This article was based on the interview with Georgia-Pacific’s Jason Ippen on the intersection of brand creativity and AI by Greg Kihlström, AI and MarTech keynote speaker for The Agile Brand with Greg Kihlström podcast. Listen to the original episode here:
There’s a peculiar tension in the air of every marketing leadership meeting I’ve been in recently. On one hand, we’re rightfully captivated by the promise of AI—the potential for unprecedented efficiency, hyper-personalization at scale, and data-driven insights that can sharpen our every move. The allure of the algorithm is strong. It promises a world of optimization, of predictable returns, of taking the guesswork out of what was once a notoriously unquantifiable discipline. On the other hand, a quiet unease is setting in. As we all rush to adopt the same sophisticated tools, we risk being herded toward the same data-driven conclusions, the same optimized copy, and the same algorithmically-approved visuals. The result? A creeping, insidious sameness that threatens to erode the very thing we’re all paid to build: a distinctive brand.
This is the central paradox for today’s marketing leader. How do we embrace the machine’s power to execute without sacrificing the human judgment required to be memorable? How do we balance the relentless pressure for short-term performance with the long-term, patient work of building brand equity? It’s a challenge that requires more than just new tools; it demands a refined philosophy. In a recent conversation with Jason Ippen, Vice President of Brand Strategy and Content at Georgia-Pacific—a steward of iconic household names like Brawny, Angel Soft, and Dixie—we explored this very issue. His perspective is a refreshing and necessary corrective to the current hype cycle, arguing that in an algorithmic world, the fundamentals of brand building aren’t just relevant; they are our most potent offensive weapon.
Defending Distinctiveness in a Sea of Sameness
The first casualty in a world over-optimized by algorithms is distinctiveness. When every brand is fed the same performance data, the same cultural signals, and the same best practices, the logical output is convergence. AI, in its current form, is a masterful synthesizer, not a truly original creator. It excels at finding the mean, the pattern, and the most probable path to a click. The risk, as Ippen sees it, is that we let the machine’s logic supersede our brand’s identity.
“If you let [algorithms] 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 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.”
This is a critical mindset shift. The “real job” is no longer just about persuading consumers that our paper towels are marginally more absorbent. As Ippen notes, marketing science shows that being easily recognizable often matters more than being demonstrably different. In low-consideration categories—and let’s be honest, most categories are lower-consideration than we marketers like to admit—consumers buy what comes to mind easily. This is where the hard-won assets of a brand—its colors, characters, jingles, and tone of voice—do the heavy lifting. These “codes,” as Ippen calls them, are memory structures. Defending them against the homogenizing pull of optimization isn’t an act of nostalgia; it’s a strategic imperative to ensure your brand is the one that surfaces in a buyer’s mind, and increasingly, in a machine’s recommendation.
The New Operational Model: Human Judgment, Machine Speed
The practical question for every leader is how to integrate these powerful new tools without losing control of the brand. The prevailing concept is “human in the loop,” but that phrase can feel vague. Ippen offers a more precise model: tiering the work based on the level of judgment required. The goal isn’t to have humans meddling in every step, but to have them making the decisions that matter most.
“Where humans stay essential is deciding whether an idea is right. 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 question becomes the bigger source of error, not the tool.”
This reframes the role of the modern creative and strategist. The high-value work is no longer centered on the manual craft of execution—resizing assets, versioning copy, or adapting campaigns for dozens of retail partners. That is precisely the kind of high-volume, low-judgment work that AI should, and will, consume, freeing up our best minds for more critical tasks. The indispensable human contribution lies in taste, stewardship, and strategic framing. It’s the ability to assess an AI-generated concept and declare it “off-brand,” even if it tests well. It’s the wisdom to ask the right question—the prompt that leads to a breakthrough idea instead of a generic one. As leaders, our focus must shift from managing production pipelines to cultivating and protecting this critical layer of human judgment within our teams.
The Biggest Risk: Death by a Thousand Optimizations
Perhaps the most counter-intuitive—and most important—point Ippen makes is about risk. In a performance-driven culture, the greatest perceived risk is launching a bold campaign that underperforms. We mitigate this through endless testing and iteration, optimizing every element for maximum short-term engagement. But Ippen suggests this approach hides a much larger, more insidious danger.
“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.”
This is a courageous stance in an industry obsessed with real-time feedback loops. It posits that the constant churn of micro-optimizations, while individually defensible, can collectively lead to brand equity erosion. A brand that is constantly tweaking its message and its look to chase fleeting performance signals becomes incoherent over time. It becomes harder for consumers—and algorithms—to learn what it stands for. The alternative model is one of front-loaded judgment: invest heavily in getting the core brand platform and the big message right, and then execute it with disciplined consistency. This doesn’t mean flying blind; it means using AI tools for “disaster checks” on clarity and readability, not as the final arbiter of the creative idea itself. This approach requires trust in the creative process and the fortitude to defend a long-term vision against the siren song of short-term data.
Cultivating the Next Generation of Brand Stewards
This new reality presents a looming challenge for talent development. If we automate the foundational tasks where junior talent has historically honed their craft and developed their “gut feel,” how do we ensure the next generation of leaders builds the very judgment we’ve just identified as essential?
“The people that we have working on the tools today developed their judgment doing work that we are now handing over to AI. So that’s a question for us is… 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.”
This is a question every marketing leader should be asking. The answer isn’t to halt progress, but to be intentional about creating new pathways for developing taste and strategic intuition. It may involve more structured mentorship, simulation-based training, or rotating junior talent through roles that force them to “frame the question” rather than just execute the answer. The ideal brand builder of the future, as Ippen sees it, is someone grounded in the fundamentals of marketing and behavioral science, combined with an agile, self-starter mentality to continuously learn new tools. The tools will change, but the understanding of how brands grow is the bedrock that allows a marketer to properly judge what those tools are telling them.
Ultimately, the message from our conversation is one of confident reassurance. The rise of AI and algorithmic marketing does not render brand strategy obsolete; it elevates its importance. The fundamentals—distinctiveness, consistency, and long-term stewardship—are no longer just defensive measures to protect brand equity. In a world where machines are learning from the signals we create, these disciplines become our primary offensive tools. A brand with a clear, consistent, and distinctive presence is easier for both people and algorithms to recognize, recall, and recommend.
As we look ahead to a future dominated by AI assistants that provide one answer instead of a list of links, the stakes will become even higher. The consideration set will collapse, and the brands that have invested in building strong, consistent associations will be the ones that get named. Ippen’s parting thought frames this perfectly: “Stewardship used to sound sort of defensive. I think in this world it’s offense.” For marketing leaders navigating this new landscape, the path forward isn’t about choosing between human creativity and machine intelligence. It’s about harnessing machine speed to execute a brand strategy guided by unwavering human judgment. The algorithmic world has, in effect, raised the return on our oldest and most valuable disciplines.
