The AI strategy gap: Why 40% of marketers don’t expect ROI before 2030

For the first time in many years, this is a new technology that's coming into the market where younger people trust it less than older people. And I think from a marketing perspective and we've all been in the industry long enough that you know there was there was the web and then there was mobile and apps and social, there's a new thing that comes along and the whole industry races to embrace it as quickly as possible. normally because younger consumers and future consumers are crying out for brands that are active on mobile or vertical video or whatever it is. That doesn't seem to be the case right now where in fact younger consumers are pretty skeptical about brands who are visibly using AI. [music] Welcome to the CIM Marketing Podcast. This is the first in a two-part series examining CIM's latest research on marketing in the age of AI with none other than Yugov. And I'm delighted to say that from Yugov itself, we have none other than Miss Gemma Connor and join an associate director in the political and social research team at Yuggov. Um, and she's mainly responsible actually at the pollster for panuropean polling, but she also leads on Welsh polling. And I have to say in the recent Welsh uh elections, the Senate election, um she was the most accurate of all pollsters. Gemma, great to have you on the show. How are you? >> Hi, I'm very well, thank you. Thank you for having me. >> It's great to have you on the show. Great to have you on the show. And the great hot guests do not end there because we also have with us today Mr. Jamie Kredland. Now Jamie, many of you will know he is of course chief executive of the World Media Group. Uh before that he spent 15 years as a marketer at the economist and before that was agency side at UN. Jamie, great to have you. >> Great to be here. Thanks Ben for having me. >> Fantastic having you on the show. And last but not least, many of you will know Mr. James Bells. Now James is head of PR and external affairs at the Chartered Institute of Marketing. He's of course a chartered marketer himself and a CIN fellow. He brings more than 20 years of experience leading agency and in-house marketing teams, but most of all, he's back on the show after what is a prolonged absence. Mr. Dell, we we're trying to count up the years, but it's great to have you back. I'm going to ask you, James, um, you know, AI has transformed the marketing landscape. We know we're all using it. Why did you do this research now? Why launch this report at this moment? just felt the perfect moment Ben because marketers have kind of moved from experimentation to widespread deployments. We're not as clear man promps more AI is now hardwired into marketing teams. Um but that acceleration has really created um a real ordinary paradox. Balls everywhere are looking at Gen AI through quite a narrow lens at the moment cost reduction um margin improvement and in some case real headcount decision. So it just seemed the perfect time to look at some of really big issues, drill down as the data with UDA and to come and really provide marketers with a kind of where we are now and where they want to go in the future. >> Joe, cost reduction and headcount reduction and not phrases that generally meet well with the ears of marketers. Um, can you tell what you found in your research on those issues particularly? >> Yeah, so overall AI is being used for a variety of purposes by marketing decision makers. If we look at the sample of that group, around a quarter are using AI to improve operational efficiency on the non-creative side with similar proportions using AI to take a closer look at their competitors and track market trends. Around a fifth are using it for price optimization. However, when we look at how AI is being used and actually the extent to which it's being used to achieve their ROI, it does seem to depend on the size of the organization. Large companies with more than 250 employees are far more likely to be using AI to achieve their return of investment than smaller companies. Uh for example, 53% of marketing decision makers working for larger companies say they're using AI for price optimization compared to just 15% of those who are working for a smaller or medium size enterprise. >> That's interesting. Um what else in there did you find that you think is a big headline finding in terms of the usage of AI in the sector? >> Um it's interesting how many businesses do not expect to achieve any return of investment from using AI before 2030. It's 40% of marketing decision makers are saying that that's not going to happen. >> 40% are going to use this before 2030 or they're not going to expect a return since 2030. >> Absolutely. And that increases massively when we look at smaller companies. So 52% of micro companies or small companies, those with less than 50 employees. So they're not expecting that return on their investment. And 47% of small and medium enterprises. Whereas large companies, those with 250 employees or more, and just 1% are saying they're not expecting to see that return. So there's a real difference depending on the size of the firm. >> Real difference, James. Um big findings there that the size of the firm is making a massive difference in terms of the expectations ROI. Uh and indeed the size of the firm also seems to make a big difference in terms of what they're using it for. These dread phrases cost reduction, these dread phrases of headcount reduction. You've done a series of roundts on this very matter. You met organizations, you've met senior marketeers. Um what were their reactions to these findings? >> Yeah, it's quite interesting. So we obviously did the research with Jeremy's team and we really wanted to stress test it to basically take it out and find out what people ordering but what way people in the front line what they actually felt of the findings. So we held two roundts with IBM in the renovation center in central London. Um they were attended by between about 30 and 40 market professionals. Everything from seniors TMOs at global banks all the way down to IBM's AI team sim course directors to give an academic view. We had young interns in there and then we had senior marketers kind of operating on the front lines and you could just see people's how the energy changed in the room when we put the figures up on the screen and we discussed them as a team. We laid all the figures out with everyone to really dig into them and there's a real consensus that AI is splitting marketing into sort of two distinct operation. Front office. >> Yeah. >> So the back office everyone was really positive. Great. It's going to take away all my effort around my mix modeling my automation of internal reports or my data sets and they really positive. You could physically see people's faces light up when they could see that the cobs woring and I'm going to clear all this rubbish off my plate. And then when we moved it to the front office and started talking about things like customerf facing copy, creative execution, brand storytelling, you could just see the room got a bit quieter and then people were distinctly more cautious and we try and conversation about things like guidance and legal and how we would do it. So I think a lot of people when they looked it through could see the massive benefits but also they could see some of the kind of the warnings such as like 63% of adult lose trust in a brand when they see poor AI content. So a lot of them saw as a really big wakeup call. It's not the big silver bullet where they can just load a whole bunch of content into it drive productivity and output. actually they need to make sure it's really of high quality otherwise people now are getting some step towards that and are particularly looking at some of those content and going you know what I'm going to step away from that brand because I don't think they value me or the content they're putting out isn't good so there is a bit of a trap there we need to watch out for so they were the kind of things that came out it's really interesting how it really quickly split two sections how it was going to be used completely changed people's physical response to the data >> it's absolutely fascinating Jamie you've been nodding furiously during James's testimony. Um, the pace of change has been incredibly rapid and you probably spent most of your time at CAN this year discussing that pace of change. Are we adapting to this stuff properly? >> I think I mean it's the perfect time to be talking about this report. I think as you say I was at Cam Lions last week um and WMG World Media Group. uh we spend a lot of time dealing with advertisers who tend to be at the larger corporate advertisers, the larger B2B kind of brands and um there is there across the whole festival of and conference in can there was a real noticeable shift this time 12 months ago there was unbridled optimism about AI that every single every single process and uh skill within the marketers toolbox was going to be replaced and you know in in fairness in the last 12 months marketers really have embraced this. I didn't you don't meet any marketers who aren't using AI in some way within their workflow. um many people have been encouraging their teams to adopt it and you know people are very excited about this technology but I think perhaps there's also a little bit more realism kicking in about which tasks AI is really fantastic at as James says some of those back office tasks um and which tasks AI might have some value to but it's not a replacement for human oversight the more front office pieces and I think this additional thing which is you know is highlighted in the report but it really is coming out many many places in many different categories and industries can this piece around trust and the truth is that what you do in the back office um I think often consumers are not potentially that interested in how you're doing your media mix modeling that that's fine um but as soon as you're putting something in front of a consumer that is obviously AI generated or touched by AI I think you know either you have to be transparent with the consumer or there's a real risk to trust um if it's not clearly labeled and the other piece around that which I think is also in this report but for the first time in many years this is a new technology that's coming into the market where younger people trust it less than older people and I think from a marketing perspective and we've all been in the industry long enough that you know there was there was the web and then there was mobile and apps and social there's a new thing that comes along and the whole industry races to embrace it as quickly as possible normally because younger consumers and future consumers are crying out for brands that are active on mobile or vertical video or whatever it is. That doesn't seem to be the case right now where in fact younger consumers are pretty skeptical about brands who are visibly using AI. So I there's a lot of enthusiasm um but there's also a certain amount of healthy skepticism I think which wasn't there previously. It's interesting you rais that said about the generational aspect of skepticism because I was reading this report last night. I was looking to get a hold of a embargoed copy from CIM pre-publication embargo embargoed copy locked down version and that was the thing that jumped out to me that the younger generation if you like the Gen Zoomers um were the most skeptical of uh uh of all of the generations of this stuff and were almost sort of you got the impression that they were sort of almost looking out for AI Gemma and if they could spot it would then walk away from the brand. Yeah, this group is actually really interesting because in polling we tend to see that the youngest age group, so in this case the 18 to 24 year olds, are normally most likely to say they don't know about something. And actually in this polling, they're the least likely to say that and they have very strongly held views about AI and how the use of AI in advertising and marketing really impacts their trust and their view of the brand. So across the whole nationally and politically representative sample of 2,000 adults in Britain, 63% felt that they would lose trust in a company that was using AI generated content. That number increases to 79% amongst 18 to 24 year olds and which I think is surprising. I think people kind of grow up in that digital age and we kind of expect them to be the most savvy with AI and to be perhaps most on board with it. Actually, eight in 10 of this group say they'd lose trust in a firm which is just a really interesting finding. When I read this report yesterday evening, I sat there with a cup of tea and I thought there's an element that there's an under there's an undertone here, a little bit of a bandwagon jump by this industry, probably by other industries getting on this train before we've got the right drivers. Getting on the train before we've got safety measures in place. Almost like the technology, the train is getting ahead of the people it's supposed to be carrying. Is that fair analogy do you think? >> I think that's probably the case in some different ways. And like I say, I think previously the message from senior marketers to their team because there was some concern about AI use within marketing. A lot of senior marketers were just saying to their team, I don't care how you use it. Just make sure you're using get on that get on chat GPT every day. I want you to be using it for everything. And that's a completely reasonable response because you want to develop these skills within your team and get people comfortable with it. I think that's very sensible. I was talking to um a couple of people at large professional services uh firms uh over the last couple of weeks with global operations who have been taking that kind of approach and have now suddenly realized they have teams in Europe and teams in the US building things that are completely duplicative. Right? they're completely wasting energy because everybody is doing all this stuff on their own and there hasn't been a central uh organized process of okay these are the projects we're going to use AI to deliver and these are the teams that are going to work on those specific tasks. This comes out in the research report as well, but we're talking about a technology. This technology isn't going to replace the need for a marketing leader to structure a team, set clear objectives, set priorities. And at the moment, you know, it's great fun. Everyone's gone off and built all kinds of widgets and bots and who knows what what else. Um, but especially if you're a larger organization with thousands of people, you need to at some point make sure everyone's on the same systems and summing from the same hint sheet. It's interesting, Gemma, that that that leads me to this other thing that I spotted yesterday when I was reading the report that there seems to be a large discrepancy between those who are expecting return on their investment versus how many of them have actually got a strategy in place. You know, you could almost call it a strategy gap, couldn't you, from by looking at the research. >> Yeah, absolutely. So, as we were saying earlier, there's 40% who say they're not expecting to achieve any return on their investment from using AI in the certainly in the next few years. Um, however, among the same group of marketing decision makers, almost half are saying that their company's not developed a formal strategy to address the new skills that are needed to use AI. So maybe that's why they're not going to see that return. they've not made that investment in the right areas of the business to understand actually how AI can lead to a return in investment. It is a much bigger problem again for smaller businesses and just 4% of decision makers at large companies say they don't have a strategy in place yet amongst ummemes it's 55% and 60% of those working for micro or small companies say they just don't have that policy in yet >> James another trap isn't it? Yes, basically. And it was something that came out loud loud and clear on when we talk to all these sex. I mean, you've probably heard that, you know, JP Morgan are spending more tokens than they spend on salaries. You know, Uber exhausted their entire AI coding budget by April. You know, Microsoft have basically revoked all their claw code licenses because of spiring costs. It goes back to Jamie and Gemma's point is that there isn't the the AI skill strategy in place in lots of firms and it may they may well have an overarching one but what's that mean for department level what's that mean for marketing and so there's that came through an awful lot is that you could say we are sleepwalking into an issue at the moment and it's the gap between approving an budget and actually driving AI strategy that's where the issue is having as Gemma said like 47% of decision makers and new bought said they had no formal AI skill strategy in place. Everyone's chasing an immediate return and sometimes they're restructuring roles without reskilling people and the bottom line it hits twice. It hits um first where's commercial risk and then there's the AI trust penalty which Jamie talked about earlier. If we automate everything using AI then the entry level roles are reduced that that's basically where the staff seem to be getting cut from. But then it's really where's the next generation marters going to come? How are we going to learn their trade to then move up the level and how are they going to develop that that you know the judgment when the AI telling them stuff that that's not actually correct and if we cut the bottom of the pipeline then the bottom line suffers just you know two or three years down the line. So I think we you could say we're sleepwalking into it. I would also say that you know this does sound very negative but this technology wasn't around 10 years ago. So everyone's kind of scrambling and upskill and employing it and there is some really good stuff that brands are doing. Yeah, >> it's just a watch point. We need to make sure we empower the staff, give them these new ways of working in a bit of a controlled safe environment but with the guidelines in place >> because otherwise back to Gemma's point is you know without central strategy we are going to waste AI resource. But on the point of the strategy gap which I think is a real worry, there's actually a quote in the report itself from Sam Winston of Salesforce. I'll read it out. was quite an interesting quote I thought which says the real strategy gap isn't about tools but it's about AI fluency the ability to embed agents or AI agents into a team's culture to reclaim the time to create and focus on high impact human judgment and innovation talked about the pipeline but what does this AI through marketing look like to you James >> well I think it's probably the antidote to the problem I just discussed if you can build a AI fluent team. It's going to look less like a factory assembly unit where everyone's been bits and more like as a former newsroom where AI is running around acting as like junior researcher shifting data spotting trends handling programmatic buying sending stuff back to you sending drafts back to you and then the humans don't step back they step up into the editor kind of role at the very top and then they can use machine intelligence to the back office stuff and give themselves time to create and that really kind products the value I think of humans in the AI process but you've got to ship that kind of that cultural internally as well because you can create infinite amount of AI content cheaply but it's the human creativity that gives you the USP >> so I think that building those AI fluent teams is going to be difficult but that could be the way forward where we really see the real benefit of these AI tools >> some AI tools are being used more prevalently than others. There's some nuggets in the researchers on the Gemma about what the industry what tools the industry is using. >> So mainly people are using the backroom stuff, the things that we've been talking about the operational efficiency um the the tracking what's going on in the market um and also the price optimization. But how it's being used does depend on the size of the company. Uh those larger companies are more likely to be using it for price optimization or yield management. and they're also more likely to be using it to to make their operations more efficient. And those smaller companies are much more likely to have not not really worked this out yet. It's the larger companies that are really leading the way in terms of using AI in their background um workings. >> It's interesting, isn't it Jamie, that price optimization for the bigger firms, these are the firms with the 250 plus employees is the most popular use. not a fairly close second is the operational efficiency. think that the marketing industry historically loves an easy to measure metric and then tends to not worry too much about whether that's the right metric to be measuring in the first place and and we've seen this happen in the world of online advertising with you know clicks and impressions become totally meaningless metrics but the entire industry obsesses about I think likewise you know AI it's a wonderful tool I don't want to sound like I'm not in favor of using it across the business but if the only metric is cutting your costs I mean the the absolute best way to cut your cost is don't do anything at all and that um that's guaranteed to work. Uh so a you know you you lose a lot of the creativity and the the specialness of what makes marketing. The other thing though is I heard this new expression last night from um someone at PWC of tokconomics, you know, the economics of tokens. But I think as James was getting at, um I met some people last week who had uh reduced their team of web developers uh by I think 10 to 15 uh people because of supposed uh AI cost savings and were now spending more on tokens than they were on the staff. You know, it seems like it's a really quick win to just get rid of junior staff. And as James already said, there is a question that raises for the pipeline for future talent, which is really important. But also on a just purely financial basis, it's not obvious actually how much these AI tools are going to cost. And also, however much your tokens cost today is probably the cheapest they're ever going to be because as marketers build these relationships with two, three, four major LLMs, right? And that, you know, there's not that many players in the market. We've seen it before. You know, think about Microsoft in the 90s. You know, once we were all on Microsoft Office, no one was leaving it. And there is a point if you build your entire business around systems that are delivered through claudic understandably say we're going to increase the token cost by 10%. Your business has very little negotiating power whereas having people within your own team you can always move around the tasks that they're doing. You can always you know scale them up and down. You have a lot more control as a marketer. So I think it's interesting you know there are absolutely tasks and I think you know pricing analysis very heavy data pieces. Um this is exactly what AI is designed for. I think some of the junior tasks are perhaps not as much of a cost saving as people think. And then finally I think we we shouldn't forget what AI is which is you know it's a really really fantastic tool to predict the next word in a sentence. By its nature it regresses to the mean. that that is literally what it's designed to do and that's fantastic for for many many things. But if you are looking for, you know, creating a tone of voice for your brand that is provocative and different from everything else in the market or you're looking for a creative idea, not I don't just mean in terms of a 30-cond TV ad, but in terms of a creative idea for your strategy, there's a real need for humans in that process. And just to I think James was right, his newsroom analogy I think is really interesting. So at WMG we our partners are many of the world's largest most trusted news organizations. So we have Wall Street Journal and the Washington Post etc. All of them are using AI in the newsroom that all of them are crunching data with with AI. They're all doing a lot of analysis with AI. None of them are replacing journalists with AI because you still need a human touch to work out, huh, what is it about this story that's really interesting? What's the angle here that's going to resonate with my reader? what's the next question I want to ask to take this story further and I actually think taking that that attitude or that approach in the marketing room uh like a newsroom is kind of an interesting metaphor I think that works quite well >> I thought I thought that was a great metaphor it appears in the reports as well and I thought it was an outstanding uh analogy but there's a risk there there's a risk there go too far and we get this similarity you know this this this uh the thing that we're looking for as brands as marketers is differentation. We're losing that very thing uh that we uh seek. And Gemma, in the reports itself, there's some interesting nuggets about that, is it? The risks that companies perceive to going too far with this technology. >> Yes. So AI is something that people pretty universally are wary of and there is a wealth of Hugo polling data to evidence that from the last few years. It's something we've been really focused on. But for this particular project for marketing decision makers as a whole after data privacy and kind of beyond that initial issue the biggest dilemma that people say they've experienced or they expect to experience in the future is AI producing inaccurate or misleading data. That concern is fairly uniform across the sample regardless of company size with around a quarter saying that this is the biggest risk facing them. However, if we dig into that data a little bit further, there is a slightly different story. So if we start to look at responses by the size of the respondent's company, um while inaccurate data is the biggest concern for those working at small and medium-siz companies, those working for larger companies are more likely to be concerned about marketing becoming too similar across brands with the use of AI with 35% of that group saying that this is the biggest risk they exper they have experienced or they anticipate facing in the future. Well, corporate risk, James delves, managing corporate risk. There's a tension in the market, isn't there, between the desire to accelerate with this technology and actually manage the risk of using it, spend all this time with the IBM Ryan tables. Um, how do we balance it? How do we balance the freedom to innovate with managing risk? >> And it's a big thing which everyone is basically slowly come to terms with and trying to work out what it means to them. The thing you need to really consider is how do you manage the risk without killing your team's pace. >> So one of the big takeaways from the IBM round table was that innovation without government isn't agility, it's liability. And it's not only a real challenge for big multinational teams either. leaner small theme teams stand to gain hugely by not going with the big LMM brands but picking smaller task specific AI models that give them tight control they lower the risk they close alignment to the brand's voice um and by focusing on picking the actual AI tool that actually meets their needs rather than just the big shiny one that may work much better for that kind of mediumsiz to small enterprise but leaders need to be really clear and need to have a frameworks in place that protect their IP, secure the data privacy while still giving their teams the kind of sandbox to play in to experiment safely to work out how these tools work. But going back to Jamie's point earlier is that you know 69% of consumers hold the brands entirely accountable for AI errors. 33% blame the AI software providers if there was an issue. So basically the burden is on us is on marketers. So we need to use transparency like a core signal. It's not about ethic. It's about almost a commercial necessity. So it's really putting those guard rails in place getting that governance really tight and then letting people still be creative and still have the time to play with the stuff but do it in a way where it's not going to cause you know government issues etc. And I think that's easy to do in a small organization, but it's going to be really really key going forward. And I know a lot of organizations are trying to work out how they do that and it's going to be a an an ongoing challenge. >> Gemma, is there much evidence is there any evidence that consumers trust this stuff much at all? >> Not really. No. Um, so we've done lots of polling on AI in in various industries at Yugov as part of our commitment to public data. Um, and people are very wary of it, not just in the UK, but with my my European hat on, it's it's a real issue beyond the UK borders as well. People are very very cautious about how it should be used. Um, in terms of how it's used in in work and in across different industries, there's the line seems to be kind of decision making and when ethics come into it. So they're quite happy for AI to be used for administrative tasks to speed up processes um to kind of take the faf out of your day-to-day life at work. Um but the when it comes to actually making decisions um and something that might actually impact people's lives then they want a human to step in. So in uh 2023 we did a white paper about AI across um education, police um and or the the judicial system um and uh medicine and people were very clear that it was fine for kind of AI to be used to book GP appointments but they wanted to see a doctor. Um juries should be people rather than AI. Um there's a real limit to what what people are willing to put up with in terms of what AI is used for. And we see this in the CIM polling as well. Um people hold the the brand responsible if there's a an error or harmful content in AI generated advertising. It's the brand that that is responsible rather than the developer. um seven in 10 say that it's the brand that that should hold responsibility for that mistake. Um compared to just a third saying that it's the the AI developer. Um and there's a real clear view from the public that this is not um regulated enough and particularly um through the CIM lens. AIdriven advertising should be more tightly regulated is very clear coming through this polling. 73% say the regulation currently isn't enough and that's in line with other use of polling. The public want to see regulation over AI innovation. >> We'll dig into the regulation aspect a little bit little bit later. Um what about personal data? We love a bit of consumer data, personal data, don't we Gemma in marketing people happy to give this stuff over to robots? >> Absolutely not. No. uh 78% say that they're uncomfortable with AI using their personal data. So this is a really quite an overwhelming finding in polling terms. Um again the younger people are not particularly pleased about this. Um 80% of that group the older generations are really really uncomfortable with this. The over 65s 88% of that group say they're uncomfortable with AI having access to and using their personal data. This is not something that people are willing to to give up and they they want humans involved in that aspect. >> Finally, we found something to unite the boomers and the zoo. It's taken a while, but we found something, Jamie. Um, how are we going to deliver personalized experiences when neither Boomer nor Zoomer and probably most other generations don't like giving our robots the data? >> I I think it's a it's a really core issue for advertisers in general and it hasn't AI has massively accelerated this issue, but I don't think it's a new issue, right? We've all had um a brand use our data in what feels like a slightly creepy way when you get an email that you know references some piece of your personal information that you didn't expect it to or something like that. So from a marketing perspective, you know, and I understand I absolutely understand those consumers being very concerned about AI using their data, but I think for a marketer, the rules are kind of the same as they always have been, which is one, be as open and transparent as you possibly can be with your customers about how you're using their data, what you're trying to do, what data you're gathering. Don't gather data that you, you know, don't need for just because you can do it doesn't mean you should do it. And if you are going to use that data, use it in a way that actually delivers some value for the customer, not for you as an organization. So, you know, when you go to the supermarket and you get a text on your phone on your way in saying, "Oh, by the way, you always buy this bag of crisps. We're going to give you 10% off that bag of crisps." Lovely. I will I will happily take your 10% off that bag of crisps. when you get a slightly creepy message when you're not not thinking about the supermarket at all saying we know that you've spent xund quid on Christmas in the last year and by the way here's some diet bills for you that's not a good feeling it feels awful and I'm you know from marketing perspective it might make perfect sense but from a customer perspective it's lousy um and I so I I think that is probably been true for a while the other thing that um I see as an opportunity area actually is this whole piece around contextual advertising certainly online on the where you know contextual basically just means you're choosing to place your ads on pages that are relevant for an audience. So you don't need to do complicated things with cookies and demographics of who that audience is. But if I'm reading a website which is the top 10 new loudspeakers for your living room or something and you want to advertise a loudspeaker, that's a perfect place to do it. And AI is enabling advertisers to do that in much much faster ways than they were before in terms of understanding the content on the page and what messages might be relevant for that page. So it's still targeting. It's still delivering marketing efficiencies, but it's not creepy as a user. you're like, "Oh, this is a brand who has found the right moment to talk to me. This is adding value to my experience. Lovely. I'll go and find out more about that brand." And so that, you know, that's using AI, but not in a way that I think the consumers are worried about when they're answering that question. I think when they're answering that question of I don't want AI, um, using my data. They're talking about AI using their personal data. Um, which I completely understand. I think there's ways that marketers can embed AI in the process that gives them gives a personalized experience without being invasive. >> Some might say that better regulation might be the answer. Um, you've touched on it earlier, Gemma, do you want to run us through what you found about attitudes to regulation in marketing these AI in the research? >> Yes. So given we've discussed such high levels of distrust and discomfort with AI, it's probably no surprise that the public find the current approach to regulating AI generated content lackluster. Um just 7% say that the current amount of regulation is correct. Um compared to 73% who think it should be more tightly regulated. Um as before, 18 to 24 year olds feel more strongly about this than other groups with 80% at least age group saying more regulation is needed. >> It's interesting, isn't it? I just put the graphs here and I scribbled Z MX and B on there for Zoomer Millennial Gen X and Boomer and again it's another one where the youngest Zoomers and the boomers are most pro- regulation. So again it's something else that this nervousness about the technology does seem to be something that unites those two generations probably for different reasons that I think that's what's interesting. It's they're they're driven by that that reasoning behind that opinion is coming from completely different places. I think that the older generation is a real fear of the data but not necessarily haven't been exposed to it that much. Um and that's maybe where the fear is coming from but then the younger groups it's they have been exposed to it and they don't like what they see. >> Interesting. Interesting. Um do we think Jamie that regulation is keeping up with innovation? No, that I think I think that's that's the easiest question of the afternoon. Uh, fantastic. I I think when we talk about AI regulation, it's >> Yeah, for the purpose of this conversation, I think part of what we're talking about is is labeling on ad creatives that have had AI involved or, you know, those kind of directly consumerf facing marketing executions. But, you know, for the members of WMG, there's extremely little regulation, if any, about these tools scraping the hard work of journalists and creators and feeding them into their systems. So whether you're a major news organization or whether you're a small singer songwriter, all of that content and you know, published authors, all of that content is being taken in with no copyright pay. Um you have severe concerns around mental health particularly around young people but in fact you know in general um of unregulated uh lack of regulation on tools like open AI where these tools are then giving mental health advice or other medical advice this whole space needs some regulatory overview and in fact I think marketers because of their um it it's in marketers interest to create trusted environments and to support trusted environments I'm I'm optimistic that marketers who tend to self-regulate, right? In the UK, we have a self-regulatory body for the for the most part in the advertising space. I'm pretty confident that advertisers in the UK will get together and say that this is what best practice looks like and we're going to support it. And I'm sure CIM will be leading the charge there. Unfortunately, we live in a globe economy where that might not be the case everywhere. And that lack of regulation um it's it's concerning. I I think it's it's a real concern and marketers should be concerned about it too because if you get to a point where consumers are absolutely distrustful of the messages they are receiving, it makes it much harder for marketers to to talk to people and you know it's not in any of our interest to have a distrusted media environment. >> No, it certainly isn't. Um does bring a question though we we can split hairs over the generational thing. There is a generational aspect to this, but overall threearters of people nearly think that ARdriven advertising should be more tight tightly regulated. As Gemma says, it's an overwhelming demand from the public. It does beg a question though, does it not James Delves, that within our own organizations, who should own this governance? Is it us as marketeers? Is it legal team? Is it the IT team? It goes right to the jams of this world, the chief executive. You could boil it down to two things really. Part of the conversation is around marketing capability. If you have the skills and you have the discipline and you produce a really tight marketing campaign that adheres to everything, then you don't have a problem. It's when you don't have those skills, you don't have the guidelines in place, you don't have the infrastructure or the support etc. um then it's going to become exceptionally more difficult and risky to basically customers because you're not adhering to traditional marketing principles. A lot of the things which Jamie mentioned around AI if you look at you know things code of conduct you just wouldn't do because they're just not correct but you could roll it back to that going back to your question about who governs it. It's really interesting. We've had conversations with HR teams saying we need to own it. We've had conversations with board members saying it needs to be up the board. It's way too big for market. It needs to be at the base of the board. But it goes back down to, you know, marketers often know they're the kind of the connection point on a lot of brands to the customer. So they are connected with the customer. They do understand what the customer wants and what they need. And to Jamie's point earlier, this technology is going so fast that putting any legislation in place is really difficult. And you know, I've I've I've followed the AI regulation act through government. It's difficult because it is moving so fast. So I think probably it's governance across multiple areas of the business and everybody needs to have a say in it rather than own it. And once we get that in place, you're probably in a safer space to operate. >> Interesting. Let's let's let's look ahead. Let's look a little bit ahead of it. One thing we do know about this technology, regardless of the advantages and the opportunities and the threats and the risks associated with it, is that it's ever advancing, right? It's it's gently generally getting better. It's becoming more potent. We've even noticed it, haven't we, all on on a micro scale with the likes of chat GPT compared that to three years ago, it accuracy and so on to to its ability now. Nevertheless, that prompts a question. Well, it does for me anyway, which is are there some elements of our business which should never be done by AI regardless of how good the technology becomes. For example, could we see a difference between whether we deploy it in, you know, generating advertising versus offering customer support? Jamie, is there some areas that are sacrosan that always should be commanded by humans and humans alone? >> I I hesitate to to name a specific area because I think time will not be my friend and and it will have moved on. Um but I I do think you know there is so much evidence you know the other trend that is happening in the world of marketing at the same time as AI is this growth of the creator economy led by individual personalities and the growth of in-person live events people meeting and you know having brand experiences in experiential web those two things are connected right and it's because your customers are crying out for a human connection on some level so while you might be able to you know I' I've used chat bots on on websites to answer my tech questions with a particular product and that's fantastic. But if you have a real problem and your product isn't working to get hold of a human being on a telephone is is gold dust and can leave you with a really valuable brand experience at the end of it. So I I'm I'm really cautious to say oh that this is the limit and this is what should never be done. But I think every marketer needs to really think through not just okay what's the what's the cost saving I can do by automating this tomorrow. what's the customer benefit of keeping this as human or automating it and yeah and that's complicated and I think there was um there's a great quote in the report from Matt Burns from Rolls-Royce and he talks about a future team being an orchestrator of talent which I really like and this idea that you're going to have people in the team and some form of synthetic bot who are also working together and it's this unified team. It's a wonderful metaphor except we don't know who's in the orchestra yet. The instruments are still being built. We don't know yet what those technologies are. So yes, we should test. We should see what happens if we make all the call centers run through AI and and see if we can automate that because it could save us a ton of money. But the minute we start seeing signals that say it's not actually your customers renewal rate or your lifetime value of a customer is dropping away, you should be very prepared to say okay this this is not an AI suitable capacity. We're going to keep this human le. James Dell, have you had done that flash dance with technology where you got your technology broken and the person you want to fix it is anything other than a robot? >> Yes. Yes. My recent laptop I had same issues. I did certain amount of trouble spotting with um an AI tool. It was really helpful. But then I had to speak to somebody to say look as part of the process it's not quite there. I get to this point it doesn't work. Spoke to a person. He cleared it up in absolutely no time. So that combination of AI and person work really well for me. The other thing we obviously hear about it is when it comes out things like cultural judgment then when you're going out internationally or you just need to read the room or you need to basically understand how different cultures react to things differently that I still think is a there's a really strong case for um a human to be involved in that process because as we know scraping all the data to James point earlier probably doesn't give you a view of actually what's happening at this precise moment in time and you know the various different um sort of nuances you need to know to really make your messaging land with local population. >> Do you think that there are some areas where we're overestimating AI's capabilities? The implication of my question is yes, but there may be other areas, Jamie, where we're underestimating its capabilities. Do you think we've got the balance right into in how much value we're affording to its various roles? >> Yeah, absolutely. So I I think James's uh description in the beginning of front office and back office is actually really helpful and I know you know marketing is a complicated function. There's a lot of things going on. Front office back office is probably a simplification but I think it's useful. I think we are overestimating the impact AI is going to have in the creativity space. Like I of course it's going to cut 50 different versions of the same ad. Absolutely. It's going to do different versions. It's going to do translation. It's going to do all that stuff. Great. But it's not going to leave lead creative strategy and really know thought leadership and content generation. I think that humans are harder to replace in that space at the quality end than maybe we think at the moment. On the flip side, you know, and we've only lightly touched on this, but we've all had to do time sheets and invoices and completing spreadsheets and, you know, >> so much of what we have thought of for the last 50 50 years as part of office work is either going to become instantaneous or basically extremely quick to do. So, I think it makes you think differently about what you're really doing that adds value to the business as a marketer. And if if what you're historically have been really good at is reporting, that's not going to be that very that interesting for the business because that's just not going to be a skill people need. It's going to be automated. It's going to be country through that very quickly. If your skill is, ah, I can understand a strategy document and then I can I can build off that and then decide where we're going to take this and do something that surprises and delights our customers. Wow, that's going to be super valuable in a world of AI slot and instantly generated content. So I think your this thing about differentiation is is going to become really valuable and loads of the other business stuff we're getting there. I think that's I think we are still struggling to understand how much of that is going to disappear. I I because really you you you shouldn't need to be doing fiddling around with Excel sheets anymore. You shouldn't need to be uploading invoices for a particular month's report or all that stuff which like it for not for a lot of people that is big part of our jobs. >> Yeah. I prompts my final question people then my my final questions are usually about crystal ball gazing which is not popular with people because they feel they're going to be held to it. But at least for this one we're going to limit that gaze the term of that gaze to 18 months which in AI world I suppose is still quite a long time. With that in mind, Jamie, how do you see an AI native marketing team looking like within the 18month period? You know, what does it look like if you can gaze into the future 18 months? We come into a well-run, responsible, effective AI human marketing team. What does that look like? I I mean I think this is really cool partly because if you look at marketing and James knows this better than I do. If you look at what marketing teams look like today, they're very very different at different organizations, right? Depending on whether they're B2B and B2C or international or the scale of the business, etc. Um but I do think you know things we should be aiming for within the next 18 months are that uh certainly some of the more technology and data parts of the media buying process are automated. there are huge gains to be had there that everyone in your team understands how these technologies work and has a shared view of how they're going to benefit the business and maybe that doesn't mean everyone you doing everything all the time means dividing and conquering those tasks and hopefully then also a view of what marketers should be doing with any time that they save as a result of those technologies so I think this is a bit that's maybe missed out but if you're saving hypothetically an hour a day Thanks to using AI tools, what are you going to do with that hour? Are you going to use it to really think outside the box of some new creative idea? Are you going to meet your peers across the industry to have a coffee with them and understand what's happening in their business? Are you going to meet with suppliers and vendors to understand better how your company can use their services? There's lots of other parts of the marketing job that get underserviced at the moment. Everyone is in front of their screens tapping away. So I in an ideal world I think you'd have a marketing team where we understand what we want to automate and we're going as fast as we can to automate it but then we understand what we don't want to automate and marketing leaders are encouraging their teams to do more of that stuff. >> James, did you want to come in there? >> I completely agree. Um to completely steal some ideas of one of our course directors, he basically put it down into talent trajectory traction tracking. You got to get the people in the right seats and then give them tools to do it. You've got to basically know where your team's skills need to be in the future and in fill those gaps. And then when it comes to abstraction, the tools only work if they're actually built into the marketing process you want to do. The tools shouldn't be driving what you do. It should be you have a marketing process and the tools enable it. And if you can't show the output per person, you can't defend investment. So you should you shouldn't just be using tools the sake of it. And if you get that kind of balance right, the whole newsroom approach, I think you can do some really interesting stuff with AI tools. But it goes down to empowering people to use their spare time for creative and you know interesting things, not just do more stuff, produce more content. I think we really need to um avoid that. I have to say fascinating show guys. Thank you very much for joining us today. Um, it's also a fascinating report and we're going to that's going to be offered to the CIM membership in around about a month's time. So, this was a special uh preview, a little bit of an exclusive preview into that report. Thanks you to Gemma Connor from Yugov. Gemma, it's been fantastic to get your insights on the report today. Jamie Kredland who is CEO of the world media group and of course Mr. James Dell's head of PR and external affairs at CIM. Now, a quick plea before we go, do complete the survey. Uh the link is in the description to help us improve this show. We do actually read every response you send. We value your input. So, it's your chance to shape uh the future of the CIM Marketing Podcast. Please give us of course a rating and review on whichever platform you're using. Thank you very much again everyone for joining us today. That's the CIM Marketing Podcast. It's been a great show and we'll see you again very soon. 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