In This Episode
As algorithms and AI increasingly automate the “”what”” and the “”how”” of marketing, what is the enduring value of human creativity, and how do we prove its worth?
Agility requires not just adapting our tools, but fundamentally rethinking how we define, nurture, and measure creative value in a wIn this episode
Jason Ippen, Vice President of Brand Strategy & Content at Georgia-Pacific, makes a counterintuitive case for the AI era: as generative tools push every brand toward the same signals, the winning strategy isn’t to be more differentiated — it’s to be more recognizable. Drawing on more than 15 years steering brands including Angel Soft, Quilted Northern, Brawny, Sparkle, and Dixie, Jason walks Greg Kihlström through why distinctiveness is now a defensive discipline, how his internal creative agency tiers work between human judgment and machine execution, how to measure brand health when there’s no closed performance loop, and why the next battleground is being named in AI-generated answers.
Key takeaways
- Recognizable beats differentiated. People buy what comes to mind easily and what they recognize; the characters, colors, and codes that are unmistakably a brand do more work than years of trying to persuade consumers of a difference.
- Algorithms point every brand at the same signals. Let AI tools dictate what you say and how you show up, and they’ll make you sound like everyone else — so defending and reinforcing what makes a brand distinct is the real job today.
- The big organizing idea still holds; the tempo changed. A brand platform that stays stable over years now has to show up continuously across far more channels and formats, at a pace older processes weren’t built for.
- Consistency beats constant novelty. Brands are built through repetition of the same associations over time — and marketers tend to get bored of a campaign long before consumers have even become familiar with it.
- Tier creative work by the judgment it requires. High-volume, low-judgment tasks — versioning, resizing, retailer-specific adaptations — can go to AI, freeing creatives for higher-value work; humans stay essential on taste, brand stewardship, and framing the question.
- As the tools improve, the question-framer becomes the bigger source of error, not the tool. AI will confidently answer bad questions, so judgment about what to ask is the durable human role.
- Adoption hurdles moved from skepticism to the learning curve. GP kept teams close to the tools’ improvement, then blocked training time and ran deadline-free sprints; the hurdle ahead is whether junior talent can still build judgment once AI handles the work that used to build it.
- Optimize distinctiveness, not every asset. The bigger risk isn’t one big idea underperforming in one environment — it’s many small, individually data-justified changes that stop adding up to the brand.
- In an algorithmic world, stewardship is offense. Distinctive, consistent brands are easier for both people and machines to recognize and recommend — and the coming test is which brands get named when an AI assistant returns one answer instead of a page of links.
Chapters
- 01:32 — The creativity question as AI automates the “what” and the “how”
- 03:04 — Jason Ippen and Georgia-Pacific’s consumer brand portfolio
- 04:38 — Why “recognizable” beats “differentiated”
- 06:29 — The durable big idea vs. hyper-personalization
- 08:41 — Tiering creative work: what to hand AI, what to keep human
- 10:41 — Moving teams past skepticism to real AI adoption
- 15:10 — Measuring brand health without a closed loop
- 17:12 — Protecting distinctiveness over asset-level optimization
- 18:58 — The ideal brand builder: fundamentals plus agility
- 20:27 — The mindset shift: fundamentals matter more, not less
- 22:22 — One year out: getting named in AI-generated answers
- 23:24 — Staying agile day to day
Why “recognizable” matters more than “differentiated”
For years, marketers focused on convincing consumers of their differentiation. Jason argues the science points elsewhere: nobody has a deep relationship with paper towels, and people buy what comes to mind easily and what they recognize. That makes the distinctive assets of a brand — its characters, colors, and codes — the real engine, and it makes homogenizing AI output the real threat. When tools point every brand at the same signals, the job shifts from persuasion to defending recognizability.
The durable idea in a hyper-personalized world
Even as content gets granular, targeted, and one-to-one, Jason holds that a large, stable organizing idea matters more than ever. What changed is how it shows up — continuously, across many channels and formats, at modern speed. The pressure to chase cultural relevance and constant novelty is rising exactly when the evidence for consistency is strongest, so the discipline is to let a big, durable idea show up consistently rather than drift in search of relevance.
Where humans stay essential when machines execute
Georgia-Pacific runs an internal agency that uses AI across copy, images, and video, then tiers work by how much judgment it needs. Low-judgment, high-volume tasks — versioning, resizing, retailer adaptations — go to AI, which frees creatives for more valuable work. Humans stay indispensable on deciding whether an idea is right, catching an execution that’s technically fine but feels off, and framing the question in the first place. As tools improve, framing becomes the bigger error source, and that isn’t automating anytime soon.
Measuring brand health when there’s no closed loop
Without a performance-marketing feedback loop, GP tracks whether people recognize its brands from assets alone, whether they recall ads and link them to the brand, and — more recently — category entry points, i.e. whether the brand comes to mind in the moments people actually buy. Jason is candid that these indicators are imperfect, slow-moving, and noisy. What makes it work is leadership that understands what the research can and can’t tell them, so short-term numbers don’t win by default.
Why stewardship is offense, not defense
Rather than testing at scale, GP prioritizes distinctiveness: the biggest risk isn’t a bold idea that underperforms in one environment, but many small optimizations that individually look justified yet stop reinforcing the brand. The team gets the big message right, stays consistent, and uses an AI pre-flight tool to check craft — branding clarity, readability, attention — while the idea itself stays a human judgment call. In this frame, stewardship stops being defensive and becomes the offensive move.
The next frontier: being named in AI answers
Looking a year out, Jason points to AI-generated answers as the place that matters most. As search turns into conversation, an assistant returns one recommendation instead of a list, collapsing the consideration set. The brands that get named will be the ones with the strongest, most consistent associations in the open web — so the memory structures brands have spent years building now have to exist in how machines represent them.
FAQ
Does the “big campaign idea” still matter in an AI-personalized world? Yes. Jason argues a stable brand platform matters more than ever; what changed is that it has to show up consistently across many more channels and formats at machine speed, without drifting in search of novelty.
What creative work should marketers hand to AI? High-volume, low-judgment tasks — versioning, resizing, and retailer-specific adaptations — which frees creatives for work that actually requires judgment.
What stays human? Deciding whether an idea is right, catching an execution that’s technically fine but feels off, and framing the question in the first place — the part that becomes more important, not less, as the tools improve.
How do you measure brand building without performance-marketing metrics? Track brand recognition from assets alone, ad recall linked to the brand, and category entry points, while staying transparent about how imperfect and slow-moving that data is.
How should brands prepare for AI-generated answers? Build the strongest, most consistent brand associations in the open web, because AI assistants collapse the consideration set to a single named recommendation.
What’s the single most important mindset shift for brand leaders? Realizing that fundamentals — distinctiveness, consistency, and stewardship — matter more in an algorithmic world, not less.
About Jason Ippen
Jason Ippen is Vice President, Brand Strategy & Content at Georgia-Pacific, where he leads brand strategy, innovation and marketing for a portfolio of some of the country’s most recognized consumer brands. Over the course of more than 16 years with the company, he has held leadership roles across brands including Quilted Northern, Sparkle and Vanity Fair, helping drive growth through consumer insight, product innovation and brand building.
Jason has more than 25 years of experience spanning consumer packaged goods, marketing and general management. He earned an MBA from Columbia Business School and a bachelor’s degree from Colgate University.
Jason Ippen on LinkedIn: https://www.linkedin.com/in/jason-ippen-1120086/
Resources
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Transcript
[00:01:32] Greg Kihlström: [gentle music] As algorithms and AI increasingly automate the what and the how of marketing, what is the enduring value of human creativity, and how do we prove its worth? Agility requires not just adapting our tools, but fundamentally rethinking how we define, nurture, and measure creative value in a world increasingly guided by machine logic. Today we’re going to talk about the intersection of brand creativity and artificial intelligence. We’re gonna explore why brand distinctiveness becomes a critical differentiator when algorithms favor similarities, not differences, the new operational model for creative teams where human judgment guides machine speed execution, and strategies
[00:03:04] Greg Kihlström: To help me discuss this topic, I’d like to welcome Jason Ippen, Vice President, Brand Strategy and Content at Georgia-Pacific. Jason, welcome to the show.
[00:03:13] Jason Ippen: Thank you so much for having me.
[00:03:14] Greg Kihlström: Yeah, looking forward to, to diving in here. Before we do, though, why don’t you, give a little background on yourself and your role at Georgia-Pacific?
[00:03:22] Jason Ippen: Sure. I lead brand strategy and content for GP’s consumer business. most people know our consumer brands, Angel Soft bath tissue, Brawny towels, Dixie plates, among others. We also have a large B2B business in food service and commercial hygiene. And my team helps the business develop and steer our brand equities and turn that brand thinking into content and experiences for our customers. So I’ve got a team of very skilled strategists, designers, and creatives supporting our business teams.
[00:03:49] Jason Ippen: And, and I’ve been at GP for over 15 years, and, and to the subject that we’re gonna talk about today, I think fortunately we’ve got a number of ingredients that I think really help, face the challenges that we’re highlighting in this conversation. I think first and foremost, we’re consumer-centric. Leadership is focused on anticipating our customers’ needs. We have an expectation to constantly transform and find better ways to do our work, and we prioritize the long-term value over the short term. And I think that last pairing is, kind of helps address the question in a nutshell. this transformation mindset, says we have to embrace all of these new tools and that they’re changing the way we work almost monthly. but that longer term mindset says our consumers still need to see us as the trusted brands they know. So holding
[00:04:34] Jason Ippen: both at once is the real tension, and honestly, I think that what makes this work fun.
[00:04:38] Greg Kihlström: Definitely. And so, yeah, to, to dive in here, a- as I teed up in the intro, it’s really, the, the concept of brand strategy certainly has not fundamentally changed in the last few years, but the way that marketing is done and has changed in, in many ways, or at least new tools have been added to the mix, and, you know, f- both from the consumer side as well as from the marketer side. And so, you know, one, one of the risks that we run with just a lot of AI-generated content using the same tools, you know, one brand using the same tools as another brand, is that brands start to look and even sound the same. How does this, change the strategic importance of brand distinctiveness,
[00:05:24] Greg Kihlström: and what does even being distinctive mean today?
[00:05:28] Jason Ippen: Yeah, it’s a, it’s an important topic. I think there’s a lot of conversation in the industry around this question of, um … And I think it helps to address what is distinctiveness, as you mentioned. I think for years we focused on trying to convince consumers of our differentiation, and that was really about persuading and convincing. And I think the marketing science is pretty clear that recognizable matters more than most of us were taught. nobody has a deep relationship with paper towels. I say that with love. I think people buy what comes to mind easily and what they recognize, and it’s less about convincing. So distinctiveness, the characters, the colors, the codes that are unmistakably our brands, do more work than we’ve maybe historically given it credit for. So essentially, that’s what we need to be prioritizing. And I think that’s the real risk with algorithms. If you let
[00:06:14] Jason Ippen: them tell you what to say or influence how we come to life, they’re gonna make us sound like everyone else because they’re pointing every brand, brand at the same signals. So now more than ever, we have to defend and reinforce what makes us distinct. That’s the real job today.
[00:06:29] Greg Kihlström: And so y- another component of, of that traditional brand strategy is really this, this big campaign idea. And, you know, as a, as a recovering agency owner myself, you know, certainly done a lot of pitches and, the, you know, that’s, that’s a familiar way of, of approaching things, but we’re moving more and more into this fragmented, personalized, sometimes one-to-one personalized at this point, and AI-assisted world where, you know, content is being, is very granular and, and targeted at the, at the consumer. Does this model of this big idea still hold and, you know, how are– h- how does a brand kinda keep these two things in, in parallel,
[00:07:15] Greg Kihlström: like the, the big idea and yet the, the hyper-personalization?
[00:07:19] Jason Ippen: Yeah, I, I think it’s we have to be doing, both to some degree. I think what matters more than ever is this large organizing idea. I mean, a brand platform that stays stable over years. I think what’s changed is how it shows up continuously across lots of channels and formats and at a pace that our older processes probably weren’t built for. so the real challenge is the pressure. With so many platforms, so many moments to connect with culture, influencers, this push to be authentic, we can feel like we need to constantly be doing new and different things, and I think that pressure is increasing at a moment when we’re learning more about how much consistency matters. So brands that are built through repetition of the same associations over time, they’re not built through constant novelty. And that’s not to say that
[00:08:04] Jason Ippen: we can’t be a part of culture. We can and should where it makes sense and reinforces what makes us distinct. but we can’t get bored with our own ideas or let them drift in search of relevance or personalization. you know, we find our marketers can get tired of their campaigns long before they’ve become familiar to the consumers or the customers we’re trying to connect with, so, and they can feel the pressure as well to chase cultural relevance, which can cost us this grip on distinctiveness. So our job is, I think remains, a big, durable idea that shows up consistently at modern speed across a much broader network of touchpoints.
[00:08:41] Greg Kihlström: So let, let’s talk about the– how, how this gets operationalized as well, and certainly, you know, there’s a lot of talk about human in the loop is kind of the, the, the term du jour for, for this, this approach. But, you know, when you think about this concept of, of human judgment paired with machine execution, you know, certainly it, it, it sounds good and s- and sounds, reasonable, but what exactly does that mean? You know, where, where is the, that indispensable role for human creatives and which parts of the process are– make a lot of sense to, give to AI and, and automation to do without sacrificing what, what you’re talking about here and the, you know, that, that, that overarching concept?
[00:09:28] Jason Ippen: Yeah. I think having humans in the loop is important, but they’re not necessarily in every loop in the same way. And, and I have an internal agency in the team, and this is a daily question. Like all agencies, we use lots of AI tools across copy, images, and video, and then we tier our work on how much judgment any of these projects is gonna require. and we’re happy to offload work that does not require a lot of judgment, so versioning, resizing, if we have retailer-specific adaptations. It’s high volume. It can eat up a lot of creative capacity, and I don’t think anybody on the team got into the business to do that work. So handing that to AI frees up creatives, to create more value in other places. where humans stay essential is deciding whether an idea is right.
[00:10:13] Jason Ippen: I mean, taste really matters. Brand stewardship matters. It’s important to be able to catch an execution that’s technically fine but just somehow feels off. That’s critical. and then a big one is framing the question in the first place. So these tools will confidently answer whatever you ask, including bad questions or bad directions. So as the tool improves, the person framing the questioning become the bigger source of error, not the tool. So that’s judgment, and I don’t see that automating anytime soon.
[00:10:41] Greg Kihlström: And so, you know, I, I certainly don’t wanna discount the technology component or even the data component. Those are certainly things that I deal with, daily and when as a consultant. But the, another huge part of this is the, the people and the, the process component here and adopting AI-based tools and, and methods and, and creating those, those, those processes with humans in the, in the loop, often requires a, a significant cultural and even a skill set shift. What are some of the biggest hurdles that you’ve seen and, and, perhaps faced in, in getting, you know, marketers that have been trained to do things a certain way, creatives that, that have been,
[00:11:26] Greg Kihlström: doing things for, for years and years in, in similar ways to embrace data-driven decisions, AI-based tools, not as a threat to their, to their jobs, but really as a, a creative partner?
[00:11:40] Jason Ippen: Yeah. It, it’s been a journey, and I think that the hurdles have changed along the way. I think f- the first hurdle was skepticism, I think which in large part was probably fair. A couple years ago, our creatives would see bad copy or they’d see weird images created by tools and just conclude that they weren’t fit for purpose. and at the time, I think they were probably right in many cases. But our job wasn’t then to debate that but to keep the team close to the improvements being made in the tools and then find use cases where even imperfect cool tools could be helpful. and as a result, I think we’re able to address the skepticism as early as possible. But as we shifted from that skepticism, then the next big challenge was making room for the learning curve. All these changes are happening while creative demand continues to go
[00:12:25] Jason Ippen: up, so we found creatives unable to really learn how to best use the tools. So we block time for training and run sprints where creatives push the tools without having a deadline hanging over their head. And, and this has really led to an acceleration of adoption, and I think allowed them to see how their, craft can be amplified, through the use of the tools. But I actually think there’s a, there’s a hurdle ahead, related to judgment, and, one thing we wonder about is we’ve armed people with information and tools that provide really well-packaged answers, but we need to have continued good judgment to assess those answers. And the people that we have working on the tools today developed their judgment doing work that we are now handing over to AI.
[00:13:11] Jason Ippen: So that’s a question for us is are– will more junior talent be able to build that same judgment, or will they become reliant on AI to the detriment of that? And I think that’s a big hurdle looking forward that we think we’re gonna have to overcome.
[00:15:10] Greg Kihlström: Let’s, let’s talk a little bit about, you know, on the topic of, of brand and brand strategy, certainly there’s, there’s a big difference between measuring, you know, per- like, performance marketing metrics, and I’ll just call it brand performance, metrics. what I’ve seen, there’s, you know, there’s, there’s definitely a lot of pressure for short-term optimization, short-term metrics, but those are not necessarily what you need to measure brand health and, and building a memorable brand. How do you kinda reconcile the two, you know, the, the, the need for those short-term metrics and, and performance with actually understanding if your creative work is, is building
[00:15:55] Greg Kihlström: a, a memorable brand?
[00:15:58] Jason Ippen: Yeah, we, we don’t have a closed loop, so there’s less performance marketing in our space in a lot of cases. But we track whether people can recognize our brands from assets alone and whether that’s strengthening or weakening over time. We track people recalling our ads and whether they link them to our brands. That linkage is, of course, very important. And recently, we’ve started looking more deeply at category entry points. So it’s already doing a click down, is the brand coming to mind in more of the situations where people actually buy? that said, we recognize that these indicators are imperfect, and they move slowly, and time adds a lot of noise. we can do everything right and not see in the data for a while or see movement that has nothing to do with what we do. So for us, I think a critical success
[00:16:43] Jason Ippen: factor has been our leadership. I think we have a data-driven company, and we’ve had to learn to be transparent about the limits in the data that we have rather than oversell what the measurement can truly tell us. and what makes it work is we, our leaders understand what we’re trying to do. They understand what the research can and can’t tell us, and they know that the principles are right. I think without that, the short-term numbers would win by default, and we might end up chasing clicks or being too overly focused on the data that’s available to us.
[00:17:12] Greg Kihlström: Yeah. I wonder if you could talk a little bit about your test- testing and, and creative iteration process too. So, you know, certainly AI-driven tools are, are able to accelerate some of the, the learnings there. Have, have they changed your approach to risk-taking? Like, are you able to place m- perhaps more and smaller bets on, on bold ideas, or does the data tend to push creative work toward a safer, space?
[00:17:45] Jason Ippen: Yeah, we have a maybe a different take on this a little bit. I think we– we’re not as focused on the testing at scale, and this may be a shift, but we’re really prioritizing our distinctiveness. And what I mean by that is if distinctiveness is the most important thing we own, then the biggest risk isn’t a big idea that underperforms in one environment. The bigger risk is making lots of small changes, each one justified by some data, or data point, but they don’t all reinforce what makes us distinct. So we worry if we optimize every asset that over time it’s gonna stop adding up to our brand. And so our model is to get the big message right and be consistent with it. We put the work in up front, and when we believe in a message, we’re not worried about small performance differences across different environments. Now, to your point on AI
[00:18:30] Jason Ippen: tools, we’re not flying blind. We have an AI tool to pre-flight test work against creative best practices that’s quick and, and inexpensive. And that’ll help us know, is our branding clear, copy readable? Is attention going where we intend it? And that definitely does a disaster check, but the idea itself stays the judgment call, of the creatives. So I think in a, in a world where constant iteration and optimization, that might feel different, but we feel it’s the, the, the better bet.
[00:18:58] Greg Kihlström: Yeah. Well, and then, and then looking ahead and, you know, I know, I know you’ve t- touched on the, just the, the value of, of, of judgment in, the, the human part of the teams. Looking at the talent that, you wanna bring into the organization, in the future, what, what does the ideal brand builder of the future look like? You know, is there … Certainly there’s gonna be a blend of things, but, you know, when we look at skills, artistic, analytical, tech- technical, you know, what, what’s that ideal mix as you’re kind of planning for, for that team member of the future?
[00:19:35] Jason Ippen: Yeah. It, it feels to me maybe that it’s not that futuristic. I think we really wanna focus on foundations first.
[00:19:42] Greg Kihlström: Yeah.
[00:19:43] Jason Ippen: So we need people that understand how brands actually grow, the marketing, the behavioral science, and that’s how they’ll learn to judge all the new tools and what those tools are telling them, and someone fluent in tools without that foundation is gonna make mistakes faster. I think the second thing, which is good for this podcast, is agility. you know, we care less about which tools someone knows today, but those turn over every few months, and that’s only accelerating. So, we care that the person, not that they’re the kind of person who picks up new tools without being told, but we have to have them really constantly exploring new tools and constantly looking for new ways to, to, to grow themselves. Self-starters who own their own growth.
[00:20:27] Greg Kihlström: And then I wonder i- if you could share what would your advice be to a leader that is, you know, thinking about one, one of the themes that, that I’ve really heard that you’ve been sharing here is just that need for, to build a, a, a consistent brand despite all the temptations to use all the tools and, and do lots of, lots of, new and interesting things. There, there’s, there’s a value in, in building something that consumers can really understand what, what it is that they’re buying. So, you know, I wonder, you know, what’s, what’s the single most important mindset shift that a leader needs to make to ensure that their brand, you know, not only survives, but thrives in this, you know, increasingly kind of algorithmic world?
[00:21:12] Jason Ippen: Yeah. It’s a great question. Honestly, I’m not sure if it’s a shift. I think the most important mindset is realizing fundamental ma- fundamentals matter more in an algorithmic world, not less. I think there’s, and you used a great word, temptation to believe that everything has changed, that brand knowledge, consistency, stewardship are sort of old-fashioned, that we should be focused on performance marketing and real-time optimization, and, and I argue the opposite. Algorithms, a retail search ranking, a social feed, an AI assistant, they learn from the signals that already exist about our brands. Distinctive, consistent brands are easier for both people and machines to recognize and recommend. That’s just the world works, I believe, and brands that constantly reinvent themselves are harder to learn for anyone or anything. So marketers who will win,
[00:21:58] Jason Ippen: will know their brands deeply. They’ll defend their consistency and distinctiveness, sometimes against short-term data signals. They’ll understand how those disciplines influence what algorithms reward. stewardship used to sound sort of defensive. I think in this world it’s offense. If there’s a shift, it’s that the algorithmic world raised the return on the old discipline. it didn’t replace it.
[00:22:22] Greg Kihlström: Love it. Well, Jason, thanks so much for joining today. I got two questions for you here as we wrap up. First one, if we were having this interview one year from today, what is one thing that we would definitely be talking about?
[00:22:36] Jason Ippen: Yeah. It’s the next chapter of, I guess, the last discussion we’re having. If, if algorithms learn from the associations that exist about our brands, the place that’s about to matter most is AI-generated answers. Search is turning into conversation. People ask an assistant for a recommendation, get one answer, not a whole bunch of links. that collapses the consideration set pretty significantly, and the brands that get named will be the ones with the strongest, most consistent associations out in, in the open web. So we’ve spent years building memory structures for our brands. now those same associations have to exist in how machines represent us. so it’s early. I think we haven’t, moved yet, but I think that’s a focus area that, what’s gonna have
[00:23:21] Jason Ippen: to be a, a priority for us in the coming year.
[00:23:24] Greg Kihlström: And last question for you, what do you do to stay agile in your role, and how do you find a way to do it consistently?
[00:23:31] Jason Ippen: I guess two things. I, I, I never stop being a student of the fundamentals. I keep reading and learning about consumer behavior and brands, because the tools change monthly, but understanding how people actually choose is what tells us, what changes are gonna matter and what’s noise. and then I do, I try to play in the tools as much as possible. I’m in them daily. I think the harder discipline is forcing myself to keep trying new ones. sometimes I find one and I feel like, “This works for me,” and then I’m surprised, you know, weeks later when someone points out just how much better they’ve gotten. So I think complacency is a real risk, and I think the moment you’re set into a comfortable toolkit, you’re gonna stop being agile, and that’s really, probably the most important thing to be focused on.
