Why AI Is Creating a Massive Opportunity for Agencies
I recently sat down with Scott Brinker, a leading voice in marketing technology, to discuss how AI is changing opportunities for agencies. Brinker has spent over two decades in marketing technology, leading strategy at HubSpot, founding a SaaS company, advising startups, and publishing chiefmartec for 80,000+ industry leaders. He’s best known for creating the Marketing Technology Landscape annual report. He’s seen every major wave of change in how marketing gets done. That’s what made his perspective on AI stand out. While much of the conversation has focused on disruption and replacement, Brinker sees something else emerging — something that could drive significant demand for agencies. AI Isn’t Just Disrupting. It’s Overwhelming. One of the first things Brinker pointed to is the speed of change. Unlike past technology shifts that took years, AI is compressing transformation into months or even less. That compression is putting pressure on organizations. Companies are being forced to rethink their technology, customer engagement models, and how work gets done internally. Most aren’t set up to manage that level of change. As Brinker put it, “overwhelming is an understatement.” This shift in behavior is critical: instead of trying to figure everything out internally, many companies are now looking outward for guidance. For agencies, that shifts the role. It’s less about executing predefined work and more about helping clients determine what they should be doing in the first place. The Structural Advantage Agencies Have In Brinker’s view, agencies are uniquely positioned in this environment because of how they accumulate experience. A brand may face a transformation once. An agency does it repeatedly across clients. Each engagement provides lessons that can be reused. He describes this as a form of arbitrage. Companies get one version of the transformation. Agencies get many. In a moment where there is no clear playbook, that repetition becomes valuable. It allows agencies to move faster, avoid common pitfalls, and bring a level of pattern recognition that most internal teams don’t yet have. A Delivery Model Under Pressure Yet, as agencies find themselves in this evolving role, the way they deliver work is also beginning to change. Historically, much of an agency’s value came from execution: the production, coordination, and manual work needed for campaigns. Pricing often relied on time and resources. AI is starting to absorb a meaningful portion of that execution layer. As that happens, the traditional time-and-materials model becomes harder to defend. Not because the work itself is less valuable, but because the inputs have changed. “The time and materials basis of this has become irrelevant,” Brinker said. What clients still want is the outcome. Strategy, creativity, and orchestration remain central, but the way those are packaged and priced is shifting toward impact rather than effort. Why This Isn’t a Simple Race to the Bottom One concern that comes up frequently in conversations about AI is commoditization. If the tools are widely accessible, does everything become interchangeable? Brinker’s perspective is more nuanced. While AI may standardize parts of execution, companies aren’t hiring agencies for sameness. They’re hiring them to differentiate. That puts more weight on imagination, judgment, and the ability to translate ideas into something that actually works within a business. Not all strategy is equal. As AI improves, some structured analysis is easy to replicate. The defensible work is original thinking, clear positioning, and tying ideas to real-world needs. A Shift Beneath the Surface: From Applications to Infrastructure Another change Brinker highlighted is happening at the technology level. For years, marketing has been built around packaged applications—tools with fixed capabilities that companies assemble into stacks. That model is evolving as AI makes it easier to build custom workflows, tools, and agents on top of broader platforms. In this environment, technology becomes less about individual applications and more about infrastructure. For agencies, this creates new opportunities. They help design how systems are built, connected, and used, extending work beyond campaigns into internal marketing operations. Multiple Transformations Happening at Once Part of what makes this moment so complex is that it isn’t just one shift. It’s several things happening at once. Brinker pointed to three in particular: the transformation of technology and data infrastructure, the transformation of buyer behavior, and the transformation of how work gets done inside organizations. Each of these would be significant on its own. Together, they create a level of change that most companies struggle to manage internally. That complexity is what’s driving demand—not just for execution, but for guidance. The Gap Between Strategy and Execution Is Shrinking AI is also compressing the distance between strategy and execution. In the past, there was a clear separation between the two. Strategy was developed first, and execution followed over weeks or months. That gap is now shrinking. What once took months can now be built, tested, and iterated in days or even hours. That creates a different operating model, one where thinking and doing are much more closely connected. For agencies, the ability to move fluidly between strategy and execution becomes increasingly important. Why Smaller Agencies May See New Opportunities One of the more interesting implications of this shift is what it means for smaller agencies. Historically, larger agencies benefited from scale: more people, more resources, and broader capabilities. AI begins to level parts of that equation by making advanced capabilities more accessible to smaller teams. That said, the advantage isn’t absolute. While the capability gap may narrow, other factors, such as visibility, reputation, and access to enterprise clients, remain significant. For many smaller agencies, the challenge isn’t whether they can deliver the work, but whether they can consistently get in the room to compete for it. The Real Challenge: Managing Change Despite all of these opportunities, most organizations are still behind. Not because the technology isn’t available, but because adapting to it is difficult. Even companies making decisions in response to AI often haven’t fully figured out how they will operate differently as a result. That points to a broader issue. The challenge isn’t just adopting AI. It’s managing
Funding Signals – Activity Through April 28, 2026
Highlights Reliable Robotics raised $160M (Series D) led by Nimble Partners Reliable Robotics develops autonomous aircraft systems for commercial and defense aviation. The funding will accelerate deployment and scale production of its Reliable Autonomy System. That matters because the company cites more than 200 system commitments, a U.S. Air Force contract, and continued FAA certification progress. Agency lens: Commercial deployment, hiring, and production expansio… Get Unlimited NextBigWin Access Subscribe to become a NextBigWin Pro member and get access to all our exclusive content. Turn access and intelligence into your next big client win. Already a member? Login Subscribe to NextBigWin Pro
