical director lead the charge. Sometimes it’s the CEO who’s driving it. So, we haven’t got absolute clarity today on where they sit because it sits across different departments. Certainly, having an overarching strategy or at least a policy and a set of guidelines definitely helps. But, you know, in terms of the ethics stuff in your question, there are discussions around ethics for sure. I think the bigger questions have probably been more around IP and copyright in what we’ve seen with clients. So, you know, if we’re creating outputs, who owns them? What can we do with them. And so, you know, we’ve ended up guiding people through those conversations so they can understand the, the, you know, the IP copyright from a legal perspective. The ground is very varied at the moment. There’s a whole load of court cases that are happening, particularly around generative AI, because we’ve never had the scenario that we’ve had today with these tools. Right? When you think about what if we just take generative AI when I’m saying generative AI, what I mean is anything where you put a prompt in and it produces something out the other side, right? It generates something. Well, we’ve never really had these systems where we’re entering unique information in, in terms of a prompt. The model has been trained on data. A lot of these models have been trained on the internet. Right? Rightly or wrongly, they’ve gone off and just trained on as much information as they could get. And that’s all being unravelled. And then they’re creating an output which is new. And so, we haven’t had this scenario before. Right? And we’ve got IP and copyright at every one of those steps. What did you put in as a prompt? Do you own the IP copyright of that? Or did you copy someone else’s material and use it as a prompt? I don’t know, what was the model trained on and did it have the right to train on all that, that content? And then what is it produced and how close to another copyrighted material is that, and does it infringe it if it is close or whatever. So, you know, we’re seeing this play out right now. So, we found that sort of the IP copyright conversations have been more at the front of the table than, the ethics. But the ethics will become a much bigger part as companies start to build out their own models of their own data and then start to make decisions on that, that are sort of much more material in their business.

CJ: The IP areas is an angle that really interests me. I’m going to choose my words carefully because I was filming and presenting for one of our clients, and although the films out there, I was very much under the banner. We were talking about Microsoft Copilot as a case in point, and that’s been a million-pound deal where an organisation was up sourcing licenses for every one of their employees. So, I think the deal was about £15 million, big numbers. And I asked the question, are we going to see more organisations doing that? That seems a massive investment for it to be able to go mass market very quickly. And the point was made by, somebody who is very close to the technology company, that the reason they wanted that deal done was to get users putting information into it, because then the information could be scraped and serve back to other users, and it grew the benefit of the platform. So, until the IP ankle’s locked down, surely organisations are going to be looking at plagiarism concerns, disclosure concerns. Even how we source insight that we put into strategy, disclosing where it’s come from, whether it’s your own work will come from a rival. It seems to me that there is a lot still to solve on that front, Tom.

TH: Yeah, huge, huge amounts of that front is and knowing where stuff is coming from will be, will be really, really important. And even just in the wider aspect of tool usage. Right? If you’ve seen on LinkedIn only a couple of weeks ago, they changed their privacy policy and about a month ago they changed their privacy policy and they auto opted everybody in who was using LinkedIn in the UK to use their data to train their models. Now, now that they got surfaced and, you know, a lot of people, myself included with were talking about, how you then opt out of LinkedIn using your data, which you should have the choice. And shortly after that, you know, they came out and said, actually, we’re not going to use anybody’s data from the UK to train our models. Right? So, we’re seeing companies and brands like make missteps here or figure stuff out in the open. Why? Because data is fundamental to the future of any organisation in terms of being able to train their own AI models. And I’m not talking about an organisation or your organisation like building a competitor to ChatGPT. I’m talking about the fact that the future is going to be smaller, lightweight models that you finely tune with your own data and you run alongside your own data that give you unique insights that nobody else can get because they’re running alongside your proprietary information, and they’re much they’re going to be much more accurate because they’re going to be taking your information. However, at that point, we’re much more into the place of, well, how biased is your information? You know, and where are the gaps in it and what do you need to do with it? So, so it’s a really interesting area, but yeah, a longer term that the data play is critical because we’re running out of data out there to train these models on. They have literally trained themselves on the internet. And, you know, there’s a hilarious story of Google we’re going after open AI, in court for, for the fact that OpenAI apparently trained GPT 4 on a load of YouTube videos, Google obviously owns YouTube. So they were going hard after OpenAI, somebody then realised that Google had trained its own models on YouTube videos, and they hadn’t asked any of the creators, so they’d infringed their own contracts with creators and that just about sums up the state of play right now, which is, you know, all of these big companies have been attempting to get hold of every bit of information that they can to train models. Now, what with the last point of that, is that what’s happening now is what we’re seeing is these big companies doing licensing deals with owners of content. So OpenAI is on an absolute tear now, signing up deals left, right and centre. They’ve done a deal with the FT. They’ve done a deal with Vice. I mean, they’ve done hundreds of these deals now these content licensing deals where in exchange for a discount on using ChatGPT, they’re then able to use all of the content that company has to train their models. And we may be heading into an almost paid search AI future whereby the deals that they’ve done with these content providers mean that if you search for a bit of content, you’re more likely to find the FT article because they’ve done a deal with them than somebody else. And so they’re going to prioritise those people in terms of the information that they feed back. So very interesting space in terms of how it’s playing out.

CJ: It’s kind of more comments to pick up on a really interesting one from Kasim Javed. In the UK businesses are quite slow to catch up with the times. Will take 10 years before most SMEs start using AI. Agree with that, Tom?

TH: I don’t think it’ll be ten years, no. I think it will be sooner than that. I think, you know, there’s always a tipping point to these things where there’s hesitancy and then stuff happens really quickly. I mean, back in the day, I can remember stuff like responsive websites, load of load of resistance to like building a mobile responsive site. And then as soon as I think Google said you’ll be punished in the algorithm if you haven’t got one. Within a year everybody had one. So, I don’t think it’ll be five years, no. I think it’s getting easier, to implement. And, and I think actually in ten years, the companies that have made moves now we’ll, we’ll be a long way ahead because, you know, this is like, this is very similar to when the internet or digital started out. And, you know, it takes some time to upskill your teams, gain knowledge, run projects, do those things right? Tend not to hit a home run straight out the first time you got but so I think it’s not going to be ten years, no. But I think in five years the companies that have got on it are going to start to be moving ahead of the others. There’s a really interesting follow up comment, and I can see where consumers are going with this. For example, they hardly use videos and it’s been ten years since it became important. There is no argument to that.

TH: That’s a good point.

CJ: One of our mantras at immediate future is serious about social and breaking the social boring. If you are not using videos. I mean, frankly, I mean, it’s such a village move today, isn’t’ it? I think that says more about the leaders’s knowledge of, what makes good marketing and how you pull yourself closer to your customers. And I think I’ve been saying, the younger generation for decades, but every year that goes by the people moving up the ranks, they’ve grown up with video. They live with video every single day. And we got to see far more of it, far quicker. But it’s.

TH: Have we lost CJ? I can’t see him anymore.

CJ: You know what? You just hung up. I’m back.

TH: That’s good.

CJ: The one time Katy asked me to step in and run things. I genuinely said in a text to her before we started, this is my ego coming, sir. I’ll try not to copy that for you. And what have I done? Royally? I’ve lived the recording. I’ve now given all of my colleagues, reasons to take the mic out of me. Right? I want to pick up on some positives, because we’ve talked an awful lot about negatives and reasons to be fearful of AI. We haven’t answered the people, but I’m going to come back to that idea. So I think that is the killer question. Most people won’t answer it because they fear for their jobs. But let’s shift gears, talk positive. Some benefits, for a moment. Despite the challenges, AI offers significant advantages, especially when tailored to a business specific need. You’ve already made brilliant points on that, Tom. Is AI like the crystal ball that B2B marketers have been dreaming of? How do they turn predictive analytics into predictive success? There’s an answer that every business leader wants. Come on, Tom. Tell us, how do we all make more money from this?

TH: Well, I mean, there are a few ways where I could really help solve some of these problems, right? In B2B. Right? We’ve had, you know, if you think about B2B and the challenges right now that they’re of course, like all marketing teams, there’s budget constraints, there’s, you know, pressure to deliver more for less. There are, in some sense, I guess, longer and more complicated sales cycles. The goal for marketing for a long time has been, you know, this 1 to 1 personalised, you know, communication, right? How do we get down to that level of communication? And that hasn’t been possible really to this point in time? I mean, it’s been sort of heading down the wrong tree. Has it really been possible? But now, you know, there are ways that you can get a lot closer to that with AI. You know, and this again, is not from our perspective, trying to wage this into everything. But if you think particularly in the area of like large language models and what they good at. They are very good at understanding language and intent and conversation, right?  And so, what we do have is we have the ability now to take more information about a group of customers or a customer where they are and use that to write coms that are a much better fit for that particular target market or that person. Right? We do this ourselves in our business, right? We haven’t fully automated this, but when we’re doing outreach ourselves, we use large language models with we’ve got some code that we’ve written that look at a particular prospect, research the latest trends about the company right back into an email for us based on where they are in a funnel. And it doesn’t send it, but it stores it for us in our drawer’s folder so that we can review it. And as the models are getting better, they’re getting more and more, you know, capable of writing these emails that are fantastic. Right? I spend 20 minutes writing my own email to somebody the other day. You know what I got back? The first line was, did you write this with AI? And I was like, I didn’t write with AI, but I might as well have done because you just thought I have straight off the bat. So, I think the ability to get down to this level of this level of comms that understands context and understands where somebody is and is able to carry on that conversation and get you to the point of then interacting with a person or breaking out of that cycle is absolutely brilliant. And if we go back to the Tesla example, like where would you use it there as a car company? What if somebody emails or somebody fills in a form on your website and is interested about, you know, having, or inquiring about a car, you could easily send them an email using AI to get some more information from them. You could maybe have two back and forths with them and get to the point of understanding what sort of slot they wanted, and then hand it off to a human right? That would absolutely work. So, I think, yeah, there’s some really, really interesting areas. And then the analysis of data and the ability to turn that analysis into action is the other really, really interesting area because, you know, we’ve all we’ve probably all run research. We’ve all had big reports. They’ve all then sat in a drawer with some half eaten polar mints for six months. And then, you know, a creative director has or an agency has done what they think is right rather than what we’ve actually got anything from the insight. Right? Because it’s quite hard to tie that up. Whereas now that, you know, as we call it, the so what chasm, you can cross that really easily and you can take insight into ideation, straight into mood boards, straight into creative that somebody can then build upon. So really good areas.

CJ: It’s interesting you hear about the lead generation, so obviously for anyone to modern generation is a slog, particularly in today’s market. Anyone that’s been doing it this year, you know how tough it is. You’ve been working damn hard to actually get your leads landed. Do you think it will ever be able to deliver the personalisation at scale, or is it wrong to even ask that that question? I say that because we’ve come through personalisation, ABM focuses on industry across the last five, ten years. Should we be using it for tailoring one on one comms with key prospects, or will it have the ability to improve personalisation on scale?

TH: No, this is it. This has got the ability to do it on scale. This is the air we’re going into. It will be able to have a conversation with every single one of your prospects. It will be different. Now the key question is where does this fit in our process of dealing with prospects and where is it right to do that? And where do we need to break out of that? You know, and back to like the Tesla example, if someone rings up, don’t feed them AI to try and handle that conversation. Talk to a person. But if they’re emailing about a test drive, you absolutely can. You can handle that conversation, and you can be hooked into your own back end booking system to know slots. And you could get to 2 or 3 emails prepped to give it to somebody, which would have saved them an hour’s worth of time to then finalise that. Absolutely. You know, look, we know this and is it there today to be able to do that? I mean, it’s quite complicated to do that today. It takes quite a lot of work. Will it be there? Absolutely. We’ve already got research that came out where they tested large language models at GP practices dealing with text message, conversations with patients. And as you can imagine, the GPs are extremely busy and, you know, don’t tend to sit there asking, you know, lots of nice questions or maybe the sort of the nicer conversational stuff around the edges, whereas a large language model just does that automatically. Or you could, you can set it up and prompt it to be to operate in a certain tone. And what happen? Patients rated the AI is more empathetic than the doctors. So, you know and again at that initial triage bit of or even just a bit of settling someone in and feeling heard and feeling like, oh, this person, you know, this somebody cares about what’s going on here. Brilliant job. Now would you then prescribe drugs off the back of it using an AI? No, of course you would. You would hand it off to a GP and that’s the same thing in our businesses, it’s like which area is it good for and how do we take those small steps into them. Because the future definitely will be personalised conversations with every single one of your prospects. You know, at some point and what that looks like, who knows. But you’ve got to take those first steps to get there.

CJ: Before I come on to the final question, I’m just going to pick up on some comments. It’s a really interesting debate going on LinkedIn, right now. So, Jason: “Much like VR (Virtual Reality), Occulus 3D TV etc it is going to take many iterations before AI has solid Use Cases in most businesses”. A response from Edgewood: “I’m not sure this is a case. VR, and the examples you referenced come along with the pain of physical hardware needs. AI doesn’t have that hangover. We tend to focus on the creative side of AI, but don’t realise many industries have a layer of already baked in via process automation.” And then Kasim: “Generally AI is completely under-estimated. I don’t think unless one has really consumed themselves and experienced ChatGPT and how powerful it is they just won’t know it. List building, research, quick data, it’s unbelievable.” Well, I’ve got colleagues that would agree with that. And then Terry Donovan: “Perhaps AI will force companies to think more about how they present themselves uniquely and without the jargon, in order not to sound like they’ve generated content with AI!? Every cloud!!” Well, Terry, if that happens, I’d be delighted, because one of the things I’m forever bemoaning of brands is, why do you take the company brochure and then make social media content out of it is absolutely the worst source. The total wrong, isn’t it? So, hopefully I’m hopefully there’s more positive. So, there are plenty of comments on LinkedIn that we’re not going to get a chance to, to call out. So but I would encourage anyone who’s watching this on, on any of the other platforms, like Facebook, YouTube, go and take a look at the comments on LinkedIn. Tom, before I let you go, I want to talk about the financial side. Is AI worth the price tag or is it just a luxury toy for marketers? How do you justify the investment with your CFO, for example? And let’s be honest, CFOs right now, you’ve really got to twist arms to get any form of investment. It’s a tough market out there. Can we justify the investment?

TH: I think you have to justify the investment in the beginning, but it doesn’t have to be like billions of pounds right off the bat. This is the thing, right? This is, I think, the mindset which is, you know, if you knew what you knew back when the internet started, you wouldn’t have set out to build a website as a company. Right? That was the goal of most companies build a website and most companies treated it like a magazine. We’ve done that. We’ve kicked it off. We don’t need to come back for it, you know, for three years, right? If you knew what you knew now, what you would have said was what we need to do is educate ourselves, is learn about this technology and figure out how we, as a business and as a team, incorporate it into the way we work every single month, every single year. Right? That’s that would be the approach. And you would have gone a lot quicker, a lot further with that approach. And that’s the same today, right? The same today is happening with AI. You absolutely need to make strides into it. But what is it? Well, it’s education is the first port of call. It’s getting people up to a certain level, and it’s reducing the fear in teams because as you alluded to, people are scared of losing their jobs. People are scared of being found out that they’re using AI as well. So, you’ve got you’ve got a level set and reduce that fear. And then the speed at which the tools are evolving that mean you can either build new ways of working, you can automate elements of your team in your role, and you don’t have to have in-depth coding knowledge to do all this stuff. Right. There’s no code options out there as well. So there’s you can jump in a little bit or you can start to build out, you know, wider use cases. It’s incredible. But you need to start taking steps on that journey now. And so, you know, as somebody alluded to, in terms of the questions earlier, getting aligned, great, great shout, having a policy, being aligned, having an overarching direction, at least getting teams trained and up to a certain level – brilliant. And then what you want to be doing is you want to be in your departments and your teams, starting to figure out where are the high opportunity areas that aren’t insanely complicated that we could start with. What do we do every single week again and again and again? Well, we’ve got to take that video, and we’ve got, we have to chop it up into 19 different parts and upload it to four different platforms. You can build automation flows that start to do some of this for you, right? Whatever it is, you can start to figure these things out yourself. Or of course, you can come to the other people who are working in the field who help you do that. But that’s the beginnings of it. So, I think, you know, one part of AI is harder to justify, which is a longer-term investment stuff. There is another part which is really easy because if you save your team X number of hours every day or every week, there’s a monetary value to that, right? So, the ROI is pretty easy to work out on those things. So, I think yeah, I think it’s much more the case now that you can’t stick your head in the sand and, you know, think we’ll get to it in five years because it’s just it’s moving too quick and you’ve got to get in there now and it’s going to be part of whatever future you’re in. And so the more you know about it, the better.

CJ:  You reminded me. I do want to ask you to killer question. There would be lots of people watching this, lots of marketers who are all possibly thinking the same thing. Is AI going to take my job? Short answer, are they safe, fearful?

TH: Are any of us safe? You know, what does the future hold, CJ? I don’t know. Like, whether the AI going to kill us all? I don’t know, I do not know. These are big questions. Long term. What do I think long term? The job market, the world of work is going to be significantly transformed. Will AI take your job over the next couple of years? Probably not. What will put you in a better position – if you use it and you know more about it, right? So, I think, you know, it’s back to leaning in long term. Who knows? You know, I could make up some crazy stuff about what might happen into the future. But, I think short term, like, over the coming years, I mean, it’s what we know now is somebody who’s really good at their job, who uses the right tools, can do a lot more than somebody who’s really good at their job, who doesn’t use the tools. That’s it. That’s what we know right now. So, my advice is lean into it, learn figure stuff out, get good help. And, you’re much more likely to be safe, not guaranteeing you’ll have a job, but you much more likely to have a job.

CJ: Tom Head, ladies and gentlemen, co-founder of G3NR8. Go and check them out. Tom, thanks so much for coming on. I absolutely owe you lunch for coming and doing that. I think this is going to be a really popular debate. So, thank you so much. Appreciate that.

TH: Thank you for having me. Was awesome to be on, CJ. And yeah, I will jump into the LinkedIn comments to see what’s going on.

CJ: Good man.