AI Didn’t Break Your Marketing — Your Decision Model Was Already Broken with Colleen Goepfert
AI Adoption: AI tools increase activity but often do not lead to improved business outcomes, highlighting operational issues.
Human Factor: Leaders underestimate the human element necessary for effective AI implementation, leading to fear and resistance.
Decision Literacy: A shared understanding of priorities and risks is crucial; organizations often lack this crucial capability.
Workflow Redesign: Rethinking foundational workflows, not just tools, is essential for successful AI integration and alignment.
Governance Need: Effective AI governance focuses on clarifying decision-making structures as organizations evolve beyond experimentation.
There's a pattern Colleen Goepfert has seen play out in organization after organization. A leadership team decides to adopt AI. Volume goes up and velocity increases. And then, quietly, conversions start to drop. Fingers point at the technology. But when Goepfert comes in to decode what's actually happening, the answer is almost never the tool.
AI is really amplifying weak decision models. It is moving faster than orgs are actually able to make decisions, which is exposing the misalignment.
Goepfert is an Executive Strategic Advisor, and go-to-market leader with over 15 years of experience guiding B2B technology companies through complex transformations. She is also the host of the Build Without Chaos Podcast, connecting with marketing leaders, founders, and executives building in complex or high-stakes categories so she’s well equipped to speak about where getting it wrong can do real damage.
Her diagnosis of the current AI moment is part mirror, part warning. And all in, the tools are fine. The operating models underneath them often aren't.
Want more from The CMO?
Sign up for a free membership to complete reading this article:
Have an account? Log In
From Experimentation to Operating Layer
For most marketing organizations, AI adoption has followed a familiar arc where someone champions a pilot, teams are encouraged to "try AI," and activity metrics climb while business outcomes stay flat. Goepfert has spent the last year helping clients break that pattern by treating AI as an infrastructure question rather than a feature add.
The biggest change has been shifting AI from an experimentation layer to an operating layer. Instead of asking teams to ‘try AI,’ we redesigned how research, segmentation, and performance analysis are done so AI accelerates decision-making upstream.
The result, she says, has been faster cycle times and fewer reactive campaign decisions. But the shift required something most organizations underestimate: a willingness to examine how work actually gets approved, reviewed, and decided before touching a single tool.
"The real work is not designing the tool, it's redesigning how marketing works and gets approved," she explains. "Workflow design matters more than the actual tool."
Where AI Still Falls Short
Goepfert is realistic about what AI offers teams. It generates options efficiently. It surfaces patterns and signals faster than any human team. But it consistently underperforms in one critical area and this is in resolving trade-offs.
AI has consistently underperformed when organizations expect it to replace judgment instead of support it. Teams that skipped operating model changes and tried to layer AI on top of broken workflows saw minimal impact. The gap was not tooling — it was decision clarity.
This difference between generating options and choosing among them sits at the center of Goepfert’s advisory work. She points to a concrete example where a client team used AI to scale ad copy and content, only to watch conversion rates fall as AI sped up a misalignment that had existed long before the tool arrived.
"One thing I was talking to these leaders about is the issue was misalignment on the definition of what the qualified lead was," she recalls. "It's AI speeding up these misalignment conversations that have been overlooked."
Once the team aligned on that definition, pipeline increased by 20%. AI can help you shout into the void, but if you’re looking to connect with real live humans, you need to be rooted in your thought process to deliver clarity.
The Human Layer Leaders Are Underestimating
One of the most consistent observations Goepfert shares with clients is that tool adoption is easier than operating change. Couple this with how leaders routinely underestimate the human layer required for AI to actually work, and you can understand the problem.
AI is reshaping identity inside of marketing teams. The leaders who navigate this well frame it as a drafting partner or an editor, not a replacement. And that helps to really preserve creativity and workflow and morale inside of a team.
Framing AI as collaborator rather than substitute also determines whether teams feel safe enough to experiment, fail, and iterate. This theme keeps coming up in conversation. In the absence of certainty, fear becomes the dominant force. Whether it's fear of redundancy, irrelevance, or or losing the skills that made someone valuable in the first place.
"Right now there's a fear around people working with AI tools thinking, if this does too well, will it replace me?" she notes. "And I think we need to remove that and start really understanding the function that AI has."
Her answer is governance and not in a bureaucratic sense, but as a shared understanding of who decides what, at what altitude, and with which inputs.
Leaders are expecting transformation without governance,” she says. “AI generates options for you. But it’s weak at resolving trade-offs. And leaders still need to know what to choose.
The Capability Gap No One Is Talking About
If there is one concept anchoring Goepfert's perspective, it is decision literacy. There should be a shared organizational language around priorities, risk, and acceptable trade-offs. In her experience, this capability gap matters more than any technology shortfall. She notes that, "teams struggle not because they lack AI skills, but because they lack shared language around priorities, risk, and acceptable tradeoffs."
You can have multiple departments battle on what acceptable risk looks like. Front-line teams become frustrated when they’re not being heard, and when escalations go nowhere, leadership lacks direction and everything forges down a dangerous path. Goepfert has walked into organizations where every level was experiencing the same friction but no one had named it.
"I walked in and talked to the people on the front lines and they all told me the same thing," she says. "They escalate what they're seeing and it never goes anywhere." When she surfaced the same dynamic to leadership, they were misaligned among themselves on how to move forward.
This is all too common, and honestly so is the fix. Goepfert suggests a simple exercise where every week, your team reviews priorities, even if it feels redundant.
"It creates a really calm organization," she says, "and it makes everyone understand what their role is and how they're contributing to the success of the company."
What Leaders Need To Redesign First
When asked which marketing system or workflow most leaders should be actively rethinking, Goepfert's answer is pointed. And, (surprise!) it's not the content calendar, the attribution model, or the tech stack. Instead, she highlights the foundational work.
Leaders should redesign how marketing decisions get made, not just how work gets executed. AI forces a rethink of who decides what, at what altitude, and with which inputs. Without that clarity, AI only speeds up existing confusion.
This is the core thesis of Build Without Chaos, and it extends beyond marketing into the broader operating model of any fast-moving organization. The podcast exists, she explains, because high-growth environments have a particular tendency to mistake urgency for strategy, and AI is now accelerating that mistake at unprecedented speed.
"AI cannot solve alignment," she says plainly. "It cannot solve people aligning around company priorities. So therefore, we're always going to need people in companies. Alignment doesn't go away."
The Groundwork Before the AI Pilot
Asked what she wishes she had understood before launching her first AI pilot, Goepfert's answer is to the point.
AI pilots fail quietly when no one owns the outcome. Without a clear decision owner and success definition, pilots produce activity instead of impact.
It is the kind of lesson that only becomes visible in retrospect, and that most organizations are still learning in real time. For Goepfert, the signal that an organization is ready to move past experimentation is not the sophistication of its tools, but in the clarity of its decision-making structures.
"The next phase of where I think AI is going to go is less about adoption and experimenting and more about governance and prioritization," she says. "We can start to understand what we prioritize and what's best for our company and for pipeline growth."
What’s Next?
Join us at The CMO Club to stay on top of trends and get the latest tips, resources, and guides straight to your inbox.
