Last week, I returned from the Gartner CMO Symposium in London with loads of new insight and inspiration. AI dominated nearly every conversation, and it is pretty evident that AI is no longer this fun little experiment we are piloting on the side. It is becoming the operating environment for modern marketing.
Across the two days, one statement kept resurfacing:
- Your next customer might not be human.
According to Gartner, 1 in 4 buyers and consumers have already outsourced purchase decision-making to AI, and 60% of buyers have used AI in a recent purchase process. This means that by the time someone reaches your website, much of the decision has already been made.
What stood out in London was not the direction of change or that buying behavior is evolving with AI. It was more the reality of how fast things are moving, the speed of change. As marketers, we are all aware of what is happening, and we are moving and adjusting, but what hit me was that the pace of change is so much faster than our ability to adapt.
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The amplification paradox
The main keynote opened with a clear message:
AI won’t make a mediocre marketing team perform like a great one. It will simply magnify whatever you already are.
If your strategy is reactive, AI will multiply that reactivity. If you are an order-taking function, AI will lock you into deliverables. The promise we have all been selling internally, that AI will help us do more with less, perform better, and move faster, is only true if our foundation is strong enough for AI to amplify.
Right now, according to Gartner, 98% of CMOs are piloting or using AI, and 80% of CEOs are looking to AI to deliver transformative change. However, only 1 in 3 CMOs are seeing the returns they expected. Near-universal adoption. Sky-high expectations from the C-suite. And two-thirds of marketing leaders are still missing the mark.
Why?
Simply because adoption isn’t strategy.
Only 30% of CMOs report mature AI readiness. The rest of us are adding AI on top of existing and sometimes broken processes. The technology isn’t the bottleneck. The organization around it is.
The CMOs pulling ahead are not the ones with the largest tech budgets, they are the ones restructuring how work actually gets done.
Are we building a faster version of the problems we already had, or are we giving AI something worth magnifying?
From Enterprise Operator to Market Shaper
This challenge was looked at in a slightly different way in Kristina LaRocca-Cerrone's session titled Become a Market-Shaper CMO.
She shared some insightful data. 57% of marketing functions fell short of at least one business target last year, as measured by their CEOs and CFOs. But even among those who hit their targets and contributed to growth, fewer than half (45%) exceeded their CEO and CFO's expectations.
Doing the job well is no longer enough.
Most marketing leaders fall under the category that Gartner calls Enterprise Operators. It's characterized by translating corporate strategy into plans, coordinating functions, and delivering exactly what is asked of us. It is necessary work, but in the C-suite, it is the baseline. It doesn't differentiate us.
The ones who consistently exceed expectations are what Gartner calls Market Shapers. The CMOs who belong to this group are business leaders first and marketers second. They anticipate where the market is going and connect unmet customer needs back to what the company can actually deliver. This is where we see payoff. Very effective Market Shapers are 8x more likely to exceed performance expectations.
It is dangerously easy to slip into Operator mode. Most of us were promoted into the C-suite for being excellent at executing what was asked of us, and that is exactly the skill that no longer differentiates us. Becoming a Market Shaper isn't a title change. It is a different way of thinking about what marketing is actually for.
- The CMO job now is 90% chief and 10% marketing.
Your next competitive advantage will be human
If marketing needs to be rebuilt, the harder question is what to rebuild it around.
The clearest answer came from Nicole Greene's session on humans, machines and the marketing org, where she made the case that our next competitive advantage will be human. The risk isn't that AI takes our jobs. The risk is that we automate the wrong half of marketing and lose the part that actually matters.
Gartner cited data showing that 65% of market research analysts' and marketing specialists' work is exposed to AI. The math points toward smaller, leaner execution teams. The real strategy lies in how we double down on the capabilities of the people who remain.
They highlighted five core human traits: judgment, empathy, creativity, trust, and ethics.
AI scales execution. Humans set direction. AI detects patterns. Humans interpret meaning. AI generates content. Humans give it meaning.
The paradox is that the more AI absorbs technical tasks, the more valuable, and more visible, the human work becomes. The skill that will define the next generation of marketing leaders will not be AI fluency. It is knowing which 10% of the work AI should not touch.
The Brand Doom Loop
Rachel Dooley's session: Help! No One Believes My Brand Is Driving Revenue! was very interesting. She stated that 85% of CMOs are confident their brand is driving results, while 84% struggle to quantify its value. She pointed out that we underinvest in measurement and that makes the executives skeptical, then the confidence in the data erodes and finally the budget gets cut. Then the cycle starts again. She called this the Brand Doom Loop.
I can certainly relate to this, however, I’m not sure if it is an underinvestment in measurement, I think it is more the challenge to know what and how to best measure the impact of branding.
Most marketers have upper funnel measures in place, like click, share of voice, branded search volume. Useful signals, but they mostly tell us the brand is being noticed, not how much it has contributed to revenue this quarter. Brand rarely drives revenue on its own. It supports the activities that eventually lead to conversion. However, most attribution models are built for short-term conversion and struggle to capture that broader impact. It credits the last click and misses the brand work that made the click possible. Performance ends up looking more efficient than it is, and brand looks weaker.
Rachel's reframe was that brand measurement has two parts. How we measure, and what we measure. No single method covers every conversation. Geographic tests can prove incremental impact in specific markets. Brand surveys track momentum and future demand. Conjoint analysis isolates what customers actually value. Marketing mix modeling reads brand's contribution across the full system. The work is to match the method, and the story, to the question actually being asked and the person asking it.
As Rachel put it, CFOs want a clear return on marketing investment for brand spend. Awareness data is not the answer to that question. And until we fix that, we stay in the loop.
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The window is closing
We are not behind on understanding what is changing, we are behind on how fast we are able to respond to it. The pace is the problem.
The themes from London point to the same conclusion. AI does not lift weak foundations, it exposes them. Operators get out-performed by Shapers. The capabilities that will differentiate us are the human ones - judgment, empathy, creativity, trust.
The leaders who will define the next two years are not the ones running faster inside the current system. They are the ones stepping out of it long enough to redesign it, and disciplined enough to rebuild it while still in motion.
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