The Brand Risk CMOs Aren’t Seeing in Favour of Optimization
Brand Clarity: Understanding the difference between brand and marketing is crucial for effective strategy in AI-driven environments.
AI Limitations: AI excels at optimization tasks, but lacks the judgment needed for building trust and authenticity.
Data Integrity: Clean, unified data and organizational alignment are essential for successful marketing in an AI context.
Agility Importance: Marketers must adapt to change and embrace new skills to remain relevant in an evolving landscape.
Substance Over Shortcuts: Investing in genuine content and strong brand foundations is critical for long-term success over quick fixes.
You might be surprised to hear that the future of marketing won’t be won by better tools. But there's merit in this line of thinking. Instead, stronger judgment, cleaner data, and brands that sound unmistakably human will be the winners in the age of AI. In my conversation, with Paula Mantle, VP of Marketing at Branch, she shares her take on where AI is delivering value, and where it continues to falls short.
Mantle didn't come to enterprise B2B marketing through the typical route. Having spent a decade in the wine industry before making the pivot to tech, she will be the first to credit her unusual background in why she thinks about brand the way she does.
"Every new year, there is a new vintage. The wine is different. You have to learn about it all over again," she says. "That's how the world of marketing feels today so every month, every year, we're going to see something different."
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As VP of Marketing at Branch, the mobile measurement and linking platform, Mantle leads a global B2B marketing organization. They serve a remarkably wide range of customers including developers building their first app, to CMOs at Fortune 50 companies. Their audience spans self-serve, enterprise, and everything in between, shaping how she thinks about what AI can and can't do for marketing organizations.
Here’s her honest and sharp take.
Brand And Marketing Are Not The Same Thing
One of Mantle's most useful frameworks is the distinction between brand and marketing. A lot of AI conversations call out how brand and marketing aren't interchangeable, for good reason.
Marketing is how you translate demand into customers. Brand is how you introduce yourself to the world—it’s the layer above where you create awareness of a problem.
"Brand is that overarching halo that makes people know and like you in a way that is much more human than marketing, which is how do we capture that demand?" Mantle explains.
The reason this matters is that AI is very good at one aspect and genuinely limited at the other. Optimization, pattern detection, bidding automation, multivariate testing are all marketing problems AI is well-suited to handle. But brand? Trust, credibility, authenticity? These require something AI can't simulate.
AI is best for optimization problems, not judgment problems. In the gray areas, where trust and credibility are built — human judgment and accountability will always be critical.
As more of the analytical side of marketing gets absorbed by AI tooling, Mantle sees this as a signal, and not a threat.
She highlights how "the world of brand becomes so much more important because it's the thing that you have to rely on to build that trust and authenticity in a way that it was never quite so important before."
Brand and marketing are intrinsically linked, but the difference between them is wholly different.
The LLM Writing Trap
If there's one place Mantle pushes back, it's on using large language models for content creation. She shares her reasoning, noting how,
Initially, LLMs seemed like a great tool for writing, but they are designed to predict the next word based on existing patterns, not to form a point of view or take a creative risk.
The challenge for marketers, warrants attention, because when “this results in AI writing all sounding the same, it becomes the antithesis of what strong brands and credible thought leadership require."
She draws a parallel to candy, referring to LLMs as candy, in that they offer reward for minimal input, as the output has no substance. So when an entire industry uses the same tool to produce content at scale, the output converges toward a kind of uniform, pattern-matched noise.
The takeaway here is the key things that makes a brand memorable like distinctive voice, and genuine perspective are what LLMs are structurally incapable of generating
In her view, you need to provide these for your audience to derive value from your content.
Individual narratives, first-party data, information that you can't even get from an LLM, and then written in a way that sounds human.
The writers who were genuinely good before AI came along, she argues, will continue to be genuinely good. The difference now is that the contrast more obvious.
The Measurement Reckoning Nobody Asked For
Mantle is direct about where she thinks marketing leaders are falling short. She shares how they're still looking at their channels in silos, which leads to huge challenges. And, AI can't fix a problem that bleeds into all areas of brand presence.
At Branch, this played out in a specific way, where Mantle notes, how "we have customers who sign up as self-serve, despite the fact they’re not even really direct marketing to them."
On top of this, her team demonstrates large ABM plays towards enterprises where the team has compiled a ton of data on contacts. Lastly they have people who they’re not entirely sure how they arrived, but become customers almost in spite of marketing efforts.
When marketing channels are viewed in silos, teams end up mistaking activity for impact. As discovery, conversion, and engagement span more surfaces and become less trackable, we need systems that connect entire journeys rather than point solutions.
Her team understands that to make sense of the many routes a prospect travels to become a customer requires unified data. The solution is not better dashboards sitting on top of fragmented pipelines.
It may sound like a given, but her advice is to fix the broken data channels first, sharing how "AI doesn't fix broken data. Taking three steps backwards to ensure your data and definitions are clean before you take that first step forward will only accelerate your ability to be successful."
Data cleanliness and governance is more important than whatever tool you're evaluating. And it requires the kind of organizational alignment that Mantle refers to as shared focus and data ownership.
"Without alignment on goals and putting in the work to address foundational data access, even strong tools fall short. Building a common understanding across teams mattered far more than adding new technology."
The Marketing Playbook No Longer Applies
Mantle isn't pessimistic about what's ahead. In fact, she's genuinely excited about learning. But she's also deeply aware that the marketers who'll struggle most are the ones holding on too tightly to what used to work.
She credits her depth of experience and an awareness of what still works in an AI-first environment. However, she urges how it's not the technical aspects that will retain brand longevity.
The things that still work are your creativity, your humanity, your ability to marry the left and right brain together. Those things will always be critical.
What's changed is the relative value of those skills. "Today, the most valuable thing is our ability to withstand change and our ability to keep up with change."
Mantle describes attending a panel of well-established CMOs with experience at large companies, and strong track record, who were refreshingly candid about feeling unmoored.
She shares how "They were all like, 'I don't know, our jobs might be obsolete.' Everybody is just trying to figure it out. And what enables the people who are going to be successful is their ability to be flexible and to understand that the playbook doesn't work anymore."
There was something she found genuinely reassuring about that conversation, not demoralizing. When even the most experienced people in the room are figuring it out in real time, the playing field levels. Not because experience doesn't matter, but because agility matters more now than it ever has.
"It really levels the playing field," Mantle continues.“If the old playbook is dead, your ability to be a really successful marketer is not dependent on 20 years of experience. It's dependent on your ability to be flexible and to understand the tools at your disposal."
The AI Truth Most CMOs Aren't Saying Out Loud
Underneath the tactical points, covering measurement architecture, data hygiene, brand vs. marketing, Mantle is making a bigger argument. While AI has dramatically expanded what's possible for marketing teams, it's also revealed the gaps that were always there.
There’s a common thread among organizations, regardless of maturity or size. Between misaligned data and siloed reporting, there are gaps that need to be bridged before the next step can take place. None of these problems are new, but they were easier to ignore before a large language model made them visible at scale.
Teams need to be aligned on their approach to data, in order to benefit from the capacity AI offers. And for organizations who do the hard work first, scale is limitless.
To summarize Mantle's assessment, the teams who build a strong data foundation, write from a genuine perspective, and invest in brand as a long-term asset, will shine. Keep human judgment at the center of the decisions that carry reputational risk, as these are the pillars that distinguish your brand.
Sure, shortcuts may be tempting. But Mantle's betting on substance—and so should you.
What’s Next?
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