Jason, welcome to the show. So pleased to have you on today. Thanks, Richard. Thanks for having me. For starters, tell us a bit about Making Science. Sure. So Making Science is a global AI technology partner. We help brands and other agencies enable their tech and data and allow them to make their media more efficient. Excellent. Well, CMOs today are under pressure to scale campaigns faster, navigate pool fragmentation, and keep creative strategy intact. From your vantage point, what's the biggest barrier holding marketing leaders back right now? And how does AI begin to solve that? Yeah, so I think the big, there's a lot of barriers, but I think the biggest barrier is just the rate of change that's happening in the industry. AI is a a way to solve things, but also is a complicating factor, right? Because the innovation, the rate of innovation is really high. And a lot of our clients, um, and partners are big companies and big companies generally move slowly. And so when you have this massive rate of change and, and people sort of, um, scrambling for competitive differentiation, right? Always. That's just the way that business works. Um, There's just so much to explore and to learn. And there oftentimes isn't a culture of experimentation and change that needs to be in place in order for that. So I think it's just the rate of change and sort of the history of how companies have operated in the past. You mentioned that there's many big barriers. What in your mind would be the second place sort of silver medalist barrier? Yeah, so I would say that I guess the first one is rate of change, and the second one would be culture of organizations. And then maybe a third one is just AI creating this opportunity for fragmentation. There's just so much fragmentation in the media landscape in the same way that there's fragmentation with streaming services. People may be just familiar with trying to find your favorite show on different platforms. platforms right if you're if you're looking at you know netflix or hbo or whatever the case may be that similar thing is happening is trying to find your favorite uh customers uh to you know show them advertising on all the different platforms you know it's google meta tech talk uh and then you know subsets on those big platforms and as well as snapchat pinterest and now chat gpt coming up there's just so many places where you can interact with consumers because consumer behavior has changed so much. You've said that applied AI reintroduces cause and effect in marketing. Can you explain what that means and how it changes the way brands test, learn and evolve their strategies? Yeah, so great question. I think that we, at Making Science, we think about AI strategy in terms of two main buckets. One is embedded AI. and one is applied AI. And when I was at Google, I worked at Google for three years as director of data and tech for the Americas before I joined making science. And this is a term that, you know, we sort of co-opted from, from my time there. So embedded AI is the AI that big tech is inserting into its platforms. Right. And, you know, they have to, to make things more efficient for their customers. And, you know, basically everybody's their customer, you know, people don't have a choice, but to sort of, spend money on the big platforms, and then understand how they work. So embedded AI are things at Google like, for example, AI Max is a new embedded AI technology that Google's introduced. And then applied AI is all of the AI that brands and agencies and partners can acquire, learn how to use, piece together different tools that will sit on top of the big tech platforms to allow them to do more things, right? Because the big tech platforms have in their embedded AI sort of a lot of, uh, everybody can use the same thing, right? So there isn't really a way to create competitive advantage. And so we like to think of applied AI as a way to, um, to differentiate yourself, to accelerate, um, and then also to innovate. I like to say innovate in the gaps. So when you have a big tech platform that has, you know, lots of embedded AI that you use for your particular business or your particular vertical, you may have special needs. Well, you do, everybody does have special things that they need to do, you know, for their individual businesses and sort of having an applied AI strategy will help folks deal with those, you know, the intricacies of that. Interesting. That's probably why I'm using it more and more all the time and realizing it doesn't just help me with what I do. It helps me understand what I'm doing, which is an extra bonus I didn't foresee. Making Sciences Creative Hub promises marketers full control from creation to measurement to even scaling assets. What makes this tool different from the countless AI driven platforms out there today? Well, Lots of things. I'll give you a gold, silver, and bronze. Perfect. To use your earlier euphemism. So Making Science is a global public company, first of all. So that's really been a useful differentiator when talking to big brands. There's a lot of startups. There's a lot of innovation. And it's... you know, really exciting times, but a lot of times big brands want to do things that are safe, want to do things that are sort of certified and regulated. And so making science being a global public company is very helpful. And so that's one kind of overarching thing. And then as far as Creative Hub itself, Creative Hub is one tool in a suite of products called Ad Machina, which is our main product, A-D-M-A-C-H-I-N-A. AdMachina is a suite of applied AI products that sits on top of Google, Meta, and TikTok and allows brands to scale their creative, as you mentioned, into a lot of different things. AdMachina was founded in two thousand eighteen. So it's a seven year old piece of technology. It's another differentiator. It's not new. It's just been evolving. We have a robust roadmap. It was born out of text messages and then has now evolved into images and videos. So it's been a very natural evolution. There's a lot of learnings that have gone into that and a lot of two step forward and one step back type of things over the years. But we have it in a good place where it's doing a lot of really performative things for our clients. We have run over a half a billion dollars in media through this technology already, which is really a lot of scale. And we have over a hundred global clients using it from enterprise, big enterprise global marketers down to more regional marketers. And by the way, in many different verticals. So it's been used in retail, it's been used in travel, it's been used in lead generation for finance and education and several others. You mentioned images. Many creative teams worry that AI will replace rather than enhance their work. How do you see AI supporting creativity instead of diluting it, especially when assets need to be adapted across so many different formats these days? Yeah, it's a it's a great question. And you know, this, the answer is evolving, and will continue to evolve. I heard a Matt Damon, the actor say that, you know, he was worried about, you know, AI replacing acting. And I, and I think that that's something that, you know, may or may not happen, you know, down the line. I have no idea, but it's certainly, you know, people are thinking about, my point is people are thinking about lots of different ways that AI can be disruptive, you know, to their lives and their work. And I think that, you know, creatives also, you know, are all very sort of, there's a lot of back and forth on how exactly that's going to play into it. What I would say at this point, As far as images and videos brands are still very protective of their brand and protective of their you know, their, their work. And they have big legal departments that do a lot of approvals and things have to be really done carefully. I was at a conference a few months ago and I saw the CEO of David's bridal speak and she was incredible. And she was talking about how AI is changing her life and her team's lives. And it's something that they've really embraced and leaned into. But she was going through her phone one night and she saw an ad that her team had created and it was David's Bridal, B-R-I-D-L-E. So it was like a horse thing. And she was, you know, obviously went crazy and said, look, I mean, we want to be doing this generative AI stuff, but we have to be really careful about approval and human in the loop. And so I think that, you know, I think the base creatives are still very needed to be done by people today. And AI, in our case, in Creative Hub, we like to say that it just gives brands control. It allows you to scale your assets, but on the variability based off of something that's been done and approved. And so there's a human in the loop aspect to the AI where For example, there could be an image that was created and approved with legal, say for a hotel chain of one of their hotels at a beach. The creative hub can be used to resize it, to shape it into square, horizontal, vertical, etc. It can be used to add text, dynamic text on top of the ads. So it could be offers, it could be specials for different times of the year. It could be different locations, et cetera. So you can plug, a brand can plug their product feed into Creative Hub and Ad Machina in order to create massive hyper-personalization at scale, but with base creatives that have been approved by the brands. Generative AI is often framed as a content machine, kind of to the points we were just discussing there, but its real power seems to be in precision targeting. how can gen ai be used to truly personalize advertising strategies without crossing over into what i think a lot of consumers think of as sort of creepy territory yeah i think consumer behavior is that the you know um consumer behavior and preference is sort of at the core of everything that's happening in marketing where you have to you can't be creepy and you have to be relevant and you have to be personal and i think that those creepiness factor i i feel is less and less of an issue you know in my twenty years in ad tech i just i feel like people are have evolved like their expectations you know they're the privacy issue there is still that of course and people have their emails and they hold them protect them they block numbers they do all the sorts of things that that they're entitled to do but i do think that the the preference for personalization and convenience is definitely becoming bigger and bigger every day you know i'm not sure if it's tipped the scales but it's certainly on the way and so i think the creepiness factor is less important than the um the brand control that we were talking about earlier i think that generative ai can create hallucinations and all kinds of things that you know david's bridal as the example and i think that that is a bigger risk than the creepiness factor um i think brands would say that at this point and will We'll find out more here in the coming weeks. We've commissioned a Forrester report for a lot of CMOs that some of that, what we're talking about here has been asked of them is to get their opinion. So it'll be interesting to see what those results look like. Interesting. Yeah, I'm curious to see that myself. With all of these faster iterations and real-time feedback loops, what do you see as the new frontier for experimentation in marketing campaigns? Yeah, I think, experimenting with messaging, right. Is, is something that can be done much more quickly. Hyper-personalization is the new, will become the new normal. I think a lot of our clients, you know, in text ads going back seven years, um, when they got their hands on Ad Machina, they said, oh, I can, I can now, you know, write. Five hundred ads instead of fifty. Right. And I can write five thousand ads instead of five hundred and The only limit, I like to say the only limit that you have with generative AI is how many creatives do you wanna approve? If brand control is important to you, which it is for most people. So I think messaging and hyper-personalization is still only scratching the surface. I like to say that if your ads are a good listener, then you're gonna get better performance. So like if you talk to your partner or your friend and they say something to you and you say something, a little piece of what they said back to them and then add your own comments, people feel heard and it's, you know, are much more receptive. And I think that the hyper-personalization has proven over and over again, a hundred percent of the time, if you can hyper-personalize your ads based on what the user is searching for, you're going to get better results. And I think that's still at the very, very beginning. So I think experimenting with that is really exciting. And I would say, I don't know if you're going to ask me this next, but I think it evolves directly into consumer behavior again. Consumers are searching for more and more complicated things, right? Like people are asking questions now, like short queries are turning into questions. So instead of people saying like, best running shoes, right? Now they're saying, best men's trail running shoes for muddy conditions, you know, that kind of thing. And so taking like, right. I mean, I, I, I see it myself. I always tell my teams and my, my people over the years, like if you're doing it, everybody's doing it. You know, like you're just a person trying to find a pair of shoes, you know, and you say like, I have a picture in my head of what I want. but there's so much variety now. Like if I just say, you know, best shoes, like I get stuff that I wasn't thinking that I didn't want, you know? And so people are starting to like, they see with ChatGPT coming on the market, you know, a few years ago now, people are getting used to it. And they're saying like, oh, I can ask it all kinds of crazy things. I can talk to it like it's my friend or whatever. So it's like, no, I wonder what will pop out if I say best, you know, men's trail running shoes for muddy conditions. And then you get much more relevant and hyper-personalized content back. And I think that that's an area where we're just scratching. It's just the beginning. Was that an actual real-world search of your own? I'm just curious. I actually had a colleague who did that, so that's sort of what's been stuck in my head. I do work out a lot, but trail running is not my thing. Okay, well... How about you? Not lately, but I mean, you know, I'm kind of curious to go put that in and see what comes up just, you know, in case I may want to try it at some point. If you had to give one piece of advice to marketing leaders considering an AI first approach in twenty twenty five and let's face it, most of them should be, I would think, what would that be and what's at stake if they don't adapt? Yeah, great question. I think that I've been in ad tech for twenty years, as I said, and I was in Australia in the twenty tens, early in the twenty tens. And I was listening to somebody talk and he said somebody asked him a question like, when should I start this? You know, and he said, start now because you're never going to finish. And so I always remember that. I just thought it was such a clever way to say to say that. So I think considering the strategy is great. I think you have to. You know, it's required. There has to be some experimentation. There has to be some things. But I do know that there have been many reports that have come out from Accenture and others that, you know, Deloitte that say, you know, most AI projects today have failed. And I think that, you know, it's just like overinvesting without jumping, you know, not looking before you leap and investing very heavily in things that change so quickly. You know, and again, back to my slower moving organization point is like, you know, the analogy there I use is I'm from Boston originally. And the biggest public works project in the history of man at the time was the big dig where they dug a tunnel under the ground and under the harbor in Boston to make the traffic better. Well, it took ten years for them to finish it roughly, maybe a little more. And by the time they finished it, the traffic had grown so much that it was now obsolete already by the time they finished it. And so that's the same thing that can really happen to brands that move a little bit more slowly. And they say, I'm going to put fifty million dollars in this thing. And then, you know, in six months, it's like way been way surpassed. And so that's a very big danger. So I'd say the piece of advice I have is create a culture of experimentation, which I said earlier, if you don't have it already. Fail fast and small and make incremental improvements. and keep testing and learning, testing and learning, testing and learning. I think that's the best way that you can, and start now. So start now and then test and learn, fail fast, et cetera. And I know that's very cliche to say, but it's so true now, more than ever. Sort of making big bets and trying to win and installing massive applied AI platforms is really, can be really challenging and can be very risky. Last question, what marketing opportunities do you foresee arriving in twenty twenty six that have you most excited? I think the evolution of multimodal search and as we talked about and multiplatform multimodal search is very exciting. It's scary and exciting for people. But I think that getting a handle on how that's going to look you know, month by month going forward is very, very exciting. And understanding how you can fit in and how you can test and create performance and scale, you know, reach at the same time is really exciting. And I think that there was a commercial that was released. I was at Google Marketing Live in May. And Montclair, one of my favorite aspirational brands, I have no affiliation, but I just like the brand. And, um, they, they put out a commercial, uh, using VO like a hundred percent AI. If you have a chance to find it, uh, you can search for Moncler VO, uh, AI commercial mountain or something. So there's a guy that's climbing up a mountain and, and the snow is falling and he creates this big, like, like vortex of snow and everything. And the whole thing is AI, including the guy. Now the guy still looks a little bit, you know, not, not real, real to the human eye, but it's really good. It's getting closer and closer. Back to the Matt Damon comment. And I just think that like the potential and the power of AI used, you know, with experimentation and continuing to push the envelope is where the excitement is for me going forward. Excellent. Well, Jason, if one wanted to find out more about you or making science or better yet, both, where would you send them? Yeah, so I mean, people can find me on LinkedIn, Jason Downey, D O W N I E at LinkedIn. Uh, and then also, um, of course, making science.com is our, is our global website. Um, and then, uh, for advertising week, we have a very exciting session coming up on October sixth in New York. Uh, that we're, we're going to be on the innovation stage that we have a very exciting panel with, um, Forrester. moderating a panel with the head of Google Marketing Platform and the CMO of Hyundai and our Global Chief Product Officer for AdMachina and Creative Hub. And we'll be talking about Hyundai's success and experimentation with AI. And this session is titled Searching for More, How Hyundai Improved Performance on Google with Agentic AI. So that's a good session coming up and more to come. Excellent. Well, we will see you there. Thanks so much for taking part in the podcast today. Yeah, Richard. Thank you.