This article was based on the interview with #847: Acquia CMO Jennifer Griffin Smith on MarTech that delivers beyond the hype by Greg Kihlström, AI and MarTech keynote speaker for The Agile Brand with Greg Kihlström podcast. Listen to the original episode here:
The deluge of AI-powered tools has created a palpable sense of urgency in every marketing department. The temptation is to chase the latest shiny object, to integrate generative AI for the sake of generating more. More content, more variations, more assets. But as seasoned leaders, we know that volume is a vanity metric if it isn’t connected to a coherent strategy. The real opportunity isn’t just about accelerating production; it’s about fundamentally re-architecting how marketing operates. It’s about moving from the tactical “ing” of marketing—the endless cycle of creating, formatting, and publishing—to a strategic focus on the market itself.
This requires a shift in mindset, from seeing content creation as a series of tasks to embracing content orchestration as a core strategic discipline. In a recent conversation with Jennifer Griffin Smith, Chief Market Officer at Acquia, we explored this very transition. As a CMO who is both a practitioner and a provider of enterprise marketing technology, Jennifer offers a grounded perspective on what it takes to move beyond the AI hype cycle. The insights shared are not about futuristic science projects, but about the practical, operational changes that enterprise leaders must consider to build a marketing ecosystem that truly delivers value, elevates human talent, and prepares for a future where winning the “answer battle” of Generative Engine Optimization (GEO) is the new SEO.
From Production Lines to Orchestration Hubs
For years, the promise of marketing technology was efficiency. The goal was to help teams do the same work, just faster. AI, in its initial application, has often been viewed through this same lens—a better, faster writing assistant or image generator. While helpful, this approach is incremental at best. It doesn’t solve the underlying operational bottlenecks or, as Jennifer points out, the pervasive issue of team burnout. The true transformation lies in moving from production to orchestration.
“Content production is humans doing the work with AI helping them around the edges… your org still stays the same, your marketing organization stays the same, and the bottlenecks stay the same… Content orchestration shifts us to a totally different realm, right? It means that humans set the direction, they define standards, they make judgment calls, but AI can handle the mechanical volume.”
This is a critical distinction for any leader structuring their team for the future. Orchestration isn’t about replacing people; it’s about elevating them. When AI handles the “mechanical volume”—the formatting, the versioning, the multi-channel assembly—it frees up your most valuable resources to focus on what Jennifer calls “the delta.” This is the space for bold insights, unique points of view, and the creative leaps that AI, for all its prowess, cannot yet replicate. In this model, mid-level managers evolve from being content reviewers into “workflow architects,” designing the automated pipelines that ensure quality and consistency at scale. The senior leaders are then liberated to focus on pure strategy, asking the tough questions and setting the creative direction that gives the brand its soul.
The Real Hurdle: It’s the Systems, Not the Silos
Every marketing leader has fought the battle against organizational silos. We’ve all been in meetings aimed at fostering cross-functional collaboration between content, data, IT, and sales. We often blame a lack of communication or competing priorities. But Jennifer argues that we may be diagnosing the wrong problem. More often than not, the friction isn’t caused by the people, but by the very systems we’ve put in place to help them.
“What has stopped us being successful… is not the people… It’s the systems that have created and we have spent years recruiting people… to fix the underlying problem of the systems and I’m not even going to name them, but we all use a lot of systems that you have to buy systems on top of the systems because the systems actually don’t work properly and it kind of drives me crazy.”
This is a sentiment that will resonate in boardrooms everywhere. The modern MarTech stack is often a patchwork of disconnected platforms, each requiring manual tagging, integration, and data reconciliation. We hire operations specialists not to innovate, but to act as human middleware, bridging the gaps between technologies that were never designed to work together seamlessly. The shift to an AI-driven orchestration model demands that we rethink this entire approach. Instead of asking teams to serve the systems, we need systems that are outcome-based. Imagine telling a “digital teammate” to build the assets needed to get 300 registrants for an event, rather than manually creating a landing page, social posts, and ad copy. This outcome-based approach is where the real power lies.
However, this increased automation brings a new, critical challenge to the forefront: governance. As AI agents begin drafting, publishing, and optimizing content, who is ensuring brand safety, compliance, and coherence? The risk of an off-brand or non-compliant bot is real. For leaders, especially in regulated industries, establishing a robust governance framework isn’t just important; it’s a prerequisite for scaling any AI initiative.
The New Measurement: Winning the Answer Battle
For two decades, marketing has been obsessed with a specific set of metrics. Dare we mention the word “funnel”? We’ve optimized for search rankings, tracked clicks on blue links, and celebrated lead form completions. But the customer journey is fundamentally changing. The way people seek information is evolving from simple keyword searches to complex, conversational queries. Answering these queries effectively requires a profound shift in how we measure success.
“We spent 20 years optimizing for search ranks and the next five years are going to be about winning the answer battle.”
Jennifer’s example of searching for a blue office chair is telling. A modern search isn’t just “blue office chair.” It’s a detailed request specifying a star rating, price, location, and assembly preferences. The result is no longer a list of links to click, but a direct answer. In this new paradigm, traditional SEO metrics become less relevant. The goal is no longer just to rank, but to be the source of truth that powers the answer. This gives rise to new KPIs that leaders must start tracking, such as “AI citation rates”—is our content being surfaced and trusted by the LLMs that are increasingly becoming the primary interface for information discovery?
This doesn’t mean SEO is dead overnight. As Jennifer astutely notes, marketers must run parallel strategies for the foreseeable future, managing both traditional search optimization and the new challenge of LLM visibility. It also means we have to rethink the role of our websites. If customers have already done their research via AI-powered search before they even arrive, the website’s purpose shifts from education to transaction. Every visit becomes an opportunity to convert an already-informed buyer, whether that conversion is a purchase, a download, or a deeper form of engagement.
Building a Practical, Composable Future
The dream of a single, all-in-one MarTech platform has been sold for years. Yet for most enterprise organizations, it remains just that—a dream. The reality is a complex ecosystem of specialized tools. Jennifer offers a refreshingly pragmatic take on this, urging leaders to be wary of vendors oversimplifying the challenge.
“The all-in-one dream is just overselling simplicity and underselling complexity and expense. Every time.”
Instead of searching for a silver-bullet platform, the focus should be on building a flexible, composable stack. This means prioritizing solutions that are LLM-agnostic, open, and orchestration-friendly. In a world where the leading AI model can change in a matter of months, being locked into a single proprietary ecosystem is a significant risk. True partnership with technology providers is key. This goes beyond a simple customer-vendor relationship. It requires transparency, a shared understanding of the roadmap, and a commitment from the vendor to “walk the talk” by using their own tools. As leaders, our due diligence should include talking not just to a vendor’s sales team, but to their marketing team, to understand how they are solving the same challenges we face.
The transition to an AI-powered marketing future is not about adopting more tools; it’s about adopting a new operating model. It’s a move away from the relentless churn of content production and toward the strategic orchestration of customer experiences. This shift requires us to rethink our team structures, our systems, our metrics, and our technology partnerships. It demands that we elevate our teams from tactical doers to strategic architects.
The ultimate goal, as Jennifer suggests with her own title, is to become true “Chief Market Officers.” By leveraging AI to handle the mechanical “ing,” we can finally dedicate our full attention to understanding the market, anticipating customer needs, and building the bold, creative strategies that define great brands. This isn’t just about efficiency; it’s about unlocking a higher level of strategic impact and building a more resilient, intelligent, and ultimately more human-centric marketing function for the years to come.
