Chris Perry:

Cool. So I’ll try to make this brief as it goes with probably others that you have talking to you. The path isn’t linear. So I actually got into the agency scene super early. My dad ran a graphic art studio in Detroit during the heyday of marketing and advertising called on Camal, called on JWT, all the big houses turned to his shop and shops like his to essentially produce ads by hand. I joined him coming out of school right around the same time that the Mac hit the street, but also PageMaker Cork and Photoshop.

And so my weird trajectory was based on actually being automated. His whole shop actually imploded based on encoding creative technique into the software and then the agencies took a lot of that stuff. So my career trajectory now to accelerate very quickly has been seared into my mind and soul that it’s far better to be on the right side of a big tech event than on the wrong side. And we’re dealing with a mother of all call it tech transitions right now, and through the future’s work as well as consulting with clients, as well as talking with people like you guys, it’s really for me less about the marvels of the new LLMs or the new technologies and how the hell are we deploying these to create new things, not just replicate, call it the old things that we’ve always done. So there’s all kinds of stuff in between there, but that’s a bit of a bookend feeling I have right now, given some experience going through it 30 years ago and seeing what we’re all struggling with today.

Dustin Raney:

Awesome. Jason, why don’t you maybe piggyback off of Chris and introduce yourself or

Jason Snyder:

Reintroduce yourself. Yeah, I can’t believe I’m the first returning guest, so I feel I had no idea first of all. And so what an honor. So thank you guys for having me back on. You must like me a little bit, so thanks a little bit. Anyway, I’m the biggest nerd ever. I got my first computer in 1978. I was eight years old and I’ve used a computer every day of my life since then. I was an only child in northeast Ohio, and so I lived in a place with no sidewalks and there wasn’t a whole lot of other people around. So I taught myself how to use that computer and spent all my time there. My parents made the tragic mistake of buying me a modem in about 1980,

And that was it. Once I figured out I could talk to other computers and call their computers and I started to build stuff. When the Mac first came out, I wrote my first commercial piece of software in 1984, I was 14. I’d helped set up some of the first bulletin board systems on Apple, on Mac and just sort of never really looked back and I studied it and went to school for it the way I found myself into marketing and advertising. I was a part of the Silicon Alley community in New York and was a CTO at startups there. And I got a phone call from one of the very early recruiters in Silicon Alley and said, Hey, do you want to work in advertising? And I had no idea what that meant. And I turned up to an interview at Deutsche Advertising before it was owned by IPG.

And Donny and his dad were still running the agency and they needed somebody to start an interactive department. They had won a piece of business which was predicated on a pitch that was fictionalized, couldn’t execute what they had to do. And I ended up starting the interactive group over there and brought a bunch of my friends with me. And from that original group was born huge, the agency huge, and sold IPG and all this stuff. And I said, you know what? This is way better than being in a dark room with a bunch of sweaty guys writing code all day. I said, I think I can hang out with you guys. And eventually I met my wife.

Kyle Hollaway:

Awesome

Jason Snyder:

Working at these agencies. So it all worked out for me. But anyway, that’s my story.

Kyle Hollaway:

Well, great. And guys, to echo, Dustin, super honored to have you here and excited for this conversation. I don’t think we could have any more of a relevant conversation to just today’s society that we are all walks of life are trying to understand and start to grasp the importance, the relevance and the impact of AI and all the potential. And also trying to weed through a lot of the noise around it because there’s some sensationalization on one side and then other side there’s probably kind of turning a blind eye or some dismissiveness because of the fact that it is massive change and so excited to be able to talk about that. And so Chris, kind of want to lead in with you here. As we mentioned in the opening there, Dustin had mentioned you’ve got a book prospective agents and a very interesting title. Certainly that agent term is kind of really taking on a whole new life itself with agentic AI and such. You talk about this changing technological tide being this force of disruption and a new way of thinking and living. So why don’t you elaborate on that a little bit, just give us a snippet of maybe your thoughts from your book, but also just what does this mean for us and what are you trying to tell us about this?

Chris Perry:

Yeah, well, it’s going to be a long podcast. There’s a lot of territory in that question, so I’ll try to answer it. It was largely based on spending roughly 30 years trying to convey problems clients didn’t know they had or opportunities they couldn’t see before selling them the idea itself. And through that, so we went through all these call it cycles in the agency world. We started with, again, some of the stuff that Jason talked about, how do you create an interactive department in the early days? Then we had this social media which started a whole social, call it intelligence layer to the business. Then, oh my gosh, we can create brand pages on Facebook in MySpace. So we create social media practices. And so we start to go wide and pretty deep on a surface proposition that said what was created, call it in the social era 20 years ago, most companies still don’t do it well today.

It’s not because of the culture, it’s not because of the customer, it’s not because of the capability, it’s because of what’s in here versus what’s happening here. So the essence of the book is if you are going to be strategic and you are not going to get, call it whipsaw by the velocity and degree of change perspective becomes something you have to invest in. And so the book starts to take you through a journey of where maybe perspective has been off from a leadership standpoint, some pretty significant effects of that, how culture has changed, not is changing but has changed, this is an event that’s already happened. And then the third section of the book is how do you see and how do you lead differently? What’s interesting then about the name is this was actually released a year ago and the thesis with technology kind of going through it all is that we will have more agents helping us figure out how to make sense of things, how to be smart, how to do things that are relevant, put agent in the title and now agents or what everyone’s talking about.

And this things like now selling crazy. So it was a little ahead of its time in the title, but it’s actually more of a retrospective as much as a future look in terms of how much this cohabitation with technology has radically changed the game that many, many people still don’t realize yet. And you just have to look into the culture, look at the election, look at culture wars. This is all being driven by a different, call it algorithmic network orientation. And we still have people reading the newspaper or turning to cable news to help shape how they should be thinking about the world. And it’s just totally bizarre to me. So anyway, we could go down to any of those rabbit holes as much as you want, but without the right read, you’re screwed.

Dustin Raney:

Yeah, let’s actually go down that rabbit hole a little bit. I think all of us here are super intrigued and interested in the algorithm, which you said has kind of been pervasive in culture more so than I think people give it credit for. We’ve all seen the social dilemma how things can be echo chambers can be created and you not realize it. So with that being said, the power of data, I think we all are starting to understand its importance and the use of it. What things should be done to, where do you guys see this going from even a data ownership perspective and then a regulatory perspective on how it can use and how it should be used for marketing purposes. We’ll start there for that use case.

Chris Perry:

And then

Dustin Raney:

Jason, do you want to or Chris?

Chris Perry:

No, this is definitely more Jason’s territory than mine, but we should then come back around to the previous questions on this or point on this year being the year of agents, because even the way that we think about what you just mentioned, it changes when we get into this world of multi-agent AI is doing work on our behalf. So this is a pretty slippery question, but I’m curious, Jason, where you would at least start to answer that.

Jason Snyder:

So wow, I’m going, Chris is right. This could be a very long podcast. So lemme,

Kyle Hollaway:

We can break it up into multiple parts. There you go.

Jason Snyder:

Yeah, I mean it’s crazy. Number one number. The other thing I want to say before I get started is I think people who are listening to this are very fortunate. Chris is, I’m going to say this and Dustin knows I say this even if Chris isn’t here, Chris is one of the smartest guys doing this stuff. So I think people are very fortunate to hear his perspective on this and I’m personally excited to have this conversation. So let me start there. That was

Chris Perry:

So kind. Jason, can I return the compliment with your sweater?

Jason Snyder:

Thank you. Oh, you want to talk about a sweater? For those of you listening to this, I can’t see this. I’m wearing a very special sweater today. It is a holiday gift. I received it and I requested this sweater because on my sweater is if you’ve seen The Shining the film, the Shining it is the carpeting, the pattern of the carpeting from the film, the Shining, which has left a deep impression on me both from an aesthetic point of view and an emotional point of view. It’s very, very important to me, but it’s a very charming sweater and I look very handsome.

Dustin Raney:

You do, you look wonderful. And I’ll say, I think the analogy I’ll draw is that that’s what makes us human. That there’s meaning behind your sweater. And Jason, you talk about this a lot, it’s like it’s the nuance, it’s the beauty and creation and understanding and appreciation of the arts and the things that we get to do. So I’ll just throw that little sentimental thing on top of that that I think it relates, right?

Jason Snyder:

It does relate. It’s funny, I had somebody recently ask me at one of the big, and I’m going to jump around a little bit, but I will answer the question, I won’t say who they are, but it was someone who’s a very senior strategist in one of the big holding companies recently asked me, will, is AI going to kill the creative department in advertising? And my response was, no, it’s not killing creative departments. It’s going to reshuffle the deck. And this goes to some of what Chris was saying, right? The essence of creativity isn’t patterns like my sweater or in the way that AI understands the world today. It’s an inner subjectivity. And so that’s this idea of a shared, messy, deeply human experience of being alive. So AI can remix what’s been done, but it doesn’t feel joy or nostalgia or the electric charge of an idea forming between two people’s minds. It can’t do that. It can’t have a conversation like that. It doesn’t taste a childhood memory of eating asparagus or what summer smells like at the beach and it allows you to get transported back in time when that happens. It’s not Marcel Prost. So even though it can spit out your grocery list, he wrote it. It’s not the same thing.

Even with ag Agentic ai, we’re light years away from some kind of meaningful experiential intelligence. AI can predict humans experiences and advertising at its best isn’t just about prediction and recognition, it’s about resonance. So that’s why creatives aren’t going to disappear and they’ll have a new collaborator, this new entity that they’re going to partner with. And the people who are going to thrive inside of this environment are the ones who understand that creativity isn’t just about what looks right, but what feels right. And that’s the critical difference for this stuff.

Kyle Hollaway:

I love that human component to it I think is so much being dismissed at this point. Everyone’s just really, we’re talking about a technological tide, but it’s really not a tide. I mean, these are crashing waves that are just coming in at a rapid pace that in some ways is overwhelming the census, right? Every day it’s like some new aspect or spin on, wow, how do I absorb that? How do I understand that? How do I do that? But I love where you guys are really redirecting my thought patterns, which are, it’s still about the human experience and these things just become whether enablers or enhancers or agents of my own self that I can then project out. And bringing a human component in I think is a voice that’s really needed right now because of the speed at which all this stuff is happening that it’s easy to start to lose sight of that.

Dustin Raney:

And I do want to go back and touch on the area of consent and data in the algorithm. I think this is a kind of fundamental piece that we can’t overlook when we start talking about, and Chris you said, Hey, you have meta or Facebook, that was one example, right? Of where that can go in the echo chamber when you throw agents on top of it and now it’s leveraging that same stuff. It’s like when are we going to go back and address some of the things that we don’t repeat ourselves? And I think one of the things that I am kind of hounding on is how do we get from maybe that crossroads is the choice of manipulation versus participation where we collectively participate with AI and enable breakthroughs together participating in that versus the other way where it’s kind of leveraging almost people as a product. So any thoughts there? Well,

Chris Perry:

Can I start with a macro and then Jason, if you want to either chuck what I say in the trash and give us a different frame, but then get into some of the particulars that Dust’s talking about. So again, this has already happened, but I think it takes on maybe way more intention than we’re giving it as we get into AI and agents. If you think about this business has fundamentally been about entertaining, persuading, informing human beings, human to human. So call it a vertical dimension of marketing, advertising, communications. There’s a horizontal now where we have to inform machines. And so probably the easiest place to go there is SEO and content marketing and kind of flooding the system, if you will with stuff which has been explicit and call it the right leaning media sphere right now, when we take it a step further into ai, it’s training data.

So there needs to be a machine readability element of anything that we’re putting out that’s designed for machines as much as designed with great headlines and great copy and great images and all that kind of stuff. And if you think about where our clients are today, many of them global leaders for generations think about their data footprint that they have as training data to call it hit that horizontal like machine layer that ultimately is going to be the interface of the future, whether it’s through an A-G-I-L-L-M, vertical LLMs or agents that are all over the place. And if you believe in that thesis, then Dustin, the questions that you’re asking become really, really important, not only from an ethical standpoint, but from a business standpoint. Are you trying to protect your data? Are you trying to release it to the world? Are you trying to clean it up so you stand for something? It just requires a different, call it strategic in creative calculus that I just don’t see happening in the business yet, but it’s definitely happening in publishing circles because literally their livelihoods depend on their stuff being training data. So anyway, I think we’re overlooking that horizontal part as being as much or core to the equation as a lot of the creative work that we’re going to continue to do for the human to human connection that Jason was just talking about. I dunno, Jason, do you think that’s a shit view or

Jason Snyder:

No? This is the yes and moment of the podcast. I have been writing and talking about this for 20 years. This all started with spam filters. So back then if you wanted your email marketing to actually reach a person, you had to adjust your language to get through the filter.

Dustin Raney:

The

Jason Snyder:

Same principle applies today. Whoever is closest to the consumer controls the conversation. And right now it’s the machines that are closest to the consumer.

Dustin Raney:

So

Jason Snyder:

That means we’re not just marketing to people anymore and we haven’t been for quite a while. We’re marketing to machines first, machines are filtering, ranking, curating, and before a human ever sees a message, all that is happening. So those machines are talking to each other more than ever. And it’s whether brands or marketers want to believe it or realize it or not, most of the content they produce today is being ingested, ranked and decided on by machines before it ever reaches a human being. But let me be clear, I’m not saying again that machines are replacing people. People absolutely have to be at the center of everything we do. What I’m saying is that if you don’t understand the shift, if you don’t recognize that first your audience is an algorithm before it’s a person, then you are already last place in the race to connect with people.

So the brands that are going to succeed aren’t just going to optimize for machines. They’re going to know how to speak to people through machines that act as these gatekeepers of attention. And that’s the first part of it. The second part of it is none of this matters without the data because the data is the most important part of all this because that is the food with which all of this AI eats from. And so if you are feeding your child rotten food, the child is going to get sick. That is the same as what’s happening here. And Dustin and I have had some of these conversations before and I sort of say, your data is your digital DNA. And so your data is not just this trail of transactions, it’s your digital twin and it reflects your behaviors, your patterns, your vulnerabilities, and brands that understand this shift, they’re not just selling things, they’re creating value ecosystems around individuals so that every click, every search, every purchase, every question you ask an ai, right?

These aren’t just random data points, it’s you. It’s you being reflected in a digital manner. And I think of it like digital DNA, because it’s like your biological DNA that contains a blueprint of who you are. It’s your preferences, your patterns, your vulnerabilities, and the challenge becomes who owns your DNA. Because if a company owns your data, they control your digital self and the future of commerce, the future of security, of personalization. It hinges on this power shift because the best companies aren’t just collecting data, they’re participating in partnering with the consumers that are creating value from it. The data can’t be something that’s extracted from people like Dustin was saying, people, if the platform or the service is free, then you’re the product and data needs. You’re not just something to be mined, it should be something. And businesses that can embrace that mindset aren’t just going to survive. They’re going to dominate in this marketplace.

Chris Perry:

So let’s just maybe just build on that very quickly. I know we want to get into some other territory, but I feel like the stuff that we’re talking about really fits the model of we can use these tools to replicate what we do, we can use it to enhance what we do, or we can use them to create completely new call ’em territories of value. This is getting into territories of value. I’m going to flip Jason’s comment on this idea of kind of merging brand and call it customer interaction and go to the brand side for just a second. Think about brand identity. When I was in my dad’s shop 30 years ago, we did a lot of identity work. They were logos, logos and brand books. That was identity. Identity today is your data, your brand data, and it’s not only what you made, it’s how you made it.

And people on the other side are, especially from an investor standpoint, they’re not just looking for key messages or campaigns, they’re looking for anomalies, they’re looking for contradictions, they’re looking for ethical sourcing. They’re using these models to figure out what is really going on the other side of that logo. And so you really have to think about your data strategy as a way to Jason’s point of getting it through the filter. So when people then pull from that filter in whatever ways they’re looking for it, whether it’s a customer, NGO, investor, employee, you’re showing up in a way that you need to be seen in the world versus distorted, absent, or even in some cases just in a way that doesn’t reflect who you are. This is a huge shift for the industry and whoever gets there first is I would imagine going to be the next j Walter Thompson or DDB or kind of the heroic players at the beginning of the last advertising age. We’re getting you to completely new space. And just the question is, do we have the imagination and guts to be there first?

Kyle Hollaway:

So I’m all this, wow, a little bit of mind blowing going on here. So I apologize. I’m definitely feel like the dumbest guy in the room at the moment, but let’s back the train up just a little bit. You guys kind of dropped a little bomb in there that I want to go back to and kind of understand and talking about that the machines are the closest to the consumer. And you’re talking about that the machines are filtering and it’s the algorithm that, and for the brand to be able to really get through to that, to the consumer, it’s tailoring some things to the machine, the messaging so the machine can pass that through. Let’s talk a minute about the machine, about the algorithms, because I think there’s a lot of question and uncertainty and probably skepticism around who’s controlling the machine. Is the machine controlling itself?

Is it self-determining what it’s filtering and how it’s going to filter? Or are there human agents behind that that are kind of directing the machine, right? The algorithms because they’re being built and being deployed. Is it truly just from the training data aspect is how that filter is kind of tweaked, right? Because not all the filters are the same. Every machine filter is not the same filter. So something’s manipulating the filter, which then changes the messaging as it gets to the consumer, what they see, how they see it, what they hear, all that speak to give me some feedback there. Help me to understand in context of the filters, the machines that are there, how are they being managed or manipulated maybe in some ways and some of the ethics around that.

Jason Snyder:

Who wants to go first?

Chris Perry:

Maybe again, just from a framing standpoint, when we say the machine that’s singular, I don’t know if there’s a single

Kyle Hollaway:

Machines. Yeah,

Chris Perry:

Okay. So if we use, call it the two major gateways as a proxy of where we were, you have Google and you have the big social networks and you have Amazon just as like your, and those algorithms worked in a way that’s different than they’re working at the moment. So look at Google’s search enhancements, what last night it’s not or no longer you go to a search box for an answer. You’re almost going for discovery and interaction and depth. So the machines are being informed by different models then whatever the hell they were running on 10 years ago. The question then is when you get into agent discussions, will Google be, will they remain the super agent? Will the other LLMs create moats based on who they partner with? Will there be big vertical column places you go to for information, health information or entertainment? And then are there communities that are informed by agents literally being in these communities, synthesizing, surfacing, and pushing in different directions? You’re talking about three completely different use cases, primary search, vertical intelligence, and community-based interaction. And there’s agents and algorithms and technologies that are literally being built as we speak. So I don’t know if I couldn’t answer that question. Jason, could you on how they work? Because I think everyone’s literally figuring it out right now.

Jason Snyder:

So I’m going to answer it this way. I think that, so I think that the real question is isn’t who controls the machine, it’s who controls what the machine learns. In the early days of AI control was pretty straightforward. Humans trained models defined the parameters and then determined what data went into it. But today what’s happening is the AI is learning from other AI generated content. And that’s when things get really interesting because we’re entering this self reinforcing feedback loop, which is not great because that’s where AI isn’t just reflecting reality, it’s creating a new version of it. So if you think about it, AI generated text, it trains AI powered search and AI generated images, train AI vision models, AI generated music, video DeepFakes. They’re flooding the internet right now and they’re becoming the very data that future AI train on. So at what point does AI stop reflecting humanity and start manufacturing reality?

And who gets to decide which version of reality AI learns? Because that’s the question. And right now, to Chris’s point, it’s fragmented. We’ve got big tech controlling the largest models, open ai, Google, Microsoft Meta. We’ve got data scientists trying to determine the training methodologies inside of this stuff, but they’re optimizing for performance. They’re not optimizing for ethics. None of these guys, these white papers aren’t ethics forward, right? They’re efficiency forward and the machines themselves are auto training on their own outputs, which means the boundaries are no longer entirely human defined. So we’ve got to really understand in data when it comes to the data curation aspect of this, again, the data is the critical asset and all that because it’s the food that’s going inside of this. And when you have the systems and the models generating the data that they’re training themselves on, we’re standing at this edge of this huge, massively fundamental power shift from humans programming machines to machines reprogramming themselves. So if brands and businesses and policy makers don’t actively shape what the AI is learning, then they’re becoming passive participants in a world where AI dictates the rules,

Dustin Raney:

Man. So I kind of want to take this at the same question a little bit at a different angle, and you kind of touched on this, Jason. It’s like what were the algorithms tuned on? We’ve talked about this, it’s like they’re really tuned to sell more stuff. It’s like it was an advertising model. So what does it take to sell more stuff to keep you there longer? So whatever it takes in your newsfeed or whatever to keep you on the newsfeed so that eventually you see something and you buy something, is that should we rethink the models even and even rethink consent, not just consenting what data that you have that a brand can use about you, but what models you’re basically being subject to. I mean, should there be a multitude of models, models that aren’t just bent to maybe sell stuff or algorithms meant to sell stuff, but things that are meant to really give you other experiences maybe towards friendship or things that are a little lighthearted, more lighthearted, but that still is something that your brand wants to participate in because in the end it’s like you want to be able to trust.

Does that make sense?

Jason Snyder:

I want Chris to respond, but I’m just going to jump in because it’s a hot button for me and I know you’re pressing it for a reason. So consent was designed for a world where decisions were intentional, clear and human driven, and AI has changed that. And we need to stop thinking about consent as binary. It’s a realtime dynamic relationship, and it’s not a check box in it terms and conditions. It’s not this moment before you seed control and all your data disappears into the ether. This model was built for a world where interactions were explicit and predictable and human and AI doesn’t work like that. So the problem is that most people don’t fully understand what they’re consenting to because AI doesn’t just use the data you give it, it extrapolates it, it predicts, it generates new information about you from that data, and you didn’t consent to an AI deciding whether you’re a good job candidate based on your inferred personality traits. You didn’t consent to an AI generating a deep fake of your voice because you recorded a ten second voicemail. But that’s kind of like the world we live in today. So I think that we need to redefine consent from a binary thing to a organic, an organism to an organism.

Dustin Raney:

Chris, do you have anything on top of that? Do you want to add?

Chris Perry:

I might again kind of stay in the ether a bit, so I’m going to get a little philosophical for a second.

And some of this is in the book again, so it’s not something that just, again, it’s something that studied quite a bit and trying to figure out what the point of this thing is. So you remark that again, like the whole call it algorithm is about attention and those that seize the most attention win. That is a proven economic theory. Again, that created the most powerful, the richest companies. What in history based on that, if you look at it again. So that’s again going in the axis, that’s the call it the vertical or the horizontal, what’s going on on the human side. I think one of the greatest scarcities, if not the greatest scarcity right now is making sense of what is going on, which requires perspective, which requires exploration, which requires more interrogation. So now think about that through the lens of AI and LLMs and even Google’s announcement or launch last night, you don’t get the answer.

You get an exploration to try to figure out what the hell’s going on with a degree of agency. Now is that true agency based on again, how the system is surfacing answers in further prompts? I don’t know. But what becomes super interesting is when you move off of, call it the mega platforms into things that are more tailored communities. And again, to make it very explicit, you can go to Google and try to learn about a subject today and get probably a surface level understanding far more quickly than you could without it. If you use notebook LM and you essentially train notebook LM on what you feed into it, and then you open that up to others, it becomes a brain trust around a very specific topic that you have directed the data inputs. And when we have used it as a brain trust, not as again, a gimmicky kind of podcast summarizer, it is extraordinary, not just in terms of call it simulated synthesis or imagination, then we layer our creativity in our creative imagination on top of it to figure out what the hell are the new questions and new avenues based on a body of work that could become really thick if you load this thing up.

So to me, sense making perspective, huge scarcity, you’re seeing a push into deeper search and discovery through the big models, but you’re seeing incredible capability with those that know how to use it on call at the small language side and how this all evolves. No one knows, but man is there really, really cool ways of exploring and experimenting with what’s being thrown out there every day.

Kyle Hollaway:

So playing off of that, then our listeners are in the marketing advertising ecosystem primarily. That’s where we’re targeted. So come out of the ether a little bit, bring some practicality to it. And for a practitioner today, what would you be telling them today to do? What are some practical next steps or practical things they need to be addressing and not reacting out of fear or ignorance, but just saying like, Hey, your job isn’t necessarily going away. It may be changing, but it’s not going away. What can you lean into?

Jason Snyder:

I mean, I think you got to get tactical, right? I mean, we’ve talked about, to Chris’s point, we spent a lot of time in the ether today talking about really big ideas, and some of them are scary ideas to a lot of people. But I think a lot of it, for me, it’s all going to come back to the data for me at the end of the day. The thing is, machines don’t have opinions. They only reflect on the data they’re trained on. So if you are not actively shaping the data that trains ai, someone else is doing it for you. So whether you are a brand or you’re an agency or you’re an individual at anywhere along that macro, you got to understand that. You got to understand how you can gain control of that in that context. And I would go back to the point I was making, and that’s again, what I think Chris just described, right, is that AI is not going to take your job, right?

This is a partner, right? It’s someone who knows how to use AI as a partner that’s going to take your job. The smartest people in any industry aren’t asking that question. They’re saying, how do I make AI my most powerful partner? And we’ve got to stop thinking about AI as a competitor and start thinking about it as a partner and not replacing people. It’s amplifying the best of what people can do, and the people who are going to win in this new environment, in this new world are the ones who are going to know how to make it work with them and not against them.

Chris Perry:

So I’m going to get super, super tactical, and I’m going to start with just a quick metaphor and then we’ll get into maybe some steps to think about. So Weber plays in the communication space, if the, call it the 32nd spot was synonymous with ad agencies, the press release is synonymous with communications agencies. Chachi, PT drops, what happens? Oh my God, I can write a press release in about 10 seconds and it does like 80% of the job. Oh my God, what does that mean? Versus asking the question, what’s the purpose of a press release these days? What’s the purpose of it? The form factor itself, and optimizing that is optimizing the wrong thing. So what do we start to make that reflects how people communicate and what they need in terms of information to convey stories? It’s very different in an AI context than a magazine or a broadcast context.

Alright? So if you start with that, if you don’t have the right sensibilities at the base, you’re dead before you started. So you have to train yourself, no matter how scary it is to see reality for what it is. That’s why I wrote the book. The book is not about ai, it’s about the sensibilities to step into an AI environment. Next up, if you’re going to participate going forward, you have to use these things and not just use ’em in a superficial way. You have to understand the grammar of what it’s like to work with a notebook LM versus a open eye, open AI O three model versus a midjourney. It’s totally different and it’s not something you can do by going to a two day prompt class. So it doesn’t matter how busy you are, you have to either dedicate the time personally or hammer on your teams and your managers to say, we need to be incorporating these more we with the guardrails and the foundations and guidelines in place.

And then the next level is ask the question, are we replicating what we do or are we creating something new? Our clients buy creativity from us, and there are lots of examples popping up all over the place. New form factors, new art forms, new ways of using data, new ways of simulating strategy. I mean, I don’t have enough fingers to go through amazing new use cases, but if you are still using old assumptions for a new world, it doesn’t matter what you’re playing with, it doesn’t matter. So when I said again, in our pregame, we have a lot of work to do, it’s individually, we have a lot of work to do and collectively, but those that want to be part of it, I think are going to be living through a really exciting time, not those that are playing defense. And there’s a lot of defense being played right now at all levels of our business and everyone else’s businesses right now.

Jason Snyder:

And I just want to build on that from an experiential marketing point of view, because the point Chris makes from a Weber standpoint, from a momentum standpoint is not dissimilar, right? For me, immersive experiences today, the line between digital and physical has disappeared, right? So we don’t just consume content, we live inside of it, and the brands that are winning are the ones that are turning experiences into ecosystems. Because today, from experiential marketing standpoint, we want to build experiences. We are building experiences that adapt to people in environments in real time. So we can go beyond personalization into this kind of notion of what I frame out as adaptive intelligence where AI and spatial computing create environments that learn and evolve with one another so that we’re shifting from engagement to immersion and people expect interactive, responsive, hyper personalized experiences at all the activations that we do.

And that can be in the physical world, it can be in a digital space, or it can be in a mixed reality environment like we do at stadiums and concerts and things like that. So the brands that are winning inside of this, the sponsors that are winning inside of this, the people that are doing the shopper marketing or the retail commerce, they’re not just creating campaigns, they’re building ecosystems where people aren’t just consuming content, but they’re shaping it, they’re interacting it, they’re existing within it. And the challenge isn’t just about reaching people anymore, it’s about creating experiences that people can step inside of.

Chris Perry:

So let’s take that one step further. And again, this isn’t like in the future. There are capabilities and models that are in place right now. What happens when you start to think about marketing as an expense versus an asset? So in the world that Jason is talking about, you create these ecosystems and you start selling new stuff, there’s a growth strategy that pays for itself. Training data, especially high call it quality training data. It’s extraordinarily valuable. How many brands are talking to these middleware gatekeepers on trainers to use the same leverage that some of the publishers have brought to extract quite a bit of value, not in the media as call it typical content, but as data. So if you change your, you can also change how we think about what we do economically. And that’s why again, more people experimenting, more people creating new ideas and more people asking different questions could change parts of our business model, which obviously needs to be thought through as well, given automation on one side, but maybe new value creation on the other. So that’s why it’s, it’s a super exciting time, but more people have to be in the game.

Dustin Raney:

Yeah. Chris, I kind of want to go back to something you said earlier. I think summarizes a lot of this in a really cool way. Mean, you were talking about your past and how growing up brand was a logo and now brand is data and hearing Jason talk about the future, the immersive experience. And if you think about even chatbots autonomously leveraging data to speak to you, well, that’s a brand voice. It’s got, it’s representing your brand. All these things represent your brand, but they’re new things, more immersive ways to convey a person, a persona, because that’s really what a brand is. And it takes data to inform that voice. And it’s literally, we’re getting closer and closer to this kind of, I go back to the Yola convenience store model where they knew who you were when you walked in the store and it was a very personal experience. It’s almost like it’s coming full circle to where that’s going to become possible again. But how you do that and how you leverage the data to inform your brand is becoming absolutely critical, right?

Chris Perry:

Or market,

Dustin Raney:

Do that with dignity.

Chris Perry:

Think about the amount of r and d that sits inside of our clients around the world, generations of r and d, whether it’s engineering, health, retail, every category, and what is the marketplace for r and d, it’s academic thought papers, media interpreters, a little bit on obviously the corporate side of the think tank stuff. What if that data was unleashed and people started to build off of generations of research work that using AI could take that foundation to a whole new level in terms of solving problems, creating novelty, and forming the market leading. It’s not just, can you buy the widget from me? Do you trust what went into the widget that has a lot of in depth research development, creativity, experimentation that probably is better suited for a company to convey versus mediated through all the expert filters we had in the previous generation, right?

Dustin Raney:

Yeah, totally. It wasn’t healthcare, I mean, just the breakthroughs that this could solve specifically in that market if done correctly. If done correctly. Well, I know we could, honestly, I wish this was an ongoing series. We could do this. I think the four of us could talk about this man in so many different avenues. And there’s so much more I want to talk about with you guys. So we might have to, Jason, you might be a three-peat zoom

Kyle Hollaway:

About, say

Dustin Raney:

Part two, part three, part four. Let’s go

Jason Snyder:

Let, and if you can get a bourbon sponsor, that’d be great.

Dustin Raney:

Okay. That’d be another first. I do want to throw out that, Jason, just a little quick promo. Jason and I are actually speaking in Atlanta next week at the Forays decision conference, and we’re going to be talking a lot about some of these kind of core topics around data ethics, consent, the future of AI

Jason Snyder:

And legislation too.

Dustin Raney:

Yeah, absolutely. So we look forward to seeing people there at that event. These are obviously, it’s a very passionate, we’re very passionate about this topic. All of us, Kyle and I, we’re identity wonks. We always call ourselves that, but it’s human psychology at scale, really, and we have creative, all this comes together and there’s just so much to talk about and so many exciting things, but also very serious things. So I think that’s thematically where we land today, is Chris and Jason. Thank you guys so much for giving your time to us. To our audience, fascinating conversation. Please everyone go out to Amazon and pick up Chris’s book. Again, it’s the Prospective Agents, A Human Guide to Autonomous Age. I think you guys will, you already heard that in depth knowledge that he holds. He’s really an expert in this field like none other. And then Jason as well, go out to Forbes, check out Jason Snyder, a lot of the stuff that he’s pushing out there. Kyle, is there anything else that we want to touch on before we give it a wrap?

Kyle Hollaway:

No, I think that covers a lot of it. I would encourage folks, feel free to comment on the podcast listing on our Acxiom.com, and we can take some of that in. Speaking of data, let’s ingest some data that can help Taylor our next conversation. So appreciate you guys being here. Absolutely. I know we’ll have some more of these conversations because again, the rate at which all of this is evolving and revolutionizing things is incredible, and so plenty of fodder for conversation.

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