Latest / Sleeping Barber - A Marketing Podcast / SBP 228: Interview - AI Won't Decide the Future of Marketing. We Will. With Pats McDonald.

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SBP 228: Interview - AI Won't Decide the Future of Marketing. We Will. With Pats McDonald. · Sleeping Barber - A Marketing Podcast

• 0:00
  SPEAKER_01: Welcome to the Sleeping Barber Podcast.
• 0:02
  SPEAKER_01: Easy things.
• 0:03
  SPEAKER_01: People say, oh well, you know, we don't need entry-level talent because AI can take care of that.
• 0:08
  SPEAKER_01: And I think as an industry, if you give up on entry-level talent, you've kind of given up on your future.
• 0:13
  SPEAKER_01: You're saying we've only got another kind of 10 years in us, which is a really dangerous place to be.
• 0:18
  SPEAKER_00: Welcome to the Sleeping Barber Podcast, the place for business leaders to get the best and most credible information on marketing, strategy, and innovation.
• 0:27
  SPEAKER_00: Your hosts, Mark Binkley and Vasily Storos, share their experiences as they gather insights from the world's leading experts.
• 0:35
  SPEAKER_00: Now, on with the show.
• 0:38
  SPEAKER_03: Yes.
• 0:38
  SPEAKER_03: Hey, welcome back.
• 0:40
  SPEAKER_03: We are with Pat McDonald.
• 0:42
  SPEAKER_03: Thanks for joining us today.
• 0:43
  SPEAKER_03: Pleasure.
• 0:44
  SPEAKER_03: Super excited to have you here.
• 0:45
  SPEAKER_03: You were on the panel on stage at Cannes earlier this week, speaking a lot about the future and planning for the next 18 months.
• 0:52
  SPEAKER_03: And it's I wanted to kind of maybe sorry, before we even jump off into the questions, the chief strategy officer at Densu Creative, I should have introduced you to that.
• 1:01
  SPEAKER_03: Sorry, straight, straight on that.
• 1:05
  SPEAKER_03: We originally met because of an article, a series of articles I've been writing for work.
• 1:09
  SPEAKER_03: And you've really been leading a charge with AI for Densu Creative and the approaches that you're taking and how to integrate it and thinking about it and organizational impacts, which is so grateful to have you here.
• 1:19
  SPEAKER_03: So thanks for joining us.
• 1:21
  SPEAKER_01: Thank you.
• 1:21
  SPEAKER_01: My pleasure.
• 1:23
  SPEAKER_03: So the question I wanted to ask you around the panel that you were on is just as a starting point, maybe where are we today with this and thinking about it from your perspective in at in the agency and implementing it into an organization?
• 1:36
  SPEAKER_01: Yeah, so the panel that we talked about a lot about AI and human agency and agents.
• 1:42
  SPEAKER_01: And it was really about the fact that no one really knows what the next 18 months are going to bring.
• 1:47
  SPEAKER_01: We don't always know what the next 18 days are going to bring at the moment.
• 1:51
  SPEAKER_01: We're sort of defined by that incredibly volatile environment.
• 1:55
  SPEAKER_01: But it was a kind of plea for people to stop saying things like AI will do this or AI will do that.
• 2:03
  SPEAKER_01: Because in fact, AI can't do any of those things.
• 2:07
  SPEAKER_01: Human beings do those things, and they're enabled by AI.
• 2:11
  SPEAKER_01: But the language that we use can sometimes make us feel very passive.
• 2:16
  SPEAKER_01: And it feels like the human is not the agent, is not the decision maker.
• 2:21
  SPEAKER_01: So we had some really nice research with about 4,000 people around the world, which showed that people feel quite out of control right now when it comes to the impact of AI on their lives, on their jobs.
• 2:34
  SPEAKER_01: Um they don't necessarily feel government is in control of AI.
• 2:38
  SPEAKER_01: And that's creating a certain reluctance to give up too much control.
• 2:43
  SPEAKER_01: So I think there's a tendency to assume that because the technology makes something possible, people will adopt it.
• 2:49
  SPEAKER_01: And actually, when we ask people, will you give an agent your credit card?
• 2:53
  SPEAKER_01: Will you let it book your travel?
• 2:55
  SPEAKER_01: Will you let it send messages, access your healthcare data?
• 2:59
  SPEAKER_01: Lots of people are still saying, no, no, no, hang on.
• 3:02
  SPEAKER_01: I'm really not prepared to give that full level of autonomy up.
• 3:07
  SPEAKER_04: Because I I took all my health records and I'm like, tell me what I need to know.
• 3:11
  SPEAKER_04: Let's go.
• 3:12
  SPEAKER_04: What do I need to fix?
• 3:13
  SPEAKER_01: Well, actually, people are more comfortable giving up their health data than their credit card data, or their which is um which is fascinating.
• 3:20
  SPEAKER_04: That is fascinating.
• 3:21
  SPEAKER_04: So for the most for the most of your career, you've kind of sat at that intersection that many really want, right?
• 3:26
  SPEAKER_04: You know, the strategy side and the creative side, which is a phenomenal place kind of to be.
• 3:31
  SPEAKER_04: Now we have AI.
• 3:32
  SPEAKER_04: So now you're sitting at that intersection of both strategy creative and now AI as well as a part of that.
• 3:37
  SPEAKER_04: When you think about, you know, if we think about how you thought as a strategist about five years ago versus how you think today, how much of what what and how you approach things have changed with that you know, new vehicle or new medium?
• 3:50
  SPEAKER_04: I don't know how the best way to characterize uh the AI.
• 3:54
  SPEAKER_01: Yeah, I think AI is impacting strategy in three big ways.
• 3:58
  SPEAKER_01: I guess there's the the workflow and the the process, the our process for how we define strategy.
• 4:05
  SPEAKER_01: So that's certainly changing.
• 4:07
  SPEAKER_01: It's accelerating some things, it's giving people more optionality, it's providing a kind of thought partner.
• 4:14
  SPEAKER_01: We're also seeing, you know, AI is the context that our consumers are existing in.
• 4:20
  SPEAKER_01: So we see customers and how they're feeling about the world, about how safe and secure they feel, how they're responding to certain types of content.
• 4:30
  SPEAKER_01: So that's the it it's having a huge impact on cultural context.
• 4:35
  SPEAKER_01: Um the strategies that we create for that cultural moment have to be informed by that.
• 4:39
  SPEAKER_01: We talked on on Monday on our panel a lot about the desire for imperfection and humanity and things that kind of show the cracks in response to how perfect AI generated content can feel.
• 4:52
  SPEAKER_01: What I haven't seen so much of, and I need to go spend some more time with the creative strategy uh submissions for Khan, but I haven't yet seen people say because of what AI enabled me to do with data and insight, I got to a radically different place.
• 5:07
  SPEAKER_01: And I think that's the next step for people to start showing how in their practice uncovering a different data set or uncovering a different kind of wrinkle in the data created a sharper and more differentiated strategy.
• 5:22
  SPEAKER_03: When we were doing the prep call a while back, you had talked given given us a couple of great examples.
• 5:26
  SPEAKER_03: We were talking about a couple of great examples you guys have done.
• 5:28
  SPEAKER_03: And and I think there's I'd love for you to talk about one or both.
• 5:32
  SPEAKER_03: Uh or if I think you give me three.
• 5:34
  SPEAKER_03: But the idea that creative can't be done, as it seems to be can't be done on AI, or it's not good AI is not good at creative.
• 5:42
  SPEAKER_03: But the examples you had in and there was the phone scammer one as an example.
• 5:47
  SPEAKER_03: The what's possible was the thing that made me kind of go like maybe it's not necessarily the creative output, the you know, it's the the i creative ideation component that is possible.
• 5:59
  SPEAKER_01: Yeah, I think that's right.
• 6:01
  SPEAKER_01: I think AI is at its best when it's not about doing more with less, it's doing things we couldn't possibly have done before.
• 6:08
  SPEAKER_01: So the case you mentioned is a a great case by uh VCCP in the UK.
• 6:12
  SPEAKER_01: It's uh Daisy versus scammers.
• 6:15
  SPEAKER_01: And they created an AI grandma who, when phone scammers would call up, would just bore them to death, basically.
• 6:23
  SPEAKER_01: So they'd be on the phone an hour later while she's saying, Oh, have I told you about my cat and my grandson and they're going out of their minds.
• 6:29
  SPEAKER_01: And it's it's the kind of thing that's only possible with AI.
• 6:33
  SPEAKER_01: So that's a a great example.
• 6:34
  SPEAKER_01: Uh I think we talked in the pre-call about some work we'd done on the Inflation Cookbook.
• 6:40
  SPEAKER_01: Yes, it's gonna affect which was a lovely combination of human empathy, understanding that when you're in the grocery store, yes, it's scary that prices are going up, but it's the volatility that's really terrifying if you're a kind of mom and you have a plan for the week.
• 6:55
  SPEAKER_01: The fact that suddenly what you plan to buy is like three dollars more than it was last week.
• 6:59
  SPEAKER_01: But that so human empathy, but only made possible by the fact that we could access dynamic pricing, generate dynamic recipes, generate dynamic imagery.
• 7:07
  SPEAKER_04: Right, right.
• 7:09
  SPEAKER_04: The other I guess the other side of this is the development side.
• 7:13
  SPEAKER_04: Right?
• 7:14
  SPEAKER_04: And what's interesting is like where you read what or sorry, you read what you hear, or you hear what you read, where people are like those entry-level jobs are becoming a lot more difficult for people that are coming out of university, how do you get them trained?
• 7:25
  SPEAKER_04: Because now AI is kind of taking on some of those mundane tasks that you know a lot of us kind of grew up through or we we you know, we work through to get to where we are today.
• 7:35
  SPEAKER_04: How do we, from an organizational perspective, actually look at that talent gap?
• 7:40
  SPEAKER_04: Because there is a gap that we still need to for have people to come in, but what's the role of AI and then actually making sure there's new individuals coming in to help with that?
• 7:50
  SPEAKER_01: Yeah, it's it's a great question.
• 7:51
  SPEAKER_01: I mean, it's it's one of those very easy things.
• 7:53
  SPEAKER_01: People say, Oh, well, you know, we don't need entry-level talent because AI can take care of that.
• 7:58
  SPEAKER_01: And I think as an industry, if you give up on ent entry-level talent, you've kind of given up on your future.
• 8:03
  SPEAKER_01: You're saying we've only got another kind of ten years in us, which is a really dangerous place to be.
• 8:08
  SPEAKER_01: I think it's incredibly important that we're still training young talent.
• 8:13
  SPEAKER_01: You know, we talk a lot about training the model.
• 8:16
  SPEAKER_01: So much time about how we're training the model and teaching it the kind of our best practice.
• 8:20
  SPEAKER_01: And we've got to do the same for for young strategists, if not more so, you know, because they're creating the training data of the future in the strategies that they write.
• 8:30
  SPEAKER_01: And they're the ones who are going to hopefully call us when we're making these kind of brand bland, sweeping generalizations about their generation.
• 8:40
  SPEAKER_01: They're the ones who have got time and mental bandwidth to go around and find really interesting little nuggets of of insight that, you know, we're missing as we kind of fly around the world.
• 8:50
  SPEAKER_03: Aaron Ross Powell Related to the talent side of things, there's always this conversation around specialists versus generalists.
• 8:57
  SPEAKER_03: And organizations, and I don't know if this is true for Densu Creative, but a lot of organizations kind of segregated their staff by almost channel or then not even just channel in the media side, but then you've also got like PR and comms and creative, and so there's like specialist sort of departments within the marketing, but then also even within that, there's even subspecializations.
• 9:19
  SPEAKER_03: And so is this a time when we should be thinking more about generalization because AI could do everything, or do we really like how do you create that balance between special and general?
• 9:30
  SPEAKER_01: I think it really ebbs and flows in the industry.
• 9:32
  SPEAKER_01: So sometimes we're at a moment of we need incredible vertical specialism, and sometimes we're in a moment where we need people who can see the whole board.
• 9:42
  SPEAKER_01: And I think certainly in strategy at the moment, we need people who can really understand both the customer, the audience in a in a very profound way that strategists have always done, but also really understand the algorithm and understand how a message is going to travel through the modern media ecosystem.
• 10:02
  SPEAKER_01: So we talk a lot about we need people who can not just create big ideas but create catalyzing ideas.
• 10:08
  SPEAKER_01: So an idea that's going to be easy for a creator to find a way into or a co-creator, a culture maker to grab onto and kind of find a way to tell their stories through the lens of that idea.
• 10:20
  SPEAKER_01: And um I've talked to some CMOs this week who've said actually our current brand strategy isn't quite right because it's not giving enough of those little spikes and hooks for other people to attach themselves to.
• 10:32
  SPEAKER_01: So I think strategists today, even a generalist, need to be very strong on creative strategy, but also com strategy, channel strategy.
• 10:42
  SPEAKER_01: They need to know a little bit about creator, they need to know something about community.
• 10:47
  SPEAKER_01: So we're definitely needing a much broader set of skills.
• 10:50
  SPEAKER_01: But then of course, you'll need absolute specialists in how you optimize for an LLM, for example.
• 10:55
  SPEAKER_01: And it's about being open and curious and knowing just enough to say, right, here's when I need my specialist partner, and I know where to find them, and there are no silos in my organization to going and borrowing a bit of them.
• 11:08
  SPEAKER_04: I can definitely see the value in making like creating or training individuals to have more of that open aperture, if you will.
• 11:17
  SPEAKER_04: Because like a lot of it, you know, we probably gain through experience and and things like that.
• 11:22
  SPEAKER_04: There's a lot of people that are probably looking to move quicker.
• 11:24
  SPEAKER_04: So when you're, you know, maybe there's a strategist listening to this episode, it's like, hey, how do I get to that next unlock?
• 11:30
  SPEAKER_04: How would you guide them when they're looking at that and and they're trying to navigate that in their career?
• 11:35
  SPEAKER_04: Because it it does take a lot of fortitude to want to go and do all the different things to get become more of that generalist.
• 11:44
  SPEAKER_01: Yeah, I think you've got to just be very humble and very unthreatened by specialists.
• 11:51
  SPEAKER_01: So, you know, maybe 10, 15 years ago when programmatic was the buzzword, I knew very little about that because I'd come up through a brand strashy background, and I just found some smart people and said, I don't know about this.
• 12:05
  SPEAKER_01: T teach me.
• 12:06
  SPEAKER_01: So explain to me exactly what you mean by it, and tell me all the different ways you can target and retarget people and the pros and cons.
• 12:13
  SPEAKER_01: And then a little bit later, when we're starting to use, you know, large language models to understand social data and things like that, sitting with specialists and going, talk to me about the difference between a probabilistic model and a deterministic model, and kind of, you know.
• 12:27
  SPEAKER_01: I think a lot of people are sitting in rooms at the moment not understanding, and they're terrified to say.
• 12:32
  SPEAKER_01: And I think it's okay to say.
• 12:34
  SPEAKER_01: You don't have to know everything, but you do have to be curious about everything.
• 12:40
  SPEAKER_03: I know, right?
• 12:42
  SPEAKER_03: And it's true though, because it what you have this and there's a couple of thoughts that we sh people have shared with us.
• 12:48
  SPEAKER_03: There's this book, I keep forgetting the exact title, but it's something like Ask Better Questions.
• 12:52
  SPEAKER_03: Yes.
• 12:52
  SPEAKER_03: But there used to be this notion that we had to have all the answers.
• 12:55
  SPEAKER_03: And so it now that AI has all the answers theory in theory, maybe it is about asking better questions.
• 13:02
  SPEAKER_03: I don't know if like, but how do you train that?
• 13:04
  SPEAKER_03: That's because then there's almost a part of curiosity that you need to like reinstill in people from an organizational point of view.
• 13:12
  SPEAKER_01: Yeah, I think that's right.
• 13:13
  SPEAKER_01: But I think good strategy's always been about it.
• 13:16
  SPEAKER_01: Yeah, I agree too.
• 13:17
  SPEAKER_01: I mean, I think great strategy has always been about asking the right question.
• 13:20
  SPEAKER_01: Absolutely.
• 13:21
  SPEAKER_01: If you ask a really smart question, you're halfway to a really smart answer.
• 13:25
  SPEAKER_01: And so it's that kind of relentless asking of why.
• 13:28
  SPEAKER_01: And I think that's when AI gives you an answer, and not to kind of say, okay, great, you know, you've given me the information.
• 13:34
  SPEAKER_01: Or why is that happening?
• 13:36
  SPEAKER_01: And let me pick on that bit of the answer and go down that particular rabbit hole for a little bit to find something interesting.
• 13:41
  SPEAKER_04: Agreed.
• 13:41
  SPEAKER_04: It's funny because d does AI help accelerate curiosity now?
• 13:46
  SPEAKER_04: Like, could we look at it from another lens and say, you know what?
• 13:50
  SPEAKER_04: Because we have these tools now available to us, maybe we can accelerate the process of becoming more of a generalist because now I have this tool to kind of ask it, push it, and become even more prepared or informed when I go to Pat to say, hey, I need you to help me on programmatic.
• 14:05
  SPEAKER_04: Here's what I understand, here's the foundational stuff, help me unlock that next level.
• 14:09
  SPEAKER_04: I think that I think there's a there's something there to make sure that consumers, it's not consumers, Jesus, people, you know, operating in these, you know, these very now, Voltail is not the right word, but fast-paced environments right now where there is more that's being asked of us.
• 14:24
  SPEAKER_04: When we're thinking about leadership, though, that's something else.
• 14:27
  SPEAKER_04: So we're talking about those people that are trying to navigate and potentially get more holistic.
• 14:31
  SPEAKER_04: How about leaders now are on the other side where some of this is coming to them that's all new as well?
• 14:36
  SPEAKER_04: So they're also adjusting and trying to, you know, train these up-and-comers, make create space for them while at the same time, even kind of protecting what they have as well, right?
• 14:48
  SPEAKER_04: There's got to be a level of threat that's coming in for many leaders.
• 14:52
  SPEAKER_04: I may feel like, hey, because I'm not as close to AI, is there something that may push me out because I haven't been able to adopt a technology as quickly as others have?
• 15:00
  SPEAKER_01: I think it comes back to that relentless curiosity.
• 15:04
  SPEAKER_01: So, you know, I think it's it's very easy to slightly sort of uh AI bash and you know, you see a lot of, well, it's never going to be able to do this, it's never gonna be able to do that.
• 15:13
  SPEAKER_01: And never is a really long time in technology.
• 15:16
  SPEAKER_01: So I think you have to stay open-minded to to what it can do and stay curious.
• 15:22
  SPEAKER_01: So we have been, we talked about this through a process of building our strategy AI toolkit at Dentsu Creative, and it's been a brilliant learning curve for me.
• 15:34
  SPEAKER_01: And I think you've got to keep learning.
• 15:36
  SPEAKER_01: Doesn't matter how senior you are, you've got to keep learning, you've got to keep adapting.
• 15:41
  SPEAKER_01: And the process of building those tools has been great for me to sit with the AI experts, to sit with the UX specialists, to sit with strategists and you know, the strategy team deconstructing our practice and trying to codify that for the model is is really interesting.
• 15:59
  SPEAKER_01: Because you do sit there for a moment and you go, Well, I would do this, this, and then I'm like, hang on, why am I telling you how to do my job?
• 16:06
  SPEAKER_01: So there's definitely that moment, but you have to kind of feel that fear and kind of run with it.
• 16:11
  SPEAKER_03: Yeah, yeah.
• 16:12
  SPEAKER_03: There's when we were doing the prep call too, there's this line that or phrase you said strateg.
• 16:18
  SPEAKER_03: Like ISH.
• 16:20
  SPEAKER_03: Yeah.
• 16:20
  SPEAKER_03: In case I didn't pronounce that properly.
• 16:22
  SPEAKER_03: It was it's just been ruminating in my head, living rent-free since we spoke.
• 16:27
  SPEAKER_03: I'm like, it's such a great word because there's so much I mean we talk about AI slop all the time, but like maybe you could just talk about that and like your experience and where that came from.
• 16:37
  SPEAKER_01: Yeah, well, I think it's very like AI slop or even, you know, really nicely crafted AI content and it just looks just a little bit too polished, you know, that when someone's skin is a little bit too perfect and to you kind of there's no texture and there's no friction.
• 16:54
  SPEAKER_01: And I think you can start to see some of that in strategy where it AI gets you to an easy and very plausible answer very quickly because it's you know brilliantly trained and everything sounds quite plausible, and it's very easy to nod along and go, yeah, yeah, okay, yeah.
• 17:11
  SPEAKER_01: Categories of C sameness, you know, Gen Z value experiences over things and yeah, yeah, yeah.
• 17:16
  SPEAKER_01: Kind of tracking.
• 17:17
  SPEAKER_01: And then you sort of go by the end, nothing has stopped you and made you go, ooh, wow, do I really buy that?
• 17:22
  SPEAKER_01: Is that true?
• 17:23
  SPEAKER_01: Let's let's talk about that for a minute.
• 17:25
  SPEAKER_04: Yeah.
• 17:26
  SPEAKER_04: Well, there's also like making sure that you're thinking about like the bias checkers or learning to understand or or how do you make sure that you're looking at that contrarian prompting to push some of these models as well.
• 17:38
  SPEAKER_04: I don't know if there's anything you'd like to add to that, but it just feels like again, it's a it's a skill that you have to really start building or a muscle you want to start training.
• 17:47
  SPEAKER_04: Because without it, then it just puts everything to this median that these LLMs are just naturally good at.
• 17:54
  SPEAKER_01: Yeah, well, I think one of the the really great uses of AI in Strategy and Creative is we talk a lot about designing for difference and not scaling for sameness.
• 18:04
  SPEAKER_01: And I think because the LLMs are brilliantly trained on the you know, the the body of work in a category and they know exactly what average looks like, they are brilliant at creating those moments.
• 18:16
  SPEAKER_01: So you say, tell me all the cliches, all the conventions of this category, find me five really obvious cliches and places to go, and then find me some tensions, find me some different spaces that I could go.
• 18:32
  SPEAKER_01: So within our our tool, we have a kind of cultural tensions section where we explicitly ask it to find the cliches, find the conventions.
• 18:42
  SPEAKER_01: In our next situation, we're building out exactly that kind of blind spot finder.
• 18:46
  SPEAKER_01: What have I missed?
• 18:47
  SPEAKER_01: What is their inherent bias in what I'm looking at?
• 18:51
  SPEAKER_03: So yeah, it's interesting because then you're you're not just because AI would be great, and I've done this before.
• 18:56
  SPEAKER_03: Like, why do you keep saying things like, great idea?
• 18:59
  SPEAKER_03: I should have caught that.
• 19:01
  SPEAKER_03: Yeah, you're yeah, you're brilliant.
• 19:03
  SPEAKER_03: That's the right way to think about that.
• 19:04
  SPEAKER_03: And it keeps doing that over and over.
• 19:06
  SPEAKER_03: And then I asked it, why do you do this?
• 19:08
  SPEAKER_03: Why do you do this?
• 19:08
  SPEAKER_03: And it gets eventually comes to an answer of I had there's some really interesting answers.
• 19:13
  SPEAKER_03: One was that one of the LMs said, uh, if I were a team of science uh like a research team, I'd be the one I wouldn't be the one saying, hey, you better check the data.
• 19:23
  SPEAKER_03: I'd be the one going, keep going.
• 19:24
  SPEAKER_01: Yeah.
• 19:25
  SPEAKER_01: Yeah, that that's so interesting because I'm I I'm the one on a team who's always like, hang on, check the data.
• 19:31
  SPEAKER_01: And you know, I think in some ways AI augments your natural practice.
• 19:35
  SPEAKER_01: You know, so if I uh one of the big things I will use it for is I have a hypothesis, find me five very credible peer-reviewed sources for this, which I think something like perplexity is great for because it will go and it will find, you know, proper academic peer-accredited studies.
• 19:53
  SPEAKER_01: But yeah, it it's it is a dangerous tool for people who are not natural fact checkers.
• 19:57
  SPEAKER_01: And that's that's one of the reasons we've got to train our young folks in data hygiene and you know, what's the sample on that?
• 20:06
  SPEAKER_01: What's the source on that?
• 20:07
  SPEAKER_01: You know, when you say percentage, do you mean percentage?
• 20:10
  SPEAKER_01: Do you mean percentage points?
• 20:11
  SPEAKER_01: Really boring stuff, but if we're going to kind of be a good partner to AI, we need to ask all those things.
• 20:18
  SPEAKER_04: Can you walk us through how AI can help prevent strategic drift?
• 20:24
  SPEAKER_01: Yeah, I thought that was such an interesting question.
• 20:26
  SPEAKER_01: And I've been thinking about it this morning, and I'm wonder is I'm wondering if that's AI's job or whether that is the job of of leadership, to have that that North Star and those that very clear kind of sense of metrics.
• 20:42
  SPEAKER_01: I think that is missing in lots of cases when it comes to AI.
• 20:46
  SPEAKER_01: So we've just done a study and we're saying that actually lots of CMOs are don't quite have buyers remorse, but they are saying I invest some of the AI tools and platforms I invested in, I'm now kind of having to rethink and kind of be much more intentional about my investment.
• 21:06
  SPEAKER_01: So I don't know if AI is the the the the entity to prevent strategic drift, but I think we need incredibly key clear KPIs to prevent strategic drift in our use of AI.
• 21:21
  SPEAKER_03: I mean, you when you lose people in an organization, there's often this thing where you lose the institutional knowledge that that person contains.
• 21:29
  SPEAKER_03: And so in a way though, that we're we're in in inheriting a new employee or bringing on new employee with AI that doesn't have the institutional knowledge.
• 21:38
  SPEAKER_03: But then it it on the other hand, if people are not willing to put in that institutional knowledge to say, like, hey, this is how I do things, like you were talking about before, there's this gap.
• 21:48
  SPEAKER_03: And I think that's one of the things that kind of leads towards that drifting.
• 21:52
  SPEAKER_01: Yeah, it's a great question.
• 21:53
  SPEAKER_01: And uh yeah, I actually had some conversations this week about exactly that.
• 21:57
  SPEAKER_01: You know, how do you, as you know, talent Transitions, how do you make sure all of that inherent in start understanding of the brand is passed down and onboarded?
• 22:09
  SPEAKER_01: And I I do think that could be a really interesting use case.
• 22:13
  SPEAKER_01: So I've just been creating a a new brand book for a client, and one of the things that I'm really keen to explore is well, if we you know train an AI on this brand book and then we run our current body of work through it, how much would get through, or how much would the AI flag and say, Well, actually you said you weren't gonna do this anymore?
• 22:33
  SPEAKER_01: Which is quite interesting because those are hard conversations to have, and having a kind of objective lens on them since, well, the AI said that this is off-brand, it's uh it's gonna be interesting.
• 22:43
  SPEAKER_04: Peppering you with questions.
• 22:45
  SPEAKER_04: Unfortunately we have more.
• 22:46
  SPEAKER_04: For you, at least.
• 22:47
  SPEAKER_04: We're we're thinking about where where it can.
• 22:49
  SPEAKER_04: We're recording this at CAN.
• 22:51
  SPEAKER_04: And but you've judged can before.
• 22:53
  SPEAKER_04: Has there been a campaign that you've seen recently that you've kind of paused and been like, you know what?
• 23:00
  SPEAKER_04: AI can really help do this better.
• 23:03
  SPEAKER_04: Or like here's like AI in its in its in a great form.
• 23:07
  SPEAKER_04: Because everything that we've seen so far, even if even if we look at the Coca-Cola ad, yeah, it's like AI, but it's not great, so to speak.
• 23:16
  SPEAKER_04: Does it pass?
• 23:17
  SPEAKER_04: It passes, but but is there something that you have seen that you're like, you know what?
• 23:20
  SPEAKER_04: No, here we go.
• 23:21
  SPEAKER_04: This is where we should be headed.
• 23:23
  SPEAKER_01: Yeah, there's some work for uh it's an optometry brand in Australia.
• 23:27
  SPEAKER_01: I think it's called A Thousand and One Optometry.
• 23:29
  SPEAKER_01: And you'll see the posters actually all over the palais.
• 23:32
  SPEAKER_01: So they created a beautiful campaign last year which won, I think it was a sil a silver or a bronze in strategy, but a golden craft.
• 23:40
  SPEAKER_01: So basically they used AI to design posters that if you had a problem with your eyes, you would see the text.
• 23:48
  SPEAKER_01: It would say eye scan or eye test or whatever it might be.
• 23:51
  SPEAKER_01: If you didn't have a problem with your eyes, you would just see some very cool looking people in some cool frames.
• 23:56
  SPEAKER_01: And it just wouldn't have been possible without AI, and it's so smart and such a conversation starter.
• 24:03
  SPEAKER_01: And this year they've used AI, and I'm fascinated to go and dig around more in the technology, but they're using your camera role to detect early onset child myopia.
• 24:15
  SPEAKER_01: So analysing all the pictures you take of your child, and I don't know exactly what the details are, but using a model to to detect that before a child can really verbalize that they've got problems with their vision.
• 24:27
  SPEAKER_01: So things like that I think are absolutely fascinating.
• 24:30
  SPEAKER_03: Yeah, that's a great example.
• 24:33
  SPEAKER_01: Yeah, if you see a poster that says I scan, that you need to go and get your eyes checked, yeah.
• 24:38
  SPEAKER_03: Yeah.
• 24:42
  SPEAKER_03: I'm not sure.
• 24:43
  SPEAKER_03: I would love to say yeah, I would love to actually experience that because my eyes are terrible.
• 24:47
  SPEAKER_01: Yeah, this big billboard.
• 24:49
  SPEAKER_01: Yeah, okay, okay.
• 24:52
  SPEAKER_01: It'll say it'll save you a lot of time.
• 24:53
  SPEAKER_03: Yeah.
• 24:54
  SPEAKER_03: One of the other things too that I think is really interesting about like there is there's a concept of no bystanders, I think.
• 25:00
  SPEAKER_03: Yeah, we're like, it's we're at this point now, and V and I've talked about this a lot this week.
• 25:05
  SPEAKER_03: Almost that there's not as much about AI as a hits thought there would be here at the end of the year.
• 25:11
  SPEAKER_03: The festival.
• 25:12
  SPEAKER_03: Yeah.
• 25:12
  SPEAKER_03: Okay, interesting.
• 25:13
  SPEAKER_03: There's been a lot of it, and maybe we're just not totally exposed to it, but lots more on, I would say, creators that seems to be coming up.
• 25:21
  SPEAKER_03: And now there's digital cre or AI creators and all that kind of stuff.
• 25:24
  SPEAKER_03: But it's almost that there's it it's it's just part of the fabric.
• 25:29
  SPEAKER_03: It's kind of like talking about Microsoft Office or Word, or you know what I mean?
• 25:32
  SPEAKER_03: Oh, in a way, here anyway.
• 25:34
  SPEAKER_01: Yeah, I think there's been uh so one really interesting move I think that the the festival have made is they've introduced AI craft categories in the craft lions.
• 25:44
  SPEAKER_01: So I think that's a really important acknowledgement that there are just like any other tool, like any other kind of palette, there are brilliantly crafted ways of using the technology and less brilliantly crafted.
• 25:56
  SPEAKER_01: So I think that's a really important acknowledgement from the festival.
• 26:00
  SPEAKER_04: Is there something here as we're looking to wrap up now?
• 26:04
  SPEAKER_04: Is there something you would, you know, advise leaders as they're navigating this new environment or just marketers in general, that you'd if there's one thing they they could take away from this conversation, you know, what would that be?
• 26:16
  SPEAKER_01: I think my big theme of the week is is agency.
• 26:20
  SPEAKER_01: So w we very easily get lost in the idea that this technology is going to progress in a very logical, linear, exponential way.
• 26:30
  SPEAKER_01: And we almost talk about it as if it's evolving in a kind of organic way.
• 26:35
  SPEAKER_01: And we have choices.
• 26:37
  SPEAKER_01: Every day, organizations, governments, humans are making choices about how we use the technology.
• 26:44
  SPEAKER_01: So let's own that.
• 26:45
  SPEAKER_01: Let's stop saying AI will and start saying people enabled by AI will, because that sense of agency is incredibly important.
• 26:54
  SPEAKER_01: When people don't feel they have agency, they make, you know, bad and interesting and problematic decisions.
• 27:00
  SPEAKER_01: So that's my big, my big sort of plea is we we have agency.
• 27:04
  SPEAKER_01: This is we're making decisions every day about the future, and that's designed for the future that we want to see and live in.
• 27:11
  SPEAKER_03: Such a good distinction.
• 27:12
  SPEAKER_03: Because yeah, you're right.
• 27:13
  SPEAKER_03: Like as you just said that I'm thinking about well, AI is gonna do this, or AI, and it's like, well, AI doesn't do it on its own.
• 27:19
  SPEAKER_03: I mean, maybe agents, but that's a whole separate conference.
• 27:22
  SPEAKER_03: But I'm at least still training the agent to do something.
• 27:24
  SPEAKER_03: So I have a responsibility, I'm not a bystander.
• 27:28
  SPEAKER_01: Right.
• 27:28
  SPEAKER_01: Yeah, I mean, we we did some analysis of of the language people use around AI, and we used Claude to do it.
• 27:35
  SPEAKER_01: So there's a whole set of ironies nested in there.
• 27:37
  SPEAKER_01: But we sort of said, what when is how often is AI the agent in the sentence?
• 27:43
  SPEAKER_01: And, you know, for example, the future of work, conversations about the future of work, massively important topic.
• 27:50
  SPEAKER_01: AI is the agent in 67% of the language that we sample.
• 27:55
  SPEAKER_01: There's not a human decision maker present in that content, which is incredible, really, when you think about it.
• 28:03
  SPEAKER_04: This has been such a great conversation.
• 28:05
  SPEAKER_04: How can people find out more about you or the work that you're doing?
• 28:08
  SPEAKER_01: Uh well, I think the I think Monday's talk will be on the Can't Love the Works site, always on LinkedIn if anyone has any questions or wants to drop me a note.
• 28:17
  SPEAKER_04: Awesome.
• 28:17
  SPEAKER_04: Thanks again for your time today as well.
• 28:19
  SPEAKER_04: First of all, thank you.
• 28:19
  SPEAKER_01: That was a great conversation.