Expert Mode: Scaling Personalization Without Sacrificing Your Brand’s Soul
This article was based on the interview with Jason Ing, CMO at Typeface by Greg Kihlström, MarTech keynote presenter for The Agile Brand with Greg Kihlström podcast. Listen to the original episode here:
For years, the twin ambitions of enterprise marketing have been pulling in opposite directions. On one hand, we have the drive for hyper-personalization—the holy grail of crafting a unique, 1:1 conversation with every single customer. On the other, we have the non-negotiable need for brand governance—ensuring that every one of those million conversations speaks with a single, coherent, and trustworthy voice. The result is often a paradox: the faster we try to personalize, the more we risk our brand’s identity fragmenting into a million inconsistent pieces. It’s a tension every marketing leader managing a global team, multiple agencies, and dozens of channels knows intimately.
The arrival of generative AI has thrown this challenge into even sharper relief. Suddenly, the ability to generate content at a previously unimaginable scale is a reality. But speed without control is just a faster way to create chaos. The conversation is shifting from treating AI as a clever creative tool to integrating it as a core operational engine. This requires a fundamental change in our approach, moving away from simply producing more assets and toward building an intelligent system that can create, personalize, and govern simultaneously. It’s about building a foundation that allows for infinite creative variation while remaining anchored to an unwavering brand core. Jason Ing, a career marketer with experience shaping brands at P&G, Microsoft, and Amazon Web Services, argues that before we can truly scale personalization, we must first build a “living brand brain.”
From Brand Book to Brand Brain: The Foundational System of Record
Most of us are familiar with the “brand book”—the proverbial 300-page PDF gathering digital dust on an intranet server somewhere. It’s a static document, a snapshot in time that relies on human interpretation and diligence for its enforcement. In a world of distributed teams and rapid-fire content demands, that model is simply no longer viable. The natural drift in brand interpretation across teams, geographies, and channels becomes a significant risk when you inject the exponential scale of AI. The first and most critical step, Ing argues, is to transform these static guidelines into a dynamic, intelligent system.
“A brand system of record is really the opposite. It’s what we consider a living brand brain…and it captures your tone, style, examples, your language, terminology, visual ID, layouts, all of the things that makes your brand distinct. And it turns it into something that AI can use in real time. So when content is created, it’s not about it being close enough. It’s actually checked and shaped by the brand agent to make sure that everything is consistent, safe, and on voice.”
This concept reframes brand governance from a passive, after-the-fact policing action to an active, real-time enablement function. By creating a “brand brain,” the system isn’t just checking for compliance; it’s an active participant in the creation process. This is the foundational layer that makes scaled personalization possible without introducing brand risk. When an AI agent is grounded in the brand’s DNA—its specific terminology, legal requirements, visual identity, and nuanced tone—every piece of content it generates is born on-brand. This solves the governance problem at the point of creation, rather than leaving it to a bottleneck of human reviewers down the line. For leaders, this means you can empower your teams with the speed of AI while trusting that the output will reinforce, not dilute, the brand you’ve worked so hard to build.
Beyond Determinism: Achieving Truly Curated Personalization
For a long time, “personalization” in marketing has been fairly rudimentary. We’ve substituted first names, recommended similar products based on past purchases, and served ads based on simple behavioral triggers. It’s personalization, technically, but as Ing points out, it’s a deterministic, rules-based approach: if you like X, you’ll like Y. It’s functional, but it rarely feels human or genuinely curated. The next frontier is moving from this mechanical substitution to creating content that feels like it was crafted with a deep understanding of the individual’s context, preferences, and even cultural nuances.
“The opportunity now is just much bigger. It’s about delivering content that feels like it was created with you in mind. So it’s human, it’s reflective of someone’s preferences, cultures, behaviors, and needs over time… A great example is we worked with a national grocery retail chain. And they use our ARC agents to produce localized culturally relevant campaign variations for different regions. So if you imagine a local supermarket, you know, what I see in Seattle might be very different than what someone should see in Texas.”
This is where the power of an AI-driven system becomes clear. Manually creating dozens of culturally relevant campaign variations for different regions would be a prohibitively slow and expensive process for most organizations. With an AI agent that understands both the core brand and the specific audience insights, this becomes achievable in hours, not weeks. It can adapt imagery, copy, and offers to resonate with a local market in Texas versus one in Seattle, all while ensuring the core campaign message and brand voice remain consistent. This is the true promise of scaled personalization: not just changing a name, but changing the context to make the message more meaningful and valuable to the recipient. This requires a system that can synthesize brand rules with audience data, a process that moves beyond simple automation to genuine, intelligent adaptation.
The Human Shift: From Asset Producers to Systems Orchestrators
The integration of AI into the marketing workflow inevitably raises questions about the evolving role of the marketer. The fear of being replaced is often misplaced; the reality is a significant elevation of the marketer’s role. As AI takes on more of the repetitive, mechanical tasks of production—resizing assets, versioning copy, formatting layouts—it frees up human talent to focus on work that requires uniquely human skills: strategy, judgment, and narrative craft. According to Ing, we are moving away from a world of channel-specific specialists and toward a future where marketers act as “systems orchestrators.”
“I see a lot of those silos between roles kind of breaking down and marketers having to adopt a much more systems point of view and being more of a systems orchestrator of these AI tools… And skills like taste, judgment, narrative craft will become the differentiator… I see us ending back in a world of like old school marketing. So think of like, you know, David Ogilvie or Mad Men, the show and those type of skills mattering much more, which is taking human storytelling, insight that just comes from lived experience and creative instinct.”
This is a powerful vision for the future of our teams. Instead of being bogged down in the production queue, marketers will design the logic, set the strategic goals, and define the audience parameters that guide the AI agents. Their value will be measured not by the volume of assets they can personally create, but by the clarity of their thinking and the effectiveness of the systems they orchestrate. This shift has profound implications for how we measure success and structure our teams. The ROI isn’t just in content velocity; it’s in the incremental conversion lift from more relevant content, faster approval cycles, reduced agency dependencies, and, perhaps most importantly, a more strategic and less burnt-out creative team. When the cost of iteration drops to near-zero, teams can experiment more freely, leading to better ideas and more effective campaigns. The focus returns to the fundamentals of great marketing: understanding the customer and telling a compelling story.
Ultimately, the journey toward AI-powered personalization is less about adopting a single tool and more about embracing a systemic change. The brands that succeed will be those that move deliberately, establishing a strong foundation of brand governance before attempting to scale. They will view AI not as a replacement for human creativity, but as an amplifier of it, freeing their best minds to focus on strategy, storytelling, and customer insight. This isn’t a speculative future; it’s an operational reality that is taking shape right now. The gap between early adopters and laggards is poised to widen quickly.
As we look ahead, the evolution will continue toward what Ing describes as “agentic workflows,” where autonomous systems create, adapt, and optimize campaigns in a continuous loop, guided by human-set goals. The challenge for us as leaders is to guide our organizations through this transition. It requires not just a technological investment, but a commitment to retraining our teams, redesigning our workflows, and rethinking how we measure value. The opportunity is immense: to finally resolve the paradox of scale and governance, and to create marketing that is not only more efficient but also more human, relevant, and resonant than ever before.
