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The CMO Confidential Podcast is a proud member of the I Hear Everything Podcast Network. Looking to launch or scale your podcast, I Hear Everything delivers podcast production, growth and monetization solutions that transform your words into profit. Ready to give your brand a voice? Then visit iheareverything.com welcome to CMO Confidential.
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The podcast that takes you inside the drama, decisions and choices that go with being the Head of Marketing. Hosted by five time CMO Mike Linton.
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Welcome marketers, advertisers and those who love them to Chief Marketing Officer Confidential. CMO Confidential is a program that takes you inside the drama, the decisions and the politics that go with being the Head of Marketing at any company in what is one of the most scrutinized jobs in the executive suite. I'm Mike Linton, the former Chief Marketing Officer at Best Buy, ebay, Farmers Insurance and Ancestry.com here today with my guest Tom Goodwin. Today's topic Reflections on AI Questions, Contradictions and Observations. And we're also throwing in a few extra topics just as a bonus for our followers now. Tom has been studying innovation and change his entire career. He started in the agency business and held positions as the Head of Innovation at Zenith, the Head of Futures and Insight at Publicis, and SPV of Strategy and Innovation at Havas. He's a prominent speaker, wrote a book called Digital Darwinism and publishes Nowism. We've had him on a number of times during our three year run and always appreciate his provocative challenges to conventional wisdom. Welcome back Tom.
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C
I'm back. Thanks for having me again.
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A
Back again, Yes, a fan favorite. Well, let's start with one of your more famous traits, skepticism of commonly held thinking. In fact, lately I couldn't help but noticing in your posts that you have labeled a lot of thinking about AI and marketing plain old wrong. As in big W R O n g. Let's start with AI and the theory of AI is the automatic answer to all issues. And you've said it's wrong to think of AI as a plugin. Tell us what you mean by all that.
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C
I mean, people are very enthusiastic about AI and they should be because it's amazing and it's transformative. But every time something that's exciting comes along, people rush to apply it as soon as they can. And the way to apply it as soon as they can is to take the most sort of obvious and superficial and kind of easy places to apply it. I mean, we kind of saw it before, really, with every company having a chat bot. We're kind of seeing it now where every single Kind of digital product has this sort of weird sparkle icon. You know, you can see that at the bottom of this zoom call saying AI companion and this sort of vague notion of sparkliness. And it just appears that we're adding it where it's easy, but not where it makes a difference. You know, if I think about a platform like LinkedIn, if I wanted LinkedIn to be better, I'd want AI to reject automatically 95% of people that try and get in touch with me. I would like it to suggest upcoming meetings I should have in Chicago based on clients most likely to employ me. But instead we're kind of using AI to help me write a post. And as if somehow, you know, we need more help with getting more people to write stuff.
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A
Yes, we definitely need more posts.
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C
Yeah, we need more posts that no one can actually see because there's so many posts on the platform that no one can see anything anymore.
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A
Hey, Tom, is this laziness? Is this laziness or is this not thinking or what? What is driving this behavior or this just normal humans doing the normal human thing?
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C
I was going to say, for once, I'm actually quite well qualified to speak on this, which is I've been studying how technology is adapted for hundreds of years, and it's how we always do things. We have an existing structure, we have an existing business model, we have an existing workflow, we have existing incentives. And we sort of apply the new thing as something that can fit most easily into that. Because actually the real change comes from rethinking what we do. So actually, AI and commerce is an extremely exciting discussion. Discussion, but it requires a really deep understanding of how data is structured in commerce. It requires a really fundamental understanding of how people actually make decisions. It requires people to invest in new sort of infrastructure. And most people with their career trajectories don't have time to do things properly. They want to get out a press release. They want to show to other people that they've understood it and they've done something. A lot of times in this industry, people talk about sort of teenage sex as this sort of analogy for something new. And I find it quite sort of superficial and a bit grim. But in this case and the consulting that I do, you know, this really does feel like being 16 years old and at school and everyone's talking about sex. And there's this. This sense that everyone else is doing it. There's this sense that people are doing it really well. There's this sense that you don't really understand what it is. And when it happens and how it starts. But that's not the problem. And there's this enormous fear of missing out. There's this enormous need to pump share prices. There's this enormous need to signal to the rest of the industry. There's this enormous need to show that we're not sitting on our laurels. And as a result, I see case after case and white paper after white paper and example after example of stuff that's not really AI but it's called AI. It's of no benefit to a consumer whatsoever. It's producing large amounts of sort of waste, and it doesn't really go anywhere. And I get angry just because it could be so much better.
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A
Let's, let's give a couple examples of that. But first, I want to go back in your book.
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C
You.
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You made a. A demonstration of how electricity was misused when it was first invented.
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C
Yeah.
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A
And you're saying the same thing is happening here. Draw the parallel for our, for our listeners on that.
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C
It's quite a nice one. I mean, when electricity was invented, it took about 50 years for the world to really change. And for the first 20 years, you know, we took the iron and we made it an electric version. We took a toaster and we made it an electric version. We took an oven or a heating system. We took things that we already had and we applied electricity to them, and they were good. You know, an electric oven was slightly better than a stove. An electric toaster was slightly better than a toasting iron. But it didn't change the world. It was only really when we thought, wait a minute, this means that we can invent a fridge, or wait a minute, this means that we can invent a fax machine or a TV or a radio set or a microwave oven. It was only really the inventions that happened around the possibilities of electricity that made the difference. And quite weird because it's genuinely quite profound. Like when you take an existing structure and an existing mental model and you apply the technology, everyone sort of looks at each other, is a little bit surprised, is a little bit excited. But when you start with first principles and you don't go, this is how we work. Let's add AI. But instead you think, what are all the possibilities of stuff that we've always wanted to do? Can we make that happen? Is it now economical to do this? That's when you get the really profound shifts.
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A
And you were saying a bunch of the things going on right now drive you nuts. Tell us some of those things.
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C
Well, I mean, I think Often I get quite angry because most of the conversation about a technology is normally dominated by technology people. And technology people seem to be very good at getting on stages, very good at getting given micro microphones, and they're very good at getting noticed by other technology people. We saw it with Web3, we saw with blockchain, we saw it with VR. So all of a sudden, conversations about the future of law, the future of R.E.T, future of architecture, they're all being led by technologists who actually have no understanding of what a lawyer does or no understanding of what a retailer does. So I think I'm getting a little bit frustrated because we're seeing people talk about, I don't know, agentic commerce with no understanding of commerce whatsoever. You know, we're talking about movie making with AI without any understanding of the kind of craft and the dedication that goes into making a movie. And we're seeing people, you know, I'm being a bit rude here, but we're seeing kind of quasi autistic people effectively set the agenda for the medium term future. And they're amazing. People in the world needs people who think like this, but they're not people who are best placed to understand, you know, the weird logic and empathy and emotions of the world.
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When is the last time you researched something on a website? If you're like most people, AI did that work for you. And that raises a question. If AI is doing the work, what is your website really for? This behavioral shift means AI bots are becoming your most important new visitors. A challenge our sponsor Scrunch is taking head on. Scrunch is the customer experience platform that helps you understand how AI agents experience your site, when and why they show up and what's blocking them from being retrieved, trusted or recommended. Scrunch shows you the content and citation gaps and technical blockers and helps you fix them so your brand shows up when consumers start with AI because your most important site visitor might not be a human. For our listeners, Scrunch is providing a free website audit that uncovers how AI sees your site and how you're showing up in AI versus the competition. Run your site through it@scrunch.com CMO. Let's go to Agentic Commerce. You know, I was going to save that for later, but since you brought it up, you think a bunch of people working on agentic commerce have no idea what commerce really is. I think that's, that's what you're saying, right?
- [10:14]
C
The reality is that people quite like buying a lot of things. I mean, if you actually look at the things that you own in your house and you were to think about how it was that you came to procure them. You realize that you bought a vast number of things in completely different ways, in completely different. For completely different reasons and completely different situations. And even the same purchase may happen in different ways. So I might have some olive oil that sort of Whole Foods Basic, and I'll have some olive oil that sort of Israeli from some kind of kibbutz that's got a whole sort of, you know, picture of the owner on the back. And I'll have bought that from a farmer's market, and it will take me 37 minutes, and I'll try 17 different flavors. We buy things in remarkably different ways. And most of that stuff, we don't really want to be automated. Like, if we really wanted our commerce to be automated, we would actually would have subscribed to it on Amazon. It's a remarkably small part of Amazon's business subscription commerce because actually, most people, they want to sort of think about it a bit. They want to check out the price points. They want to see what's on sale. Maybe they want to try it. Maybe they want to ask their friend what they do. You know, shopping for a lot of people is part of life. It makes them feel something. It makes them feel a bit excited. They'll enjoy the process.
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A
And they don't always know exactly what they want.
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C
They absolutely don't. And I think, you know, people talk a lot about agentic commerce and flights. You know, for a lot of people, flights are kind of the foreplay of a weekend away. You know, this idea that you might have a stopover in Frankfurt, or the idea that you might get to fly on, you know, Air France's new seats. You know, not everyone gets stuck into it, but quite a lot of people get stuck into it. You know, trust becomes a huge problem with this stuff as well. And what. What sort of strikes me with something like agentic commerce is we've seen quite a lot of these things before. You know, we saw the Amazon dash button, which was quite a good invention, but went nowhere because that's not really how people work. We saw voice commerce, which was fairly helpful until you actually tried it for about 10 seconds and you realized it was completely unusable because no one wants to talk for 17 minutes about what type of battery to get. You know, we realized that actually pictures are quite good. You know, voice commas always suffered because, you know, one can tell how many Tide pods there are and which edition of Tide it is, and what it's going to smell like just from a picture. But if that information is read out to you, you know, you basically got a podcast of Tide pods talking at you for 20 minutes.
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A
And then beneath all this, you've got the algorithms, right? I mean, the other side of what you just said, which is the, let's call it the experience of shopping and the humanness of shopping, is the other side of that. The algorithm driven content you're talking about a little bit.
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C
I mean, it's all sort of part of this world of sort of new discovery, I guess, where some of our discovery is done on a sort of hand picked basis. Some of our discovery is done because brands help us navigate. Some discovery is done through agents or people or services that you curate. But increasingly more and more of our stuff comes into our life because of algorithms. You know, at one point when you use social media, the majority of your content was from people that you follow. Now, on a typical social media platform, about 90% of stuff that you will see has been suggested to you by the algorithm. So we're in a very interesting situation where a lot of people's opinions, a lot of people's knowledge, a lot of people's influences are now sort of being shaped by algorithms that are not necessarily working around people's best interests.
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A
And how are brands playing in this space? Because clearly a bunch of marketers are pouring money into the algorithms. You know, if you click on something like, you know, I race, I raise flowers, if I click on gladiols or something, I will get, you know, for the next several months just gladiolas will show up everywhere in all my stuff. You want to buy some gladiolas or, you know, a biking helmet or something, it'll just show up for it forever.
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C
Yes.
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A
How are brands playing in this and what are they doing right and wrong in your mind?
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C
First of all, I want to take a step back and that's to say I think it's actually very hard to be a CMO at the moment. I think effectively there was a traditional playbook which we kind of knew worked and it was kind of block and tackling where you kind of buy enough impressions on tv, you, you know, do an outdoor campaign, you do some print, you know, maybe you'll invest some money with retailers. We sort of had a playbook. And I wouldn't say that that playbook doesn't work. But for many brands and many audiences, it no longer works very well at all. And that's why if you turn on the tv. Almost every ad is for a kind of, you know, erectile dysfunction drug or for reverse mortgages or stairlifts or something. And then there's the kind of new playbook, really, and I think maybe I've talked about on here before, yeah, which is effectively to kind of spend money on digital media, you know, to let the algorithms decide for you. You know, you basically put in an objective, you kind of upload, maybe lookalike audience.
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A
Right.
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C
And the black box of it all sort of automatically spends your money. And we just got to trust that it actually happened and it was a good thing and that we got results from it. And effectively we're kind of. Someone like me is straddling these two worlds where I understand how the modern world process works, but I don't think it works very well for most clients that we face. And what I mean by that is a lot of the discourse on this is set by a direct to consumer shoe polish brand or it's set by a insurgent suitcase manufacturer or a direct to consumer wallet company. And these are companies with no brands and with often, you know, a direct to consumer relationship. And they're, they're companies that people expect to transact with online. And these companies are now being used almost as the kind of playbook, you know, for the Unilever. And the buyer's door from the Zurich insurance companies is to follow without understanding that most of these companies don't make any money, without understanding that often attribution is really create, about creating a reason to be successful rather than actually creating success itself. And they haven't understood how advertising really works. And the power of advertising, to me, and I may be wrong on this, but for me the power of advertising is not being able to sell more, it's being able to charge more for what you sell.
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A
So, and you have said, you know, one of Your posts said 95% of people in advertising think they know how it works and they are wrong.
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C
Yes.
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A
And we're also seeing advertising come to, you know, AI now or announce that it's coming. Tell us about 95% of people don't know how it works. And then what's going to happen when you're seeing ads in your AI?
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C
I mean, that number is based on this idea that almost every small and medium sized company has someone in advertising. And increasingly those people are following the playbook of the performance advertisers. And therefore they think that their job is to get immediate sales. They think that their job is to translate an impression into a click. They think that click through rates matter. They think that a real time dashboard that does social sentiment listening will pick up on what matters about their brand. I think they base being kind of sold on a whole religion of advertising, which is not untrue, but it's not necessarily reflective of the entire scope of advertising and the entire world of advertising. Because actually advertising is a really weird thing. Advertising makes people behave in ways that don't make sense. Advertising is somewhat unexplainable. Advertising works over a really, really, really long period of time. Most impacts of advertising will never be possible to attribute into a spreadsheet. And I think therefore there's this sort of weird thing where a lot of the old guard of advertising people, they understood that they didn't really know how it all worked specifically, but they knew that it worked generously.
- [18:41]
A
Well, you had those bass, those bastion companies like Proctor and Pepsi and you know, Frito and Lever Brothers and General Mills that yes, believe to their very core to a person, that it worked.
- [18:55]
C
Yes, yes. But they probably couldn't be out. They couldn't explain how each one did. I mean that that's my sort of general point I'm not making very well is that they knew that if they spend 25 million on media, then all of these things would happen over roughly this period of time. But you wouldn't be able to say, well, it was that 48 sheet, you know, outside Tottenham Court Station that drove this pack of cereal being port.
- [19:20]
A
Right.
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C
Whereas there's this sort of new wave of thinking that kind of looks at advertising as a science. And it kind of assumes that if you can put this many eyeballs into this black box and then you can turn that handle and put in this third party data and then use this tracking software and then use AI to optimize and then change the woman's color from blonde to brown and then put them in a boat rather than the plane and then serve it on a sunny day, not a rainy day, and then pull in this special offer. They kind of think that it's a logical process.
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A
They're going to do a million a B tests with AI now to optimize that. But in your theory then a bunch of brands are going to lose their way over time and lose their brand power. You've also said AI won't fix old companies. Tell us why.
- [20:09]
C
It kind of goes back to what I was saying before, really about the application of a technology rather than the ability to make significant changes. And this sort of comes from a lot of experience I have really again, some of My kind of emotion comes from the fact that I'll go to many events where extremely bright 29 year olds will say that AI is going to change everything. And then three days later I'll be in a kind of an office in Detroit, you know, talking to a legacy car maker. And you'll realize that, you know, they can't get their computers to work in the room and the WI fi doesn't really work in that part of the building. We've got 27 different databases where different country managers recorded the data in different ways, where the license on some software is expired and they haven't got around to buying a new one, where 13 different people own the data and they all have arguments about who owns it.
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A
They all get paid differently too.
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C
Usually they all get paid different. They've got completely different incentives, their own individual performance plans. And this is not me being in any way sort of miserable or dismissive of it. I'm just explaining that the reality of businesses is they've been built up over a really long time by people that have done a really good job, who've done the best with what they can. They've used very old software, they've got technical debt, they've got software audit, software audit problems, they've got license issues, they've got incentives to act against each other, they've got risk aversion, they've got version control. And there's this sort of feeling somehow that that's all great, but if you just add a bit of AI, it's going to fix it.
- [21:45]
A
So does this mean that older companies that have these issues, are they at bigger risk from AI? Native companies that do the electricity model you said before, I think one needs.
- [22:00]
C
To go through every category and figure out where this is likely to be a much bigger problem. AI, I do think is a very transformative technology, but it doesn't change every industry. You know, if you look to something like the car business, you'd already find out that actually most car plants are using extremely advanced forms of AI to optimize how they do things. You'll realize that the majority of their advertising actually works quite well in a sort of non AI environment. And you'd realize that actually the best use of AI would probably be through their dealers. It'd probably be to kind of apply it in a very decentralized way and to let their dealers have access to better technology. You look at a company like P and G and I would imagine that AI would have a fairly minimal impact on their business. And P and G is not under threat from a kind of direct to consumer fabric conditioner company, because that's just not how the unit economics of that industry works. When you get to a company like an area like insurance or banking or payment companies, when you get to products that are more service based, when you get to things that the unit economics are a little bit different, you know, then you can start to see some places. But the difficult thing about being me is I firmly believe the technology is changing the world and I firmly believe that that's happening quite fast. And I firmly believe it's a threat to most companies, it's an opportunity to most companies. But I don't believe any of this extreme thing, you know, like the idea that big companies are doomed for death unless they change everything immediately.
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A
And then you also, you have different opinions on AI threatening entry level positions because one of the things you think is it actually can enhance some positions.
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C
I think broadly speaking, what we're doing with AI is completely wrong because we're applying it where we can apply it most easily and almost every single way it's sold in is now you can do things faster and cheaper and easier. So great news like now you can send a million emails to people like.
- [24:10]
A
Great news, you can personalize 10 million emails at speed.
- [24:13]
C
Yes. And I think when we're in the faster, cheaper, easier way of thinking, then entry level work is kind of screwed because most of the time AI is better than an intern. Now there are two sort of issues with that. One is I think it's incumbent on us as professionals to keep the ladder in place that we climbed up. And I think every company needs fresh blood and every company needs people to come up through the ranks. And younger people and less experienced people are invaluable in many different ways. I think the second thing is we need to not be focused on cost cutting, but instead be focused on new possibilities. You know, I myself, if I work for a big company now, I'd actually be really excited to have a team of people reporting into me because I could be saying to them, you know, go out and explore and experiment with this stuff and have fun with it and come back to me at the end of every week with a couple of projects that you've done on the side that, you know, four years ago would have taken you a hundred thousand dollars in a year and now you can just give to some sort of agentic workflow or you can give to.
- [25:21]
A
Have any good examples of that like that you can share.
- [25:25]
C
I'm going to have to make this Quite vague because it comes from a client of mine, but I have a client that's basically kind of dabbling in this stuff all day long. And they're not the kind of person you'd expect to do this because they're in the sort of latter stages of their career and they're not a technologist by any scheme of the imagination, but they will routinely pick up on projects that are not really theirs to do and they'll effectively sort of play around with them, with I think in Claude in their case, and effectively kind of spar ideas against each other. So they may, and I'm going to deliberately make this not the real example, they may say, you know, what destination should this airline be flying to? They may play around and say, give me some examples of the unit economic changes that would happen if we completely rethought economy class and made it even more expensive and made it better. And effectively what they're doing is they're just sort of co, kind of collaborating and co instigating lots of discussions and lots of questions which they never would have ordinarily have time to consider. And then as a result of three or four of these experiments, they'll find one or two interesting hypotheses to take further.
- [26:43]
B
Over the weekend, I asked AI to do dozens of things for me. Please help me make this dishwasher start working. Settle a debate between me and my partner. Is it safe to sleep at 80 degrees?
- [26:56]
C
It's not.
- [26:57]
B
Please help me find a robotics kit for a five year old operating at a middle school level and even help me compare the Scrunch Agent Experience platform with Adobe's LLM optimizer. In every one of these interactions, I never once visited a website. In this day and age. What's your website actually for? The truth is, almost everything on your website is now for AI consumption. The Scrunch Agent Experience platform helps manage, optimize and deliver content directly for AI to retrieve.
- [27:38]
A
There's another thing I want to flip too, which is your belief that social media is becoming even more shallow and vacuous than it was before. Something many thought to be impossible. Tell us what you're seeing.
- [27:51]
C
I'm gonna sound like really grumpy and.
- [27:53]
A
Sort of, you know, we love that about you. If you can't be grumpy, who can be grumpy? You are licensed to others to be grumpy.
- [28:01]
C
I mean, here I go. So I'm gonna sound like a snob as well. But I mean, you know, eight years ago you'd, you'd sort of see how people were spending their time on their phones. And it would be quite tragic. You know, people would be watching terrible TV and people would be watching awful, you know, influencer films on TikTok. You'd see, you know, really sort of pathetic viral content. And the general quality of what you would see on algorithmic feeds in a user generated world was really awful. You know, the quality of celebrity was, was low quality, production was tiny, the ideas weren't very good and most of what people were watching, if you actually asked them to afterwards to explain what they saw or what it was, they wouldn't be able to remember it and they wouldn't feel very good about it.
- [28:46]
A
Except for cat videos. They always remember the cat videos.
- [28:50]
C
And it's kind of weird because now I look at those times almost with a kind of nostalgic glow of how good it was because it was real people crafting films and doing their dances and overlaying their music. And now you see feeds. And it's not just that it's made by AI, it's, it's quite sinister. So either it's kind of fake news for things that didn't happen either it's deliberately kind of misleading films to kind of God people into being angry, whether it's kind of just cheaply made stuff that is essentially trying to maximize odds in the casino. I mean, I, I am routinely pitched by these companies and there'll be one which says, Tom, you know, just turn every single article of yours into a 45 minute podcast and you can produce, you know, 1,000 of these podcasts. I, I don't need that to be 1000 really badly made AI generated podcasts of me. And as a result, you kind of look at the average fare that's on TikTok or Instagram or Google Shorts or, or YouTube and it's just like genuinely of no calorific content. But somehow the algorithms are so good at kind of knowing quite how hopeless and lost we are that we're all there, kind of like stuck to our phones like a kind of moth that keeps on flying into the bloody heat because somehow we kind of.
- [30:21]
A
So after this we should go to the dentist for an uplift. Let's, let's write marketers and agencies into the story. You, you believe everyone should stay true to the craft of building a brand because in the end that the brand does drive sales and is a sorting mechanism for consumers. What else should marketers do today? And I agree with you, the, the function of marketing as it was, is in great transition now, and it's unclear exactly how it shakes out to me. What should marketers be doing now?
- [30:58]
C
I think first of all, one needs to recognize quite how challenging the situation is, because I actually think that what they know to be right and what their instincts tell them to do is still very much the way to do the job. But I think it's becoming increasingly hard to kind of fight that battle when every single week there's a kind of press release saying this will automate your marketing and this will increase return on ad spend by 2.9%, you know, so I think, I think first of all is they need to kind of stick to their guns. I think they need to make sure that they're still experimenting with this stuff and they have an open mind to it and they're happy to kind of make some changes and to try new things. I think there's an enormous opportunity to use digital media as a way to build brands. For some reason, just because you can micro target and just because you can produce content that people click on, that doesn't mean that you have to make stuff like that for digital screens. You know, my kind of big hope for the future is that people would take stuff that looked a bit like old school outdoor and looked a bit like TV and they would effectively be placing that as sort of digital forms. You know, I don't understand why on Twitter I'm not shown like beautiful burgers, that kind of glimmer. I'm not sure why a digital ad on my phone doesn't kind of come alive when I, when I turn my phone slightly. And the reason is because people have always assumed that digital media is a place to do performance rather than brand building. I think they need to get up to speed with AI and what it means. I do think it will be quite a big threat for a lot of people's jobs in the short term. Not because it's amazing, but because people will think it's amazing and people will take some of the average quality work that AI does and they'll think it's good enough and they'll see some of the errors that are in there and they won't be worried enough about them.
- [32:56]
A
And how about as ads come into the LLMs, the possibility of how this works out. Yeah, it's super interesting, especially given the power the LLM will have to recommend things to you. How do, how should people be thinking about that?
- [33:14]
C
Maybe I'm being, maybe I'm wrong here, or maybe I'm lazy, but I think of it almost exactly the Same as a search. I mean, when one went to Google and said, tell me a good weekend destination to go to, there would be organic listings and there would be paid listings, right? And now when we go to an LLM, we get effectively organic listings. And the way that that data is impacted is very similar to the mechanisms that SEO used. And then increasingly there'll be sort of paid suggestions which will be based either on that particular query or demographics they have about us or memory of our recent behavior, depending on how they decide to do it. But in all of those instances, we will effectively be in a similar situation to search.
- [34:02]
A
I think it's just a real transfer of.
- [34:04]
C
I think so. I mean, you can argue it's different because it's a bit more intimate. You can argue it's different because we can use AI to, you know, target those ads a little bit better. But I think the kind of fundamental dynamics of this being a screen where having your intent signals a piece of real estate is transacted in real time, I think a lot of those dynamics will produce something very similar.
- [34:27]
A
Great. Since we're still early in 2026, what is a top prediction you have for something that happens by the end of 2026?
- [34:37]
C
I think we're going to see a lot of mistakes with AI, actually. I really get the feeling that a lot of people are phoning it in. I think we're going to see some really, really expensive media being used to make, to place ads which are simply not good enough. So probably the super bowl will be an example. There's probably going to be some entirely AI generated ad which is just going to be 100% shit. And then people are going to be thinking, why did you save, you know, $500,000 on production and spend $23 million on media? This doesn't make any sense. I think we're going to see some massive security breaches. Without sounding too miserable, this idea that somehow everyone in their jobs are kind of uploading secure company information and sort of proprietary data to LLMs is completely bananas to me. So I think we'll see some sort of massive security implications and I think slowly we'll come to a recognition that this technology really has its place. And it's not to do everything for you, it's to be a partner in testing you and training you and teaching you and opening your mind to new horizons. But ultimately you're the kind of person that's in control and you're the person with the best judgment and the best innate feeling for what works.
- [36:01]
A
All right. We'll see how many of those come true. We'll have you back and talk about it. Which brings us to our traditional last question. Funniest story you can tell on the air or practical advice we haven't discussed yet. Last time you talked about being locked out of a Waymo. So what do you got for us this time?
- [36:18]
C
I was thinking about this the other day. So you now have these AI generated images, and they're beautiful and they're quite high resolution. And I don't think that's necessarily the solution. But at the same time, one has to recognize that the ad industry has been very slow to change. I was reminded the other day of a project where, for a large mobile phone company that was dominant in Europe, we were given about $3 million to shoot a print campaign. We flew around the world to about 17 different cities. In each city, we went to some amazing underground club. We commissioned some amazing photographer. We cleared out global rights. We basically spent $3 million making about 52 images. And when these images were finally shown on the last campaign, each image was about the size of a kind of postage stamp.
- [37:11]
A
Yeah, they were beautiful.
- [37:13]
C
They were beautiful. They were crafted. They were perfect for the target audience. And they were about a hundred thousand dollars each. And no one even today can even sort of see anything in these images at all. And I think that's where we are. I think we have to recognize that spending $3 million on a print shoot and having 17 people on the shoot and 53 people working on the production team is not the solution. But one also can't just give this all out to an AI and have no soul and no craft and no. And no control and no care over what we do. Because what we do should be considered really important. And doing stuff really well is vital. And ultimately we are in the industry of being exceptional. And AI by definition does a really average job. And therefore it's really powerful when used for things that don't matter that much. But I think we all have to be a bit more ambitious and struggle against the desire to be lazy and instead use this technology to be more brilliant than we've ever been before.
- [38:18]
A
There's a way to look at this to say there's a layer of conformity. And your job as a marketer is to make sure you use that conformity to your advantage.
- [38:26]
C
Yes.
- [38:26]
A
But that you are adding some exceptional element on top of it.
- [38:31]
C
Precisely.
- [38:32]
A
Your business noticeable. And if you had sucked completely into the conformity, it will be impossible to stand out.
- [38:41]
C
Precisely. I see a bit like elevator music versus Top Hits. You know, like the world is elevator music. It's our job to struggle and to work hard and to be in agony trying to produce the remarkable thing that breaks through from that.
- [38:58]
A
Yes, we must get out of the elevator music. I think that's a great way to end the show. Thank you Tom. And thank you everyone for listening to CMO Confidential. New shows drop every Tuesday and all of our more than 150 shows are available on Spotify, Apple and YouTube, which include why Can, Can't Colonel Mustard in the study with the job spec, How Poor design shortens CMO lifespans, B2B marketing, the year in Review and the Year Ahead, and Tom's previous shows like A Contrarian's View of Everything Everywhere all at Once. And if you drop the best marketers of the 1950s into today's jobs, how would they do? Hey all you marketers, stay safe out there. This is Mike Lindsen signing off for CMO Confidential. When is the last time you researched something on a website? If you're like most people, AI did that work for you. And that raises a question. If AI is doing the work, what is your website really for? This behavioral shift means AI bots are becoming your most important new visitors. A challenge our sponsor, Scrunch, is taking head on. Scrunch is the customer experience platform that helps you understand how AI agents experience your site, when and why they show up, and what's blocking them from being retrieved, trusted or recommended. Scrunch shows you the content and citation gaps and technical blockers and helps you fix them so your brand shows up when consumers start with AI. Because your most important site visitor might not be a human. For our listeners, Scrunch is providing a free website audit that uncovers how AI sees your site and how you're showing up in AI versus the competition. Run your site through it@scrunch.com CMO.