Building Brand Gravity Podcast

Dan Nestle: [00:00:00] The big problem is thinking about we need to get this into the times. We need to get this into the Wall Street Journal. We have to get this covered by the ft. Stop that and think about, I need to reach these stakeholders. What are they reading? I need to reach these people. What are they watching? You're gonna find that they have multiple and dynamic reading and and viewing habits soon.

Anne Green: Hello and welcome to Building Brand Gravity. I'm Anne Green, CEO of G&S Integrated Marketing Communications Group.

Steve Halsey: And I'm Steve Halsey, the Chief Growth Officer. And Anne, we've got a lot to talk about today. Two topics that are not only timely, but I think they're really deeply connected. Talking about AI's growing impact on discovery, traffic, and search behavior.

And talk about what that means for the future of earned media. And yes, it is true. PR is having another. Moment. It's great to be in an [00:01:00] industry that constantly reinvents itself with moments and just when the critics are ready yet again to declare the press release. Dead surprise. Turns out large language models kinda like 'em.

I mean, maybe not for click, but definitely for context. So no, the press release, my friends is not dead. It's very undead. It's a corporate zombie, quietly writing its own metadata. And as it turns out, Ann, that's not a bad thing.

Anne Green: It's so funny. You know, everything old is new again. I was telling Steve the other day for our listeners that I've worked in financial services for years and was walking with a colleague, passed a bank branch that has a cafe in it.

I'm like, well, that was there 20 years ago and they're doing it again. But, um, you know, it's interesting, this whole discussion reminds me of, of an event I was at. Last week we got invited to, it was an invite only event, um, by some of the folks from the PE firm, human Ventures, and it was called Media and Brands in a post traffic world.

And it was really high level audience you [00:02:00] had. CEOs or you know, leaders from a lot of media brands like Forbes and Adweek and, and New York Times. And you also had brands like Paramount. They've been in the news a lot. You had Meredith, um, Meredith, you had a lot of advertisers. CloudFlare was there, which was quite interesting because of some of the work they've been doing lately to help gate, um, content for Meredith.

And I think the whole discussion of the event was really zero click search that traffic is going off a cliff. This future that many had predicted and prepared for is happening right now, and it's happening very, very, very fast. And this was a room of very smart people. You could tell a lot of them had just been at CAN and France and a lot of folks knew each other and you know, we were there also as G&S, but Edelman was also there.

So there weren't, weren't as many of the integrated comms firms there. But I think for me, the point of view is just. Underscoring how fast this world is changing, which I think has paired with how fast the dialogue [00:03:00] has risen and intensified around the earned media side of this, which I think is really fascinating.

Steve Halsey: Yeah. You know, and I, I think just you, you, you talk about who was in that room and it just really reinforces what a turning point where we're at. You know, not just for how stories are told, but for how they're found trusted, reused by both humans and machines, and, and that's the part that's different. You know, and what we used to think of as earned media, you know, placement in a publication, quoting a story, maybe even a backlink, is really being reframed by how AI.

Basically gathers and synthesizes the information, and that's really raising the stake for us in comms and, and PR in a big way. So basically, if an, as I understand it, if an article isn't structured in a way that makes it machine readable, like clear attribution, topical clarity, things like that. And it may never make it into the next AI generated summary [00:04:00] or insight somebody sees.

And when Greg Galant was, uh, was on the podcast a few episode, he put it really well when he said. The value of PR isn't just in impressions anymore. It's about compounding credibility, meaning how earned media actually becomes training data for the system that shape public perception. So. A great media hit.

Today isn't necessarily one that's just a short-term win, but it's one that creates long-term brand value. By showing up on knowledge panels, AI generated answers, even influence how search may evolve. So in a lot of ways, that makes the earned media part of what we do. Way more strategic in a lot of ways, way more durable.

Than it was even 18 months ago.

Anne Green: I couldn't agree more and it, I'm glad that you're calling back to Greg 'cause that two part episode on dealing in with AI enablement was a [00:05:00] good listen if people wouldn't go check that out. You know, we always encourage people to go back and see the archives, but. A couple of things.

You know, one is AI is sort of a double-edged sword, obviously for media that post traffic environment for media publishers is really problematic, right? So that was a lot of what the energy in that room was about. And there's a lot of other stuff happening with ai like flop at scale, coming into reporters, inboxes and, and overwhelming people with marketing messages, also phishing schemes and at scale, but, but on the other side, the kind of energy.

Optimism and excitement around regenerative engine optimization. By the way, in the room, everyone agreed GEO is winning versus AIO and all the other acronyms, but so that, that was good to know. That's one clarity there for us all in an unclear world. But I think that the excitement around what this means, let's say for trade magazine publishers, these are.

Entities that have been under a lot of pressure over the years, but they have tremendous authority and domain knowledge [00:06:00] in, in their sectors. Whether we work in ag or healthcare, they create events, they create multimedia, you know, podcasts, video, you know, they're doing in-person events, and the fact that.

We can say to our clients now, it's gonna be really incumbent upon us to understand how different LLMs are gathering their information and indexing it, like you said, in different ways and understanding what does that mean for how our audiences are interacting. Are they on Android phones or mobile phones?

Like you know, which LLM might be the dominant one for them. Um, the fact that OpenAI uses Bing. I mean, all of this stuff is so interesting and we really, really have to be on top of it. And one recommendation I'd make for listeners is PR Council has a great podcast series, quick hits called AI Loves pr, and these are, you know, 13 15, 18 minute real quick.

Podcasts with different experts who are very, very germane to this conversation. So I definitely recommend people check it out.

Steve Halsey: Yeah, so I guess it, you know, play with the acronym. If your [00:07:00] CEO's focused on GEO, then, then that firm's going to win. Right? At least that's what we're doing here on, uh, on, on G&S and is, is really.

For, uh, asking us to lean really deeply into GEO basically as an evolution. Not so much as, as SEO, but really an evolution, just how the entire media landscape is changing. And again, I I oversimplify things. So while SEO really focuses on keywords and backlinks, things like that. GEO is really focused on credibility.

It's on how you structure the story. It's about relevance. It's all those things that the LLMs use basically to gauge and generate, generate responses. And for me, the kicker of all this is that most of that data is earned. It's how we talk naturally. Editorial content, trusted media, industry blogs, because.

Everything I'm seeing is that the large language models love high authority sources. Right. [00:08:00] And that has always been a key part of the earned media was there's a lot of value in being direct and going direct, having people know it's coming from you. But having that third party credibility and having your brand showed up that way gets it repeated, reference referenced, retrieved all things that are really key in terms of the, the earned media where again.

Now we're starting to see an environment where visibility becomes velocity and, and I know there's a lot of challenges with the shrinking newsrooms and everything else, but there is so much power in earned media and making. That part of PR more relevant and more strategic than ever.

Anne Green: Yeah, and there's still gonna be such a need for that peso model.

We're very committed to integration, and I think we see where paid comes in, where owned comes in, where earned comes in. But it's just a new dimension to the conversation. I mean. This is a great segue if, unless there's any, anything else you wanna add before I segue in to set up our interview [00:09:00] for today?

Steve Halsey: I think that captures it. The press release is not dead and uh, you know, for those, uh, for, for those groups that have gotten away from the value of earned media, it's more important than ever. Yeah.

Anne Green: And, and that's why I wanted to talk to our guests. You know, I had a great conversation today, you know, that we're gonna cut into right now with Dan Nestle.

Who has worked as a comms pro for years. And I'll, I'll do more of an introduction when I, when I get with him. But I would flag the fact that we're talking about earned attention. And what does that mean? What's the quality of attention? And attention as not a commodity? It's really a precious capital.

People like Ezra Klein are talking about that people like Chris Hayes have written books around, um, attention being under pressure. And so the idea of where we look at the evolution of earned media. Relative to attention and what does that mean for the media landscape as a whole? You know, Dan has some interesting things to say.

So let's, uh, let's cut over and hear that conversation. So my main hope always for this podcast is to have some really deep conversations with [00:10:00] smart and fun and interesting people on topics that really matter to communications and marketers, and I would say curious humans in general. And this conversation is very much motivated by two trends, which is the evolution of earned media as a practice.

The evolution of media itself, by the way, and then the rise of what some are calling the attention economy. And so, no surprise, my guest is deep in these hot topics. I'm thrilled to welcome Dan Nestle, who excels at the intersection of communications and technology and leadership. And you are a communications leader and strategist.

Dan, I don't have to tell you this, and a podcaster and a lot of insights in this field. Really deep on ai, really deep on what we're gonna talk about today, which is earned attention and sort of that evolution of what we've practiced for a long time, which is earned media. And, um, you know, you're the founder also of Inquisitive communications and host of the Trending Communicator, which I've been honored to be a guest on, and I really encourage people to check it out.

But Dan, welcome to Building Brand Gravity.

Dan Nestle: Thanks, Anne. It is an honor. [00:11:00] I'm glad to be here. Gosh. I mean, last time we had, we were behind the mic with one another was almost exactly a year ago on my show. And, um, and yeah, and it's so amazing to see how much has changed, how much hasn't. Um, and, you know, we're gonna, I know we're gonna talk about ai, it's been driving a lot of that change, but it hasn't been the only driver.

And I think that's, you know, there's the, people forget that it's a thing. It's not the thing. And, um. We need to talk about the attention economy, as you said, the, the, the profession as a whole. And you know, of course weave in AI into it if, you know, if, uh, if that makes sense to do so. And I think it always does so

Anne Green: well.

To get us started, I've been thinking a lot about a paradox. Or I'm identifying is that paradox you can help me decide if it is, which is, it feels like in some ways earned media due to the media itself being under tremendous pressure is under pressure and the practice is under a lot of pressure. Um, but at the same [00:12:00] time, there's all this discussion and energy and excitement.

Also related to a AI, AI about earned media and media itself being on the brink of a renaissance. And both of these realities are tied to media fragmentation, but they're also tied to the proliferation of AI in all its forms. So you know, you've got the AI content at scale and slop and crap, and zero click search and traffic going off a cliff and things like that.

But you also have the way that large language models are pulling and organizing information, serving as the new search, new discovery. Really honoring and pulling from sources that tend to lean more into the world of earned media and the practices we've done. So this is a big question, but what's your overall take on this moment of time?

And is this a paradox in your mind?

Dan Nestle: I, I think it's, it's. I, I agree with you. It is a, it is a paradox of sorts, and I think that paradox lives mostly in our heads, uh, rather than in reality because of, you know, what you'd normally [00:13:00] see when, when any industry is disrupted, you have, uh, legacy mindsets and forward thinking mindsets.

And it's not, I'm not, I'm not being judgy about it. It's just that's kind of the way it is where. The approach to media relations and our, and our kind of inherent ranking of media. You know, like this is top tier, this is mid tier, this is whatever, and there you have the trades and you have different categories.

And categorizations is being turned upside down in a lot of ways. And, um, it's a lot to cope with. And there's still a lot of, I think whether it's cognitive dissonance or whether it's just straight up, um, no. The, the only authority is the New York Times, wall Street Journal, LA Times, you know, et cetera. Um, mindset.

I, I don't know what the answer is, but, but I think that that is, you know, that's sort of our reality now where it's, where everything's jumbled, priorities are jumbled, and [00:14:00] there's a very, I think there's a question of what is valuable and what isn't in terms of. The media coverage and in terms of what counts for earned attention.

Anne Green: That's really helpful. You've asserted, you know, and I, I, I'd love to hear thoughts on this, that traditional media relations is in some ways, not just outdated. Potentially broken or kind of even harmful sometimes just strategic objectives. And I think that has everything to do with how it's framed. But what, when you say that, what are the things you're seeing that seem, wow, this is really counter to what we're actually trying to achieve potentially for a given organization?

Dan Nestle: I think it's, it's mostly about, uh, entrenched. Uh, values and attitudes about what makes good media and what, what does media coverage mean on the one hand? Right? And on the other hand, I think it's also about the fracturing of the media and the audience environment. And, um, I have to, like, I think I have to be, I have to give full disclosure here and, and be brutally honest about my own biases [00:15:00] here, because, you know, being in corporate comms for 20 something years and, and, um, having a stint at at, at agency in the middle.

Um, it always, it was always the case that the executive teams that I was serving or my, or working in partnership with when I was in corporate, um, the only real wins that they understood from their PR teams and from their comms teams were, Hey, we got the CEO in the fill in the blank media. Right. Oh, the CEO is gonna do, there's gonna be a feature on the CEO in, um, in the, in the New York Times.

There's gonna be a feature from the CEO in Barron's. Um, we got, we lined up all these wonderful interviews for the CEO visit next week, and here's where we're taking him by limousine to Bloomberg, to, to, to, uh, you know, to, to the Wall Street Journal, to wherever, right. Uh, we didn't do ourselves any favors, as in, [00:16:00] as a profession, in pushing that as, as CC, we're doing all this great work for you.

Um, and these are the results that we have. And I think that was the case for a long time. So the pressure never ceased and I think it still continues to get that kind of coverage, but also we didn't resist so much. You know, I think that it was harder for. For PR and comms folks to say, well, the CEO's time, the CEO's gonna be here.

We have a day for him or her. Not every CEO is is like Jensen Wang or, or Elon Musk, or you know, Andy Jassy or whatever. So you, you know, you have to have a reality check when your CEO or, or any high level executive is in town, um, and really be self-aware. Where you stand in the corporate pantheon and whether what you're saying is newsworthy or not.

And sometimes those, the answers to those questions [00:17:00] are not quite authentic or honest internally in an organization.

Anne Green: It's so funny because we're, we're gonna be talking quite a bit about the evolution of technology and platforms and processes that, you know, are really changing the game there. You're speaking about something that's so pervasive over so many years and is in some ways very analog.

It's that human perception of value and how is it that public relations is a practice or media, whatever we wanna call it, expresses that value. And that was something I was thinking about in reading one of your issues. You have the trending communicator, both a podcast and a newsletter. And the issue before the last, the one that just came out recently, the one before was about this question of.

Like building on your prior one and earned attention. It was, it was looking at a McKinsey study about, oh, they've discovered this too, you know, the quality of attention. But before, and I wanna ask you about that, but, and we will get to the technology of it all. 'cause [00:18:00] it's really, really germane and it's changing the thing.

But I, I wanna reflect on my own career where you're right, it's like there is this hierarchical value judgment. And it's not always, uh, it's always a qualitative subjective conversation. And yes, we have a lot of data of why the New York Times drives so much, and that that's really, really meaningful and that can be meaningful to most, you know, enterprises if you're in there.

But I remember back with consumer brands at an earlier decade, you know, I used to joke about the O word, which is, please don't say Oprah to me. You know, this was before it was fully like, don't use the O word. Don't use the O. But it was these things that we put up on a pedestal. And the reason that I'm bringing this up now is I've seen some clients over the past decade or so start to, I.

Almost devalue or not recognize in, in executive teams how critical trade media as a category continues to be, or those young reporters at the trade media where you have the chance to train them and inform them and help them [00:19:00] versus I don't have time to talk to that person. So, you know, I think what you're saying, Dan, if I'm correct, is that, you know, these old school pressures and tensions and tropes are still very active today.

Right? And we've gotta look at that again.

Dan Nestle: I think so, and, and you know, those, those tropes or those kind of belief systems, what somebody had once sent to me a long time ago in a completely unrelated topic, that our biggest enemy is not. You know, is not externally. It's our, it's our own bs, it's our own belief systems, you know, and, uh, I think that applies to a lot of, a lot of legacy organizations in the profession for sure.

And I know that agencies have been really pushing the envelope with technology and with kind of, you know, with new developments. But I don't see it always getting, getting through to. The, uh, to the cl clients or to pro, to potential clients or, or to, certainly to large organizations that, that don't have to worry about things like [00:20:00] awareness.

Right. I mean, it, like, I, I think we gotta be clear that when I say, and maybe when anybody says that, um, you know, media relations is really. Uh, well, I, I, my exact words were it's dying and we need to let it go. But that, you know, that is, that's a very, a little, I'm a little polemic about it, but the, I think we, we just have to understand that we're talking about the vast majority of PR of practitioners and companies.

We're not talking about, you know, your Fortune 10 or 50 or a hundred because they have different needs. They're already in the awareness game, uh, and they have that. You know, if you have a very heavy financial and, and you know, investor relations function and you know, you need to be, you're constantly in the media's eye for any move you make with employment or with, you know, with your finances, et cetera.

Your media relations need to be really strong. I don't know if your approach. Needs is would be the same or should be the same. In fact, I would, I would advocate you'd wanna [00:21:00] spread out a little bit more to different outlets, but you do need a strong media function.

Anne Green: You talked about earned attention, which got my attention because earned media earned attention.

And the reason is before we get into earned attention specifically. This whole concept of attention is very of the moment. I feel I'm hearing discussions about it everywhere. Ezra Klein has talked about. Today's most valuable capital is attention. Chris Hayes of MSNBC just published a book. I love the title.

It's the Sirens Call, how Attention Became the World's Most Endangered Resource. So. Endangered resource, valuable capital. That title says a lot. So when you think about attention, and then we'll go to earned attention, how do you think about the concept of attention today? Attention as an entity, as capital.

Dan Nestle: It's where, it's where you're putting your eyeballs. So, uh, you know, you have choice, you have more choice than ever before, uh, on, on where you spend your time for your media consumption or for your, you know, for your [00:22:00] entertainment or whatever it's online. So what is taking your, what is attracting your eyeballs at a particular time?

I think you can, I'm sure there are studies or I'll, I'll, I would imagine that, uh, there are thinkers out there who are saying, if you attract somebody. Three times to your website or to your, to your article, then we can count that as attention. Now, I, I don't get that deep about this 'cause I don't know what the answer is, but I, I would imagine that, uh, you know, that some consistency needs to be there for, for us to really say, okay, we have your attention.

You know, we throw up a, a, a. Crazy advertisement somewhere that's, that attracts eyeballs, you know, on the side of a building or drones in the air. Boy are we getting attention, right? Um, but if that attention is not attached to a brand or to a person or to something else, then it's kind of fleeting and it does, it's sort of, sort of meaningless.

It's [00:23:00] really more about, it's more about, okay, is our content or our proposition. Or what? Or our outdoor activation even what, whatever it is, is it worth someone's time where they come and look at it and spend a little bit of time on it? And that's where attention starts. Then they have to make an association with that and your brand or your person.

And I don't think you can isolate one from the other because otherwise it's impressions and those are, you know, that's kind of meaningless. What we want is somebody comes. They read your stuff. They look at your, uh, at your, they, they look at, at your, at your video. They watch your video. They, they spend a little time with you.

So then, okay, we can say, all right, we've started. Okay. That's one type of attention, but the other one is. I really need to learn about something. I really need to understand about something. It's not been any different from, from directed search or something like [00:24:00] this where you, you know, you're moving a little further down the, the funnel, which may or may not be outdated.

Anne Green: You, you're making me think of that the marketing funnel is, as you were alluding to, and where it's still really resonates and where it translates across disciplines, but mm-hmm. In, um, when you were in your last newsletter, when you were talking about McKinsey, you know, they, they were talking about attention as well, and, and you're reminding me of a separating attention quality.

Yeah. From quantity, right. Driving business outcomes. And you also in that same newsletter and people should go check it out. We're talking about that question of what drives. Intent or behavior. Yeah. And I think that in the comms world, and you know, a firm like mine is integrated marketing communications, so we kind of touch different pieces of it.

But we started as a communications firm. And I think where you start, um, is in your DNA, that question of can we measure, you know, maybe use the marketing language of conversion or intent mm-hmm. Or things like that. But what is your thought about [00:25:00] how. In this new world of earned attention, how we start to think about quality versus quantity.

And quantity could be like size of outlet, but it may not be the quality. Yeah. How do you start to parse that in your own mind, Dan?

Dan Nestle: Well, I think you, you have to marry the marketing to the, to the communications for that to be understood. You know, it's, that is really where you don't know whether it's, whether it's quality attention, when some, when your target or your customer or your stakeholder first, first grabs onto your, to what you're putting out there to your content.

You just have to understand that you need consistency in your content to kind of weed out. Well, there's two, two functions. First is, of course, to present your position and be more and, and, and promote awareness and, you know, make sure that your, your message is getting into the channels and in front of the people that it needs to be in front of.

That's your part. The quality attention part is like paying attention to how people are interacting with that content and then seeing, okay, [00:26:00] well this one's resonating, this one isn't. And that's, you know, from one side of the equation you can turn up or turn down dials and, and change your message. But on the other side of the equation, you have to think, okay, is it resonating because, is it not resonating because, um, the timing's off or because it's in the wrong channel or because it's the wrong audience?

Or is it not resonating because it's really. Part of my language. It's crap, right? I mean, you have to, you know, you have to figure it out. And then when it does resonate again, is it, is it hitting for the right reasons? Did something like go, well, I hate say, I hate this phrase, but did it go viral? Like did it hit hard because you know, you've said something or you've written something that is, that is worth that, that virality, or did it go viral?

Because there's something in your content that actually. Is completely different than what you intended. Maybe there's a, maybe something funnier, or maybe it's a, you know, you start a new meme or who, who knows what it is. [00:27:00] But you know, is it getting the attention, it's getting for the right reasons. And the only way to really know that is to look, is to be consistent, is consistent with your output.

And start looking at who's coming back over time. And from those people who are coming back over time. Um. That's where you're going to see those quality, that quality attention, like the, the, the, the audiences that keep coming back, and then the audiences that, that take action based on what you do. Now.

That, and that's a whole, that's another kind of point, is, okay, are they taking action? Are they doing something based on what you're putting out there? And that's where the marketing side of everything kind of comes in. But it should be our, it should be also in the comms, in the comms. World to measure that the reaction, the engagement metrics are one thing, but is there a actual call to action in your, in your piece or in your content that they can [00:28:00] follow?

Is there a way to measure that? There always should be, of course. And that's kind of where the quality part of the attention comes in. It's more, it's more of the measurable part. Um, so you know, there's a qualitative. If there's a qualitative way to look at quality, quality attention, I suppose. But there's also quantitative ways, and I think we need to cross both of those.

Anne Green: Yeah. And how we marry that together. I mean, I feel like all the disciplines of marketing and comms have moved closer together over time, but there's still different silos there. Um, it was interesting you were commenting on some of the audience segmentation. McKinsey was suggesting. Yeah. They had an about nine, eight, or nine or so, and you picked out a couple, like content lovers.

Interactivity enthusiast and community trendsetters. And that struck me. There's, you know, as people who've made up a million names for audience segments over time as we do. Yeah. You know, they, they are made up and subjective, but they also have reality and research behind them and power behind them. And I think what was interesting to me is these seem to be quite.[00:29:00]

Attention based segments. What kind of attention? And, you know, each of us are fans of something. You know, I have, like, I've been a fan of Sherlock Holmes since I was a child. So all aspects of Sherlock Holmes. That means I listen to a very niche podcast that covers the Granada Sherlock Holmes series from the eighties with Jeremy.

Brett. And I'm just like a person that's into that. Yeah.

Dan Nestle: Rather. It's a good microsegment. Very, it's

Anne Green: a microsegment and, and there's more people out there than I realize when I discovered this podcast. You know, how should, I don't think, we've never thought in terms of these kinds of segments before, but how do these attention based segmentation feel fresh to you or feels like something to be revisited and reflect on?

Dan Nestle: I think it's, I mean, that's a good question. I, I'm fundamentally in favor of breaking down our audiences in any measurable chunks that we possibly can 'cause. It gives you the intel and the insight to know which channels you can use and what kind of content they need, and. It gets, it's getting a little crazy because as you know, there are more and more [00:30:00] channels available and there's so much content out there that, you know, you're, I, again, it's this word fractured that keeps coming up, and I guarantee you audience out there who, anybody who knows me or follows me, you keep seeing the word fractured.

That is not an AI thing. That's me. I, I keep, because I think it's real, like this whole fractured thing is it, it just keeps on shattering and fracturing and, and there's no. There's very little binding happening. So if we can find ways actually to kind of bind that in different segments, that's actually very helpful.

So when McKinsey, my whole piece on McKinsey is really tongue in cheek and, and I certainly came down hard on them a little bit for discovering something that we already knew. But you know, sometimes they put out some really good, good information. I like the I and the idea of their consumer segments. Um.

Content lovers, interactivity enthusiasts, and community trendsetters. Those are the three that made it into my review, because those are the three that they also highlighted as worth pursuing, right? [00:31:00] When you're devising your content strategy, and if you, whatever you're doing, if you are putting out a story about, um, about turbines or if you're putting out a story about legal services, you know, those are two very, very different audiences.

But within that. Audience, who are the content lovers? Who are the interactivity enthusiasts? Do they exist? You know, and are, are, are the community trendsetters part of that group? I mean, you know, you'd think that if you're corporate and you're talking about something industrial and it's kind of that, oh man, this is not gonna attract these community trendsetters.

You might be wrong in a big way because you know those. Community people it exists at in every industry, in every vertical. And we would be really lucky or or fortunate to figure out how to reach [00:32:00] them first and understand, get their attention, which would then kind of turn into a little bit of a snowball effect 'cause they would get the attention of others.

Kind of a take on influence marketing, I guess.

Anne Green: You know, it's so aligned with how our industry, like many of us as practitioners, have woven influencers as a core part of strategy, and many companies do a great job with that. But I'm, I'm kind of shocked still in the client service landscape, how many companies do not see influencers as part and parcel and symbiotic with all of their other stakeholders from a communications and marketing standpoint.

Um, there's some incredible best practices there, and yet. It's still quite siloed and there's still a lot of, um, organizations that are just not investing what they should in that area and need. And it's, it's that evolution of media. But I wanna move on to the AI of it all because the AI of it all is all around us all the time.

And, you know, it is a double-edged sword in this area. And the fingerprints here are all over the evolution of this field. Um. [00:33:00] I think one of the most interesting things that's very germane to what you're talking about, turning hierarchies on its head and changing what we think is conventional wisdom about what's a good media hit, you know, who is the big fish, right?

So there is so much excitement. I think the acronyms have settled mostly on GEO generative engine optimization, although a IO is still trying to make a play. Yeah. But let's say GEO, right? Sure. And how it is that large language models and each of 'em are a little bit different. The overlap. There's overlap in how they pull, but they're each a little different and.

How open AI is using Bing as a crawler and you know, and other things like Reddit. But what they pull from to create those search results that create that zero click search environment where you get everything on the page, which is so disrupting publishers, so disrupting media, so disrupting like the incumbents of search,

Dan Nestle: I think.

Fundamentally, we always have to remember that quality content, uh, and [00:34:00] engaging content and compelling content will always win in the long term. But it has to be smart content, and it has to be done in a way that I think treats AI as another stakeholder rather than as a, rather than, as a, uh, kind of technical marvel.

It ha you have to think of AI as a stakeholder. How, how does AI like to read what you write? Just in the same way that one of your customers likes to read what you write. Right. So, um, I did a little exercise the other day to, you know, I took a blog post and I said, okay, now, and I was using Claude and, and I asked it to just optimize the blog post for, for search, which by the way, people should still be doing because search is still, is, is, is not going away.

Just. You know, the results are gonna be different, but you, you should still always think about, you know, writing good content for search, but, okay, so optimize for search. And then I said, okay, can you optimize this for GEO? The GEO version was so [00:35:00] radically different in structure, lot of bullet points.

Mm-hmm. Um, they added an FAQ at the end. Uh, there was, uh, there were, they added a credibility section, an authority section to, to establish the authority of the author. Um, and I wouldn't post that the way it was, right? That's not something I would do. So it's just because you, you have something that's ge optimized, doesn't mean you should always use it, you know, take elements maybe.

But the lessons there are that AI is looking for, um, digestible bytes of information. It's looking for a conversational flow. It's looking for content that actually answers questions. Um, so that's why there's a FAQ in there. And, you know, sometimes you have some stuff in the, in the conversational flow, in the content itself.

Um, it's looking for authority and that's definitely where media has that kind of light at the end of the tunnel waiting for them. It's looking for authority and credibility [00:36:00] and uh, you know, it wants to make sure that whatever it delivers to the user is. Not hallucination in Israel, because you know, that is something that even though they still hallucinate, still deliver nonsense, it's, it is something that's, that's important to the ai.

So structuring it that way is, is what GEO is looking for. So, GEO, you know, and each, you're, you are right. Each of the LLMs look at things differently. You know, pulls in, pulls in this information, however they pull in information. The other, the other. Part of it that I'm just really starting to get familiar with, and forgive me if I get some of this wrong, 'cause I, I do urge everybody to fact check me on this, but you know, it's not like search where you're, you're going to create A-A-A-G-E-O optimized um, piece and then it's going to appear or going to have a good chance of appearing in the LLMs the next day.

That's not the way it's gonna work. You know, the piece, [00:37:00] even though LLMs have access to the web. They're using web search to get to find relevant articles and yeah, you're going to certainly have a chance there. It's still search, right? They're still using search. So they're, the search results that they're getting are not any different than the search results you would get when you go to Google and you look, in fact, you can watch the reasoning play out in some of the models, right?

Um, what's happening is your piece, that content is being used for training. And for training the model. So it's going to be, it's going to be added to the models and piece by piece. It will raise your authority, or it will, it, it will kind of make it into, into the models, you know, kind of rep repository and be, be merged into the Borg as it were.

Then, you know, when you search on topics or when somebody searches on topics later. It will have it in the training and it will understand the context around which it will find a website, [00:38:00] uh, which then kind of builds the authority for that website or for that information because you've handily provided it with all it needs authority, conversational, uh, conversational content, answers to questions.

Okay, this is legit, this is where it's going. So it's multilayered, I think, is what I'm trying to say. Yeah. So within that, you know, the media. Has a, this is where there's, there's kind of a, a real interesting trend going on and I'm not sure what the truth is here, but I've seen pieces say that media should be really excited because, and, and me, you know, media relations, uh, the focus on top tier media should be stronger than ever because top tier media is going is and is always going to be the most authoritative sources for.

Even for GEO as G gets on and, and there's some truth to that, you know, they, there is authority. I

Anne Green: I think you run into the paywall issue [00:39:00] more often though now with some of those, which is gonna be a challenge for you. It's

Dan Nestle: gonna be a challenge. But, you know, we, there was a recent thing from CloudFlare, I don't know if you saw the CloudFlare, right, where absolutely where they're, they're charging for bots, um, charging bots to crawl content.

You're seeing more and more deals with the media organizations, with the LLMs. So, you know, I think it'll happen more.

Anne Green: Yeah. That was in concert with Meredith, I think, to try to, to do some of that gating of content. Yeah.

Dan Nestle: And that that's gonna play. But you know, yes. If you manage to get that high-end media hit, that's not gonna really do anything for your, for your GEO.

Um, at least. Not in a visible way and not immediately,

Anne Green: no. To me it goes back to the trade magazine piece. You know, what are those deeper authoritative that have a whole body of work on a certain area or sector? Or topic. Right. By the way, thank you for the Star Trek Borg reference. There's never a time in this world not to bring up the Borg.

'cause it always feels, I know. [00:40:00] Especially now. And it, and it's interesting too, what I really liked, I wanna pull out what you said, is treating AI as another stakeholder. Whereas, you know, we've talked about in terms of AI practices and getting more familiar with generative ai, encouraging folks to say, imagine this as a young person or an intern, or, you know, you don't wanna anthropomorphize it entirely.

Know, you have to be careful about the what it is and what it's not. And obviously this whole emergence of chatbots and therapy, chatbots and companion, that's a whole nother world that we'll do another podcast on someday. Um, whoever isn't obsessed with talking to their chatbot, and we'll be here to still talk with me, we'll, we'll do a podcast, but I think this question of.

Thinking of it as a stakeholder that has to be built with information over time and we'll find information sources and synthesize them and bring it up. I think that's really powerful and I really appreciate, I think it was really clear the way you talked about some of these aspects of GEO, which is still developing, you know, we're still learning it with SEO.

There was a lot of work to try to [00:41:00] understand and and the Google algorithm and what are the hundreds of factors and Google would release some and not the other. I think we're in this similar thing of trying to discern through practice, but the really interesting thing about this moment in time is you can also ask the entity, tell me what is GEO optimized or tell me what is gender invention optimized?

How do you communicate? What are you looking for? And one of the reasons I think it's really. An interesting opportunity for folks who have communications at the heart of our skillset as a practice, and also literally as communicators, is understanding what different audience needs an AI as a stakeholder.

We're a multi-stakeholder group. Like that's how we look at stakeholders that way, right? And we understand why would someone need an FAQ? Why would someone need a statement and context around authority? How do I build that in a way? That context come through and it's understandable. How do I reframe? I always [00:42:00] joke, you know, with clients, like, I can give it to you as a Word document, a PowerPoint.

I can do Aldi lamp, you know, interpretive dance, like whatever format you need, I can recreate it that way. So I think it does seem to give some real power to a group that has quite a broad toolkit in terms of how we communicate with different stakeholders. I dunno, does that resonate for you at all?

Dan Nestle: That's straight from my, uh, my hymn book. I mean, there's, there's a. There's, I've always been saying, and I, and I've always been advocating for, for people with the skills that communicators have to take the lead in a lot of this stuff, and we hold back in within organizations or we're, we're stuck in boxes or, you know, you, it's hard to move out of your lane.

There's a billion reasons. Uh, you could anger the wrong people and get laid off. It can happen. That said. Who else should write FAQs? I mean, who else, who else is good at writing? You know, conversational content. The, the next phase or the [00:43:00] current phase of attention is if you're getting the attention of the ai, you need to have content that that earns their attention and.

That's exactly what it is. This, you know, the kind of things that we do, and it's the same thing that attracts the attention of our stakeholders and of, of any audience. Um, people like conversational content. People want to know answers to their questions. Uh, and if it's a even, you wouldn't necessarily put an FAQ, you wouldn't think to put an FAQ with a feature article, but maybe you do now.

Maybe you put a little FAQ at the end. Maybe you put a little study guide because you can do that very easily. Create a study guide for that piece, chunk it on, and then you have all of a sudden something that's a little bit more geed and might be a lot more interesting to your, to your readers. There's a million ways to do this, but it's all comes back to who knows how to ask the que ask the right questions.

We do. We [00:44:00] know how to ask the right questions. We know how to ask the right questions. To the LLMs as well. So, you know, both in the creation side of things and then in the iteration side of things, you know, we are in, we are by nature, curious, inquisitive, uh, inter we like to interrogate in a positive way and we, you know, we, we like to interview, right?

We're interviewers, we're media people. Let's play that out and you'll come up with great content. Um. It's just, it's just interesting to see how that's evolving within our profession. Um, I've gone pretty, I've, I've gone down this huge kind of road and rabbit hole of building that into really better and better prompts and better and better kind of, you know, Conte contextual, um, operations within a, within the ai.

But it just started with me asking questions, you know, like, can you do this? Can you do better? Can you even better? What's a better way to do this? And so on. And it builds [00:45:00] out. We could do the same thing with anything, uh, we do with ai and we are the right people. I think the communicators.

Anne Green: I love that thought about it comes from that questioning nature and from multi-stakeholders.

Um, as we wrap up today, what's one thing you wish or hope every communication leader or practitioner will do to think about earned attention in a fresh way or a step you'd love them to take? You know, any tip that you wanna share,

Dan Nestle: the number one thing to do is. Clear your mind of what good media is and think in a new way about, about what is, what is really important for your message and for your story.

Where, where does it need to land? So the answer there is your audiences and the audiences has to come first before you think about your media. So, you know, we, we didn't exactly say this explicitly, but fundamentally, I think that's the big, the big problem [00:46:00] is thinking about we need to get this into the times.

We need to get this into the Wall Street Journal. We have to get this covered by the ft. Stop that and think about, I need to reach these stakeholders. What are they reading? I need to reach these people. What are they watching? If that's the ft, then go for the ft. It's just creating that strategy from the audience first is critically important.

So think about the audiences first. You're gonna find that they have multiple, uh, and, and dynamic reading and, and viewing habits you're gonna find that you might have opportunities to get into. You know, and certainly the opportunities are much easier than top tier media. The trades are fantastic.

They've done such a great job, I think over the last 10 years of surviving. Building out their technology. They're, they're, they're doing more with podcasts. They're doing more with expert content. They are certainly [00:47:00] ahead of the game with, with uh, GEO, just by default because they're authoritative and they're very technical and detailed, answer a lot of questions.

So look at them in a much with a different lens. Convince your leadership that this is good media for us to be on podcasts, videos, those kind of things. So think audience first, I think is the, is the thing I would beg people to do.

Anne Green: It's kind of a return to the very, very best practices that are foundational to this field, and yet they get lost so often.

I encourage our listeners and viewers to find Dan Nessel, find the trending communicator. Check out, you know, subscribe to the substack, listen to the podcast, and Dan, it's always a pleasure. Um, thank you for being here today. And you know, thanks for everyone's listening to Building Brand Gravity. Check out our other episodes, find us, you know, online on video and give us your feedback.

We always welcome it. So thank you again.

Dan Nestle: Thanks [00:48:00] Ann.

Building Brand Gravity – Loren King
Loren: [00:00:00] I've been thinking a lot about a quote. Essentially it says every system is perfectly designed to output what it outputs. However, a system is made whenever you're getting out of the system, that's what it's designed to do. So if you want to change what's made you need to change the design. I'm not sure that AI fully fits that mold because you could be as accurate as you want, and there is still technically the potential for something to come out that was unexpected.
Anne: Hello and welcome to Building Brand Gravity. I'm Anne Green, I'm CEO and a principal at G&S Integrated Marketing Communications Group.
Steve: And I'm Steve Halsey, uh, one of the principals and chief growth officers of that same group. And welcome you to our latest episode of Building Brand Gravity. Anne, you want to let everybody know what's in store?
Anne: Yeah, we're doing a little two part series here, a mini series, if you will. The first, um. One was focused on AI research and sort of the evolution of where it's at in our industry right now, and [00:01:00] that that industry is not just communications, it's really across marketing. And then for today, we're gonna be speaking with one of our own in the group who I'll talk about in just a moment.
Discussing about how we go from AI exploration really to enablement, especially in the context of some of our largest sectors. So I'm excited to, to build on the conversation we had last time, Steve.
Steve: It should, it should be great. And, and, and Greg is always a, um, always a great interview, great, great friend of the pod, as I like to joke.
And, and my conversation with Greg Galant, who's the co-founder and CEO of MuckRack was really on, on. For those of you, I hope you all listen to it, but if you have it, you can. After you're done with this, you can go right over and click it, but it was really on the results of their latest research on the state of ai.
Basically, AI is the new normal in pr, and there were some really interesting facts that we covered there. 75% of PR pros are now using generative ai. That's up from [00:02:00] 28% just 18 months ago. Of those who are using it, 93% say it speeds up their work and 78% say it improves the quality of their work. Does that sound about right?
Anne: I think it's adoption is growing fast. That feels very right to me. You know, as I talk to leaders across the industry, as I talk to practitioners and, and again. There's comms, there's, you know, paid media, there's adv, there's creative, um, digital. All of our teams, the teams that I know at other agencies, um, adoption is growing fast.
Some of it is because AI is being baked into so many tools we use. MuckRack is one of those, Adobe Firefly, et cetera, but others are people being very. Intentional and agencies and client side being more aggressive about saying, we need to weave this into our workflows. We need to disrupt our own workflows, and we need to bring, um, this technology in, in all kinds of ways to augment what we're doing.
So I, I think those stats are. Powerful and right. And I think it's only gonna grow. Right.
Steve: And there and there [00:03:00] were, there were two more stats in there that I thought was, was really interesting. At a, at a recent award ceremony I ran into, uh, Kim sample of the PR Council. And, and for those of you who don't know it, Ann's on the ethics committee and she's really worked to really help put together a lot of AI guidelines and guidance for, for agencies.
But there was, there, there were two stats that I found fascinating in, uh, in muck rack's research. Only 38% of PR PROS report having company guidelines. And only 43% of AI pros report access to AI training and even a smaller percentage, um, always disclose that the number I'm just looking at, only 20% of agency pros say they always disclose when they, when they use ai.
And, you know, we're, we're seeing right now. Some interesting dilemma of we all see the power, you know, uh, [00:04:00] 75% are using it on the client side. I'm hearing that a lot of brands wanna use it, but there are two things that are causing some challenges. Our favorite. Legal and procurement. So I'm interested to get your take on that.
Before we get into Lauren's interview, I guess in, in my mind, I jotted down a list of, there's three essential things for us to think about when we're talking about how we use AI for media relations, content creation, or analytics. And, and I'd love to get your reaction to 'em. Number one is defining the acceptable use and boundaries upfront, where we specify how generative AI may be used for drafts research, media list enhancement, sentiment analysis, things like that.
Number two, making sure you align on the data privacy, IP and confidentiality protection, so you're very, very clear that you're. Only going to use AI tools and not train them on any data other than what you agree to. And then the third one is to [00:05:00] really codify that governance, that disclosure, that risk mitigation share our AI usage policy, all of those due diligence.
So those are my top three. Define the boundaries, align on privacy, and really codify your governance. I. How does that, how does that tie into what you're hearing?
Anne: I, I like those a lot. It's an interesting moment for sure. And I appreciate, you know, the work with the PR council and it's so funny, you know, obviously the name PR council, all the agencies that are our peers that we're highly integrated.
So there's marketing, advertising, creative project management, you know, all the pieces that reflect who we are today. So it's pretty multi-layered, but looking at it from a communication standpoint in the toolkit. I have enjoyed being, you know, one of the heads of that ethics task force relative to how do we use AI in the best way with the smart guard rails because.
As I say many times, you know, I'm out there talking about this a lot. There's two sides to every coin. There's the amazing power of it and then there's the with power comes great responsibility and [00:06:00] there's the challenge of it too. The deep fakes, the, you know, the AI slop at scale and, and things like that, right?
So what's interesting about our colleagues and procurement and legal, so being on the agency side obviously, and working so closely with clients, tho those are their peers in house, these are our. Partners and peers, you know, across that partnership relationship. Um, there, it's coming at them fast and the problem is there is a lot of challenge with these tools.
There's, um, protection of intellectual property. There's hallucination. Hallucinations have been reduced, but not entirely. There's the question of the transparency of usage. There's a question of, I think there's gonna be an essential question of like, what are we paying for, you know, the machine, the human, what is the nature of this relationship?
So one of the watch outs we're seeing is that as these, you know, respected groups, um, they play a really important function in our client organizations, obviously. They are trying to catch up to something that's just a [00:07:00] horse is running out of the barn. It's like a whole fleet of horses. It's just a stampede flying out of the barn and they're trying to catch up to put it in language and legal documentation and questionnaires to be like, how are you using this?
So in some cases we're seeing organizations that are very large come back with AI addendums that are. Huge, long and overly restrictive because the fact is AI is baked into everything. I mean, I got my little phone right here, it's everywhere, and it's baked into the tools and it's being baked in in ways.
Greg would say those words changing every day. So those overly detailed and restrictive and kind of saying, well, you almost can't use AI at all. It's just not feasible. And I think those groups know that others are trying to do, I think what you said, Steve, which is. How do we make sure we're talking about use cases to begin with?
How do we make sure there's a transparent discussion? Like I would like my own people, you know, our people at G&S to be transparent about, Hey, I got this. I'm using generative to get me going on a draft, [00:08:00] but. I'm also, um, using my brains and my expertise to edit it and make it better. So I think that we're seeing the normal sort of churn in this fast moving landscape, but I, I don't envy our legal and procurement colleagues.
This is challenging.
Steve: It's definitely challenging for them and, and definitely people on the brand side too with their teams, um, to work. Through. So I guess what I would say is, you know, we're, we're all in this together, so you know, if you're a agency listener, let's work with our friends at the PRC and really help kind of educate.
If you're on the client side, you know, just really think about even leaning in and reaching out to. The PRC yourself, even though you're not an agency for best use guidelines, so that we can help you kinda work within your system with procurement, with legal, to really put together something that makes sense for everybody.
Anne: I agree. 'cause ultimately it's our partnership together that's gonna find out where the value in our work will be long-term, where we. Automate wrote tasks and get faster to the [00:09:00] value that matters. And we're only gonna figure this out, agencies and clients together, you know, really in concert. And that, that's actually a good transition to our guest for today.
Our guest is Lauren King. He is a senior digital marketing specialist at one of our two agencies, Morgan Myers, a G&S Agency. He is actually, um, just about, he's celebrating his third anniversary at Morgan Myers, but he has a lot of digital experience prior to that. And he is part of our AI exploration and enablement team, so he's very, very knowledgeable.
We have some super users across our two agencies, across the group. Um. Every specialist group, every, you know, sector and discipline that we offer. And that group's been such an amazing brain trust as we move, you know, from more explanation, exploration to rubber on the road and putting all the tools in people's hands, doing all the training and starting, you know, a deeper transformation process.
So. What I wanted to talk with Lauren about, Greg gave us that 10,000 or a hundred thousand foot view [00:10:00] of how adoption is changing. And I think that conversation, you guys had, had so many cool aspects to it. He's got a really great bird's eye view. Lauren is in the ground, especially literally on the ground with our clients and ag and our clients and food.
He is a real specialist, excuse me, in many aspects of ag and um, technology as adoption. So what he and I are gonna talk about, and I'm excited for folks to hear. What are we seeing on the ground in terms of tools and approaches and use cases, and also driving more engagement. Um, how is he an advocate for that self-education and upskilling that we all need to do both as companies but as individuals?
And the third view he has is it's really hard to just say, well, what can AI do? 'cause the answer is everything. It's more about what problems can we solve? So. Let's listen to the conversation with Lauren and Steve. I'm sure we'll have stuff to talk about afterwards.
Steve: I can't wait.
Anne: So here on Building Brand Gravity, we are [00:11:00] interested like everyone else in the world, in the evolution of ai, especially in the marketing and communication space in which we work across many, many sectors.
And I'm excited to have a conversation with a colleague of mine, a fairly new colleague of mine who came to the G&S family through our acquisition of Morgan Meyers, an amazing agency. That focuses on agriculture and food, and that person is Lauren King. Hey Lauren, how are you
Loren: doing? Pretty good, myself.
Anne: Excellent, excellent. So just a little background, Lauren is a senior digital marketing specialist at Morgan Myers working on many different agriculture and food, um, clients. But I love Lauren that you have such a background that's really rooted in that space. Literally, you know, a farming family. You were growing up in Southwest side of Michigan and now you live in the southeast side and you and I were kind of spiritual neighbors 'cause I was born in Toledo and I've got a lot of family there right down I 75 from you guys and educated at Michigan State University.
And I think what's really [00:12:00] interesting for this conversation is not only I. Is Lauren a specialist in digital and all those pieces, you know, very much an integrated set of capabilities, um, as many of us work in today. But also doing things like chairing the American Farm Bureau Technology Advisory Committee and working with Agriculture Future of America Alumni Advisory Committee, um, speaking at, you know, um, different types of venues that are digging into ai.
So, um. Just to get us started, Lauren, so tell us where you're coming from today and, and what you know, what home is like for you in that part of Michigan.
Loren: Yeah, like you hinted at, I'm in southeast Michigan, which is between basically Toledo on one side and Ann Arbor on the other. That's the easiest reference for many people right now.
I look up my window. I can see at least one, uh, tractor and planter combination. I think they're planting soybeans, but the fields by me are a mix of soybeans, pumpkins, corn. We did have peppers last year. We'll see if that happens again. So we're [00:13:00] very, very diverse, very agriculturally diverse. I'm 10 minutes from the nearest town, which is a small main street and that's it.
I'm 20 minutes from the nearest Walmart and that's largely my experience growing up. But thankfully we have great internet.
Anne: Yeah, which is very important, especially for today. When you and I are meeting you, you are in Michigan, I'm in New York City and we are totally connected and live, which is great. I love that.
So, um. You're working heavily in digital, but when I first met you, we bonded over many things, many different points of interest, but especially the evolution of technology today in ai. So first I'd like to hear a little bit about how you describe your digital role at Morgan Myers as part of the G&S group.
And then after that I, I have a follow up question, but why don't you talk about the kinds of work you're doing now in the digital space.
Loren: So I'm part of our digital team at Morgan Myers, which means that we touch a lot of different clients. I don't have one specific client that I work with day to day, [00:14:00] although Merck Animal Health Cattle would probably be my primary.
And my role specifically ties a lot into systems management, whether that's the backend of digital ads, our social listening capabilities, so tracking trends in real time. Deploying AI when possible. That's been a big part of what I've done the last six months to a year or so, and websites. Really anything that a system within digital touches is where I tend to specialize.
So that can take the form of pushing out an ad campaign one day, the next day. It's understanding how a client's product is viewed online, and then the day after that, having a conversation like this, focusing on how we can use AI tools. In different ways within Morgan wires.
Anne: I love the agency context and especially the kind of role you play.
'cause it is so diverse and it's also naturally. Keeps you, um, as a learner, you have to continuously learn and grow. So talking about learning and this conversation you and I are having as part of a small series we're doing on AI as part of building brand Gravity, [00:15:00] we've been having ongoing conversations is something I'm obviously very interested in as you know.
I wanna go way back in time. 'cause it was so interesting talking to you about this and preparing for this conversation. When did you start your AI journey? What was the thing that, um, alerted you to this coming wave?
Loren: So, you know, as a kid we always had stories with robots and even Star Wars and examples like that.
But when it really hit me that AI could be something that could be used, was. Around 2013, and a lot of people don't know that Google basically pioneered a lot of the innovations that make tools like Chat, GPT, and Copilot accessible and available today. So they were doing some work. There was blogs coming out, kind of explaining the underpinnings of how this one works, and this is far beyond what I could understand at the time, but it got enough.
Pre, uh, enough press and, and buzz that I was able to take a look, start hearing words like LLM or large language model for the first time. And when I, uh, I looked at it, of course, even though it was ill language, I didn't really speak, which is [00:16:00] algorithms and, and data science. I was, I. My interest was peaked because I didn't realize that you could actually do anything with artificial intelligence.
To that point, I thought it was something held in Asimov novels in the future of Star Trek.
Anne: I love that. I mean, that was 12 years ago and. Clearly there's many folks out there may be some of our listeners that understand that AI has been out there developing for quite a long time. Not just theoretically, but practically.
But I love the idea that your journey has been so long and that you started to try to get hands on right away because, um, you and I have a little bit of an age difference. I'm gonna assume you're quite young, you know, 12 years ago, but I,
Loren: 27, I would've been 15.
Anne: Okay. Yeah, exactly. See, that's what I, I was kind of guessing.
Um, I had started hearing about it as well, and I think it's interesting to. Think back to that moment, as you said, like what did you think it was? So when you first heard terms like large language models or you first heard terms about the idea of ai, I don't know if generative AI was used in that context.
Sense of ai. [00:17:00] I
Loren: have it in common.
Anne: Yeah. I, I feel like that has been. Especially chat, GPT. One of the biggest innovations, the common nomenclature of generative AI is something different from maybe predictive or, but when you first heard of large language models in AI over, you know, overall back, you know, when you were a teenager still, what did you think it would be and what you could do with it versus how you're seeing it and using it today?
What's that delta between the two?
Loren: Yeah, so when I was hearing about it, it was very much. Within the of academia that it was being considered and deployed and where I was thinking it would be used. So I'm picturing, you know, giant Excel files with millions and millions of lines, letting some type of machine learning tool loose to analyze it and find some trends or.
Maybe being able to go back and review what has already existed or apply government statistical analysis to data coming outta the USDA, those types of intense situations, you know, not something that the everyday person would probably run into very much [00:18:00] almost I. Validating, uh, existing data more than creating.
I do think that I read a little bit about creating images to the point of they thought it wouldn't really ever work because there was no way to make the hallucinations coming out of an AI tool. I. Cohesive in a way that somebody would actually get what they want. You could make it make something, but it didn't actually make any sense.
Kind of like the early days of Dali, I'm sure if you experimented with it, you got some really interesting stuff. I've got some saved down on my phone, but for me it just seemed like it would be stuck in the realm of academia and statistical research. And it wouldn't ever be something that I could truly see myself using my dad using on the farm, uh, or deploying in a business context.
I was very,
Anne: I think my version of that is, um. You know, in the sectors I've worked in, which are many, including agriculture now, which I, I love, um, engaging in and you have so much step there. But I would see it in terms of health and medical, um, innovation. So [00:19:00] things like high throughput screening, which is critical to the drug D discovery process.
You know, things like, um, other types of, like the way that alpha fold is working on protein folding. And so I was thinking about it more in the scientific context too. And it's very interesting now to see it leap into a space that is really transforming everything we touch. I, I think the other piece for me that made a lot of sense is there was such a buzz.
Even almost that far back about big data. Uh, you know, if you might remember, that was such the buzzword. There's always a buzzword, but big data was a thing, and I think what the issue was was big data was there, but what do you do with it and how do you deal with it? Especially when the big data is big, like you said, the USDA stats or data points.
So, you know, I, I really resonate with that. So there's been so much going on. The evolution is so fast. Like you said, if you, you know, created pictures in Dali a few years ago, they are quite amusing compared to what it can do today, which is, there are some
Loren: interesting ones.
Anne: Yes. And, and all the weirdness with [00:20:00] human form and human hands and all the, all the stuff we know, right?
It's, it feels like so long ago, but it was only like a year and a half ago. But when you see everything that's evolving, and you and I talk about this a lot and our AI enablement team across both GS, business communications and Morgan Myers talks about this, what are two, some of the most notable. And important evolutions that you've been tracking that you think are really material to the work you do and that we do?
Loren: Well, we actually have one that's new as of today or within the last 24 hours, which is, uh, OpenAI Focusing Chat, GPT as an Everything app. Uh, going beyond search and creation into, I'm not sure if you've seen their shopping edition, uh, that they have. So they're integrating with Shopify and they're gonna be recommending products based on very specific search terms.
Uh, no ads only going off of the metadata of the product and your personal preferences from your prior time using the tool. So that'll primarily apply to paid accounts. But if I have been doing a lot of. Researching for a trip to [00:21:00] Italy, it'll incorporate my preferences when I then ask it to recommend a bath towel that fits for a beach and can go into luggage.
It's a, a big change and it's a reason to not leave the app. It's a reason to have better SEO uh, if you're working from a marketing perspective, because that's gonna be really, really important and it changes the way that consumers are gonna interact. But it's also changing how I'm going to interact, uh, with.
A tool like Chat, GPT or copilot will have it before too long. Everybody else will as well coming out of that. Oh, please go ahead. I was gonna say, coming out of that, another one that comes to mind is integrating with other apps. We're still on the edge of what that looks like. I, you know, I can't log into my Facebook account through Chat GPT yet.
I can't log into my United Airlines account through Chat GPT or copilot yet. But once you can, that's when eventually you get to age Agentic tools, which I'm sure we'll touch on a little bit more, but. You know, making my digital life more cohesive and having an assistant. [00:22:00] So taking the shopping side and becoming everything.
App is one. Connecting to all your other apps is the other. Those are the two that I've been paying the most attention to.
Anne: I think those are so material to our work and to, and to our lives as humans. I mean, that's the thing. This is gonna be woven in absolutely everywhere. And the way we talk about AI today.
And, and by the way, one of the things, you know, Lauren, that really bugs me is when we're not precise, when we talk about ai, we just use this big old acronym when, you know, are we talking about something that's more predictive, cognitive, generative? But the fact is, is that it will be that, um, inside everything and sort of the web that connects us in a way.
And it, it is interesting. You talked about SEO, there's been so much discussion recently about. Is this the end, the, the death of search engine optimization? I tend to be very skeptical when anyone says something is dead because it's usually alive somehow. Um, my, you know, my agency life would've been gone a long time ago if I listened to all of those things 'cause we're still here.
But this idea of, um, AI optimization, [00:23:00] you know, how are you optimizing for the large language models and how they're crawling the web in a very different way and how they're ingesting information. And so. I love that you're thinking about that from a digital perspective. 'cause our clients absolutely have to think about that, right?
Loren: Absolutely. And not just SEO, but how SEO and your imagery work together. It's a little bit of a unique experience, but we've been developing a chat bot for a client that connects to food and one thing that emerged as we were working the chat bot is that it was scanning, not just. The recipes that we had, but it was scanning the images associated with the recipes as well, and it would recommend something different.
So for example, if you were to search for like red, white, and blue or 4th of July, all of a sudden you're getting, you know, foods that aren't connected to 4th of July, even though they have some in this website, but show cherries or blueberries and then like a whitish looking dough in the meal it's, or in the, uh, baked good itself and.
It understood. Like the tool understood that. And so even your imagery becomes an extension of your SEO, uh, in a sense if you're [00:24:00] trying to predict what people are looking for.
Anne: Yeah. It's kind of like a supercharging of what Google has tried to do with Google image search and um, and, and obviously Google is working hard the way it's incorporated Gemini at the top of the search page, not to lose, you know, its brand and the dominance it's had, but I think it's gonna be really, really hard at this point for Google to maintain a choke hold on that we're already seeing.
So much use of chat GBT, just as one example through the app and from a business development perspective, you know, more and more we're hearing, oh, we found your agency through chat GBT, which has not to surprise me at all when we see the kind of search volume that's growing around it.
Loren: A billion searches last week according to Sam Altman.
Yeah.
Anne: Yeah. So, so much change. So, um. Thinking about the ground level of this and that's why I was so excited to speak to you. You know, like many firms and especially on the agency side, 'cause I talked to folks on the corporate side, agency side, many of our clients, um, we don't have a lot of restrictions on the agency side about how we experiment.
We have very [00:25:00] specific guidelines. As you know, Lauren, I'm very focused on ethics. We've been part of the PR council's work and ethical use of AI for communications. Um. Respect intellectual property. We're very careful about, um, IP protection and also the ownership of creatives. You know, how things are being used, right?
So we take that really seriously. But in terms of experimenting on the upside, there's very little to hold us back. So what I wanted to talk to you about today was really that ground level. How do digital and marketing and comms professionals, how are we benefiting from use of a AI in our day-to-day work?
How are we exploring and what are we hoping. Our colleagues do say at G&S and Morgan Meyers and other places, and you know, I, I see it as there's the working smarter, not harder. They're solving persistent problems and pain points. There's knocking out those rote tasks where you're like, this is taking way too much time.
You know, I need an assistant to do this, or my favorite, which is enhancing our strategic value. So when you think about your workflows and those of your peers. [00:26:00] What are some of the either tools or platforms or workflows enabled by AI that have really changed your workday?
Loren: The easiest is something that a lot of people probably wouldn't consider, but really has been a game changer for me, which is automating a very repetitive task of receipt analysis.
We have a lot of receipts come through social media that need to be split out. For those not familiar with an agency structure, you're often going to split them out on a receipt between different jobs or outlines, uh, each with their own. Budgets, if you will. And because social media platforms don't have the ability to easily update how a receipt comes to you, you're kind of getting everything at once.
So if I'm running two different campaiG&S, they're both gonna show up on the same receipt. Well, as a result, somebody needs to go through that and figure out how much money goes where, and then note it for processing from our financial side. It sounds very boring and it can be very boring, especially, but it can also be a lot because we have campaiG&S where we'll launch.
You know, all of a sudden [00:27:00] $20,000 or a hundred thousand dollars in a month, and when we're limited in the size of the receipt, that's a hundred receipts we have to process. So we have a. Custom GPT that's trained to analyze receipts and provide a naming structure and the math that we need, uh, only for us.
So it's, it's trained in the style that we're trying to go for. It uses the structure we want. It's trained on our examples. It does not connect to the internet in the traditional sense, only through, uh, A GBT interface and. Although it's only 10 receipts at a time, it's a game changer for me. My personal estimation is a 30 to 40% increase in processing speed more if there's only a couple, uh, different jobs at any given time.
But we have receipts that can go up to seven jobs. And so I've shifted from having to do all of the math myself to double checking what's coming out. And so far. There's been one inaccuracy on the AI's part and five inaccuracies on my part that I messed up on the receipt structure beforehand, [00:28:00] and a 98% success rate, I would say, without really any changes needed at all.
It's hard to overestimate
Anne: that. Yeah, I love that example because. It, it, that's an example of a persistent problem. It, it's kind of shocking to me. I mean, no shade to the social media companies, but the way the billing structure and the receipts come, well, I meant I am throwing a little bit of shade. It's just, it's
Loren: okay.
Throw the shade
Anne: crazy from a business perspective that this is still how the billing is done. And for any paid media teams, we have the Morgan Myers team doing paid media. We have the Gs. On G&S business communications team doing paid media, it really is a burden. So I think you've hit those buckets of knocking out road tasks and solving for persistent pain points.
The other thing this brings up for me is the idea of AI as an agent that assists you. And I think, you know, we've thought in terms, so we, first we had to learn to think about the internet as an entity, then we had to think about. Kind of that social internet. Then we thought about apps. We got trained to think about things from an app perspective, not just through mobile.
It came through mobile, but now [00:29:00] it's like even apps. You think about it even in a desktop perspective in a way. So now we're being trained to think about agents. Right. So how would you define for our listeners, you know, hopefully people are following this, but. How do you think about that word, either app or agent in the context of some of the things that you're starting to build and use?
Loren: So for me, an agent I would consider as something that can persistently make its own decisions, whether that's allowing it to go operate off of its own schedule, control a specific piece of software. There's a little bit of nebulousness when it comes to what is an agent, and I think that's okay because this is all still so new that we're not gonna have like exact definitions, but it helps even in the name itself, anybody largely understand what it is.
Think of an intern who you trust enough to do a specific task. For me, I'm exploring a lot of ways that we can set up agents either for creating projects, building out things ahead of time. Or, uh, on our social listening side, which I help with that a lot, that could be competitive analysis. So repeat competitive analysis, just updating me on key [00:30:00] trends ahead of my chance to actually review the results that are coming in.
So it's almost priming. From a almost real time perspective, my work as I go in to understand a competitor and what our clients need to know on them. So still looking at the structures for those. Yeah.
Anne: Definition a way of thinking about it. And you're right, I think we're reaching toward that and we're hearing what the promise of that will be.
It kind of hearkens back to what your trends were regarding connection and connectivity of the major LLMs with other parts of our lives like. The shopping piece or. Social media, airline booking. You know, one thing that's funny about those connection points is, I actually ran into this this week, is with the note taking apps like Otter and Reed AI and how you give you like open the door a tiny bit and they're in there connecting to everything and suddenly you have.
Read AI Reader showing up to your team's meeting before you get there and I'm like, I did [00:31:00] not intend this my friend, but thank you so much for being so aggressive.
Loren: Yep. Getting emails saying, oh, here's your recap of a meeting. Not even realizing that the assistant was plugged in there, which double edged, but so far has been beneficial.
Anne: No, it's very funny and it, and obviously in our environment using Microsoft 365 and. Enabling copilot for all staff where we, and starting to build out apps, you know, I think they're almost pre agents, but building out tools, um, in every part of our business, from the client side to operations, to everything IT support, et cetera, et cetera.
Using it to work smarter, not harder. It kind of points us in that direction. I read an interesting article, and I'm CEO at our, at our group about how, you know, this generation of CEOs will be the last to only have human. Um, employees, they'll also be agent employees and I, that, that to me was one of those moments like you describing, Hey, this is how I understand agents, that they have some agency.
I had to stop for a minute and be like, that's really interesting. 'cause I feel like I've been managing technology [00:32:00] as a strategic asset for a very long time. Understanding without anthropomorphizing understanding, like agents will be part of that workforce, I find. I mean, does that, what do you think about that?
How does that sit for you? Do you feel like that's the future we're heading towards?
Loren: I do think that's the future, and I've been thinking a lot about a quote, I'm not gonna get it quite right, but essentially it says, you know, the output, every system is perfectly designed to output what it outputs. It's like however a system is made, whatever you're getting outta the system, that's what it's designed to do.
So if you wanna change what's made, you need to change the design. I'm not sure that AI fully fits that mold because you could be as accurate as you want and there is still technically the potential for something to come out that was unexpected because we don't truly have a grasp on how the backend technology works.
That's like a human I. You know, I, I've been there myself, I've been an intern. I can be trusted with the best possible, uh, instructions and go horribly wrong or go the wrong direction with it. So there is a bit of a management approach. It's, it's reflecting, it's responding, encouraging, [00:33:00] asking maybe for a redo on things.
So is there skill sets that people probably didn't expect and certainly not ones you'd apply to? Technology in many cases, you know, when it departments started to exist, people might have managed computers, but they probably expected the computer to. To be accurate all the time and while AI is getting more and more accurate over time.
There's still gonna be that element, whether it's coming from the fact that we're using natural language conversations, that could be part of it. 'cause language is tricky. Things mean different things, uh, different people. Or if it's just gonna be an inbuilt piece of the tech as a whole, my guess is, and.
Like what you were reading and like others have reported on management skills are gonna be very, very common all the way down, uh, to really anybody in an organization that touches a computer.
Anne: That's a really great point. I like that a lot. Um, you've made a point in our AI team meetings and, and we've actually been trying to advocate for this across our organization and also our clients, which is.[00:34:00]
To get over the overwhelming nature of AI because not everybody is feeling like immediately super technical or hands on like some people have been. Exploring it for a very long time, as you have others are coming to it in the course of their job, and if there's a big self-education process. But one of the ways we framed it is how do you start with a need or a problem to solve and think of that first versus what can AI do or what should I do with ai?
Why do you think that's an important way of thinking about this? Uh, especially as practitioners in our space.
Loren: I think it's the easiest way to start understanding the capabilities of a tool like ai. And we can have a thousand use cases. We can have a prompt library that does anything you can imagine. And yet tomorrow we're gonna find out, oh, all of a sudden you can shop in chat GPT.
Now. Like there is no predicting what this tool can do and there doesn't at the moment appear to be an upper limit. 'cause if there's anything digital related, it probably can, but as a person. You know what your challenges are. You understand better than anybody else, not only what is needed in your role, but [00:35:00] also what is sometimes wrong.
I think a good way to position this is, you know, you're still an expert in what you do. So if you're using a tool like artificial intelligence, you can spot when the output doesn't align, uh, with what's right. And so if you start thinking about ways that you can, uh, solve something that's really annoying for me, that was receipts.
It can open up a whole world. I mean, eventually I was getting recommendations for how to code like hard code in analysis tools and connect back to cloud APIs and all that stuff. That's not in my wheelhouse, although I feel a lot more confident now because I got to go through that, uh, exploratory journey.
Thankfully, I found that Chat two was able to do it on its own, uh, using existing systems with the custom GPT framework, but. That opened my eyes in a way that trying to read every study, uh, never could. Now when I go and I come across a new problem, the way I even phrase it or coach it to an AI tool is gonna be different because I have a better understanding [00:36:00] of how the technology works, which I think is really important.
A lot of people don't get the chance to really know like how. If something is generated back to you. So that's number one. But then also how it solves all my existing pain points in ways that I didn't expect. I didn't, the outcome wasn't necessarily what I expected when I started using the tool to solve a pain point.
Anne: I think it's gonna be transformative for us as we continue. Bringing all of our colleagues along in this journey and everybody has so much to bring to the table. I'm seeing such creative, smart, but also, you know, appropriate uses across our agencies. Like, and it's, and it's really gaining momentum obviously.
But um, I don't take that for granted 'cause it has to be super intentional. And what I love is the idea that we have folks around Morgan Myers and G&S business communications and on our client side too, as partners, different people who are. More into this or have skill sets, or they have more experience where they can say, Hey, you considered this.
And it's really more of a [00:37:00] consultative mode. It's like the way we, which we work with clients, which is come to me, um, and, and ask me your questions. Ask me what you're trying to solve for. And I bet you we can find. A use case because you're right, just listing use cases will make you insane. 'cause there's so many of them.
Loren: And a big piece of this that people often don't consider is that you can fully out a project and then use AI to figure out what you missed. That's another way to consider it because you can almost do a negative parameter. Like say I'm planning and events and you know, I've kind of got a location down.
I've got a lot of themes wr written out. I have an idea of the weather. I can upload a version of that event to chat GPT and say, this is what I already know. What have I missed? It sounds simple, but you might be surprised at what comes out to fill in the gaps you might not be aware of. So that's another spot that we've been exploring.
I know that our SEO experts have been looking at websites and they're starting to say, Hey, you know, what is missing from this FAQ that should be here [00:38:00] that would support our SEO efforts, just for example.
Anne: That's a great example. One of the concepts I came across. I think it was on Freakonomics, it was on one of the Freakonomics podcasts with Steven Dubner and they had a, had an expert on, it was a series he did on failure and he had an expert on talking about the idea of, um, kind of projecting forward, I guess you're starting a project to sort of stand at the end and say, imagine we failed, what went wrong?
And I think that that to me is a trick of the human brain to get you out of the box. Like the metaphorical I'm in the box, like how do you get outta the box? Which is a real pat thing, but. There's a real reality to that, which is I need to get like physically, mentally, in another space. And I love that idea of using chat GPT to do that very experience.
You know, either what am I missing or what will, this is the plan, what might have failed? What if we fail? What will have gone wrong? And it's another way. And that's really, again, augmented intelligence that's pushing us to think about things differently with a partner,
Loren: which is the way to think about it.
[00:39:00] You're unlikely to still get a result from AI that can really compete with an expert in a field. It, it can occur it, it's possible. But if you want re repeated excellence, you're better off training your expert to use an AI tool to augment what they do. And then your results are gonna be much stronger. I mean, you've read co intelligence, you know that the data backs that up as well.
Human plus AI is much better than human or AI on their own.
Anne: And you know, speaking of that, as we start to wrap up agriculture. Food, but, but both have a lot of specialization, especially agriculture. You know, you look at image generation. Is the corn that's gonna be generated is looking right? Is it the correct height?
Is it, you know, it's just those things that those of you've worked in that field for years or grew up in that space would know intuitively. It's hard for systems to know. So when you think about your, your peers and colleagues out there, especially in the ag space or the food space from a digital side, what are some tips for those really committed to engagement and self-education and?
Getting [00:40:00] started. How would you counsel folks to think about this or dive in?
Loren: I think there's a good three step process that I'd first recommend, and number one is just simply start prompting, start asking questions. When chat, GPT was released, my initial approach, which I'm not gonna say is correct for now, but what worked then was to do a different prompt every day for a month, whatever I could think of.
The most unusual things. Act as though you're this famous person. What do you think about this historical event? Outline the recent news. How can you help me write some code? Really anything you can imagine, uh, usually even connected back to your personal life. Start up deploying that in a way, uh, that you get a sense of how the tool thinks and how it works.
And really any artificial intelligence option will work for this co-pilot chat, GPT, uh, Google, Gemini, they all should be open for that. But as you're doing that, you're gonna naturally learn how to prompt better. 'cause you're not gonna like the responses. You know, an AI might learn from you, but you're gonna learn from it at the same time.
So as you're doing that process, [00:41:00] explore prompt recommendations. We've got some really good frameworks, uh, internally, there's frameworks out there that you can use. One of my favorites is to make sure that the tool, you tell it how you want to think. So, act as though you're the CEO of a large marketing firm.
How would you respond to the strategic plan? What did I miss? Those are the kinds of things you would do. Don't be afraid of using natural language. My first reaction was to maybe go with the Google search approach of this is really an index that I need to specify, and I kind of understand how it works, so I'm gonna avoid sounding like a human.
I'm just gonna search. Query doesn't work as well. Natural language is totally fine to use, uh, because the tool adapts to it. So once you've done those two things where you've started prompting and then you started understanding how to change your prompts, then you're largely set to go into the broader area of ai, whatever that is.
Whether that's backend technical analysis for you, image generation, or strategy. I think that those are the initial. [00:42:00] Things that I would do, and I, they sound basic, but really you need to have 10 hours or more into these tools before you start to do it right and start to really like your results. My first AI generated images were horrible.
Something between a peacock and a John Deere tractor came out. I don't really know what happened there, but. But it, yeah, not as cool as I thought, or not as cool as maybe as described as. But uh, nowadays I'm a lot more comfortable with it. I understand the parameters, uh, and how the technology works, and so not that I always get everything I, I wish for, but I'm, I.
Able to get closer, uh, to my ideal. So using those as the frame, as the approaches is what I would do. And once you've got that, I know it sounds odd to like leave the technical learning and the framework till after you've experimented, but I really do think experimenting is more valuable and then you can go back and say, okay, here's this.
System I learned online called Craft, which is one of our internal frameworks that we deploy. How can I think back on what I've done before in a way that would make it [00:43:00] better had I used this? So you need to grow at the same time that the tool's learning about you.
Anne: Yeah. That makes, I love that. Uh, and and part of it is really just getting hands on with it because one of the things I talk about a lot, you've heard me talk about this, is that when there's something that's truly very new and you've grown up in a different time, a different set of tools, I.
Um, interrupting your own workflow like intentionally is hard because your brain doesn't naturally find like, oh yeah, I have all these uses for ai because it didn't exist before in that way for you, for most people. So I love that, and I think the idea, and you mention COT Intelligence, a book by Ethan Molik of Stanford.
For anyone who hasn't read it, it's a good. I mean it's, it feels like, again, it was published a long time ago 'cause everything's moving so fast. But he is really looking at it from a very human, but also a business leader, not a technologist. Like he, his academic study is business. And so I think he's thinking about it in a great way and to put in 10 hours to get [00:44:00] familiars a lot easier than 10,000, which is the old mastery, you know, level.
So getting hands on is great. So there's always one final question here on building brand gravity, which is what has you and its gravity these days. What, what are you into? What are you reading? What are you thinking about, Lauren?
Loren: Uh, there's two that come to mind for me. First off is the book Dune.
Obviously we've had some good dune movies come out, but there's a very interesting approach to artificial intelligence in that series that is informative. It's often not really considered, but if you like, uh, to approach big ideas through the vein of fiction. That's a good way to do it. Another one, and I'm really showing my nerd card here, but, uh, and or the Star Wars TV show has just released its second season and.
Unlike many, there isn't a lot of this technological deployment. It's made like a traditional movie. There's a lot more real sets, there's a lot less, you know, CGI backgrounds, which I'm drawn to as I get more into using tools like ai. I also, on the opposite side, like to go more towards fully human created things [00:45:00] for my entertainment.
So I don't know why that is. That's just kind of the way my subconscious has been going recently, but I've been drawn into both.
Anne: I love it. Those are great recommendations. And I think the re continuing relevance of fiction like Dune, you know, as we come into these more and more modern societies, you know, sometimes it ends up like very dystopic, but I think also it's really interesting, like you mentioned Asimov early on, like how do we.
As humans think about living side by side with machines. The good, the scary, the bad, and let's try to create the world we wanna live in. But, um, Lauren King, again, thank you so much for being a guest today on Building Brand Gravity. I really always appreciate our conversations.
Loren: Absolutely. Wow.
Steve: I mean, that's really what makes Lauren's perspective just so valuable.
And, and what I really liked about that discussion, Anne, is you know, he wasn't just reflecting on the present state of technology and brand. He was really pushing us to reimagine the role humanity should play [00:46:00] in the continued evolution of AI and technology. And I guess my takeaway when I, when I heard that was that if you're a leading.
Brand or a team right now. My big takeaway from that is don't just react to technology. Design with intention, right? Use narrative, use imagination. And I like how we encourage us to even consider fiction, you know, as a, as a tool to help you shape a strategy. And maybe most importantly, and I know you say this all the time, you can put technology at the center, but you.
Cannot lose that human thread. So I really like that idea of let's try and create the world we wanna live in. Yeah. Powerful stuff.
Anne: I, I think it's great. And the thing that's wonderful about Lauren too is his enthusiasm and his deep, deep driving curiosity. When we get on the call, I mean, we could have chatted about 7 billion things, um, aside from our work as practitioners and our sectors that were specialized in the technology.
But I think it's [00:47:00] that, um, that is an example of what we all need to bring to this, the enthusia to the enthusiasm, the curiosity, the excitement, um, and the ability to connect the dots. And also what I love, I'm seeing this a lot more, not just in our firm, but you know, as I circulate around. A lot of sense of, um, shared.
Responsibility to be counselors to one another. So how do we help our peers and colleagues come up to speed solve for problems? There are gonna always be earlier adopters. There's going to be technology coming like it always has, and there's people who, it just is like breathing air. It totally makes sense.
I mean, if you remember that story Lauren told he first was engaging with AI years ago when he was so much younger as a teenager and, and. So this has been a long journey for him, despite him being a bit younger than you and I. So I think that idea of helping your peers, those of us who are natural adopters on certain aspects of it, [00:48:00] looking to say, Hey, come to me with a problem to solve because this is a whole new world.
And that is what makes me excited about the pivot to come, I think.
Steve: Well, and, and it, it also struck me as I was just hearing you talk right now, you know, you, you had made a comment, we, we do every year an employee survey and a road show. And, and Anne made a comment that, that she said, you know, we are going to be the first generation who is not just gonna manage humans.
We are gonna be, we are gonna be managing AI agents, you know, and just kind of that bifurcation. So as we're trying to create that world we wanna live in, you know, that's, that's something that's out there. And it, it kinda struck me, you know, we always like to end this thinking about what's in our gravity and this conversation of that.
Just really reminded me of a, of a article I saw in the Wall Street Journal recently by Isabella Basque, and the title was Walmart is preparing to welcome its next customer, the AI [00:49:00] Shopping Agent, and I. It was just fascinating to think about that build from what we were talking about and, and pardon me, I was just gonna read a little bit of this, but said Walmart is preparing for sweeping changes in the way customers shop, investigating how to make products appealing, not just to human consumers.
But also to the AI agents that will one day shop on their behalf. At some point in the future, shoppers will deploy an agent and tell it that they wanna restock on groceries or buy a new flat screen tv. The operator will then scan the internet and service relevance products based on what it knows about the user's preference, and ultimately the agents may even be able to complete the purchase, including.
Payment. So, wow. Talk about the marrying of the, of the human and the ai. Talk about reimagining a world or thinking ahead. I, I think that's like a perfect blend of your conversation with Lauren and, uh, [00:50:00] just the change we're seeing as we try and create this new world.
Anne: It's like we're all be celebrities with personal assistance, except there'll be AI agents.
There's a great little clip that's been going around in social about a month or two ago. I, I think it's real, but you know, you have to ask yourself questions about it. But it sort of showed the interaction between like one AI agent trying to book a hotel and that the hotel had its own AI agent. And when they both realized they, I'm, I'm anthropomorphizing them.
They're like, oh, let's communicate in more computer code. Like, you know, like bloop bleeps, you know, ones and zeros than, than human language. And so they start to, I I think it might be legit. Others may have seen it if it's fake. I, I totally own that. But I think it's a real, real metaphor, which is there's going to be so much of that AI agent to AI agent interaction.
And, and the question of what really, and Lauren said it too in the call, what really is agentic ai? Where are agents like. They're gonna be coming and I think it's gonna be both fast and organic at the same time. [00:51:00] It's funny because one of the things that I was in my gravity when we were reflecting, you know, building brand gravity, was this point about two stats I've heard, or two comments I've heard recently.
One was yours about the fact that even entry level, I think it was the CEO of Jasper AI, said this in a Fortune CEO, um, newsletter that Diane Brady does. He said. For entry level folks, we're going to have to be thinking about their management skills because they'll be managing AI agents as if they're like an intern or they're a a colleague.
The other quote I'd heard is that this generation of CEOs will be the last to only manage human employees, that there will be agents as well. And I've always thought of technology as a strategic asset, but now I have to think about it almost as. Workers. And I think that's a big psychological shift that we need to make.
Um, the other more fun thing I have in my gravity is many people are listening to this 'cause it's already shooting to the top of the podcast list. But Amy PO's new [00:52:00] podcast, good hang, is a joy bomb. It's a bomb of joy. It's fun. Jack Black, Tina Faye, she just had Michelle Obama on. Uh, it's very interesting to see more of these types of figures enter the podcast game.
And as we have a podcast too, in our own little world, I'm always looking for, um, you know, what are they doing and how are they doing it? So I definitely recommend that to others.
Steve: Yeah, I'll have to check that out. That sounds exciting.
Anne: Well, we're coming to the end of another episode. Thank you for those who listen to both parts of the AI mini series.
As Steve said, if you didn't listen to the one with Greg. Go back and check it out. And as always, find us wherever you find your podcast and on YouTube and we really thank you for listening.
Steve: Have a great day. Tune in soon. We'll be back with more exciting conversations on how we can build brand gravity.