What 3 Superhuman Marketing Leaders Really Think About AI
When it comes to the promise of AI productivity, it's easy to feel two things at once: excitement about these tools’ potential…and a sense that we’re waiting for the other shoe to drop.
With AI's help, people can certainly do more and create more. But for marketing teams, the other shoe hasn’t just dropped. It fell long ago. AI has created more work, not less. There are more outputs to review, more tools to switch between, and more async threads than any one person can reasonably track.
The gap between what AI was supposed to do and what it's actually doing day-to-day is real, and it's not being talked about enough. We asked three of Superhuman's marketing leaders to weigh in on how their teams are using AI to advance their work, not just create more content for review.
How AI Should Be Working for Your Creative Team
Most mornings, Leah Pincsak, VP of Brand and Creative, wakes up and feels behind. By 9 a.m., she's sifting through Slack messages, emails, Coda docs, and Figma files. And that doesn't even include the async review threads, where a 20-comment chain could likely be solved in a 5-minute live conversation. AI has only made this daily routine more intense.
Leah's morning ritual reflects a shared experience: 73% of marketers say AI creates extra work to review or fix, and the actual number is likely higher. Because most AI tools skip straight to an output, every artifact requires some sort of human intervention before it's usable. When teams have to do multiple rounds of brand voice reviews or creative tweaks, their workload quickly doubles.
Leah also finds that AI outputs skip what she describes fondly as "the messy middle"—the dialogue, the iteration, and the moments when you change your mind and have to figure out why. That's where creative judgment gets formed and where the joy of the creative process lives. Sure, what AI produces may be considered "good enough," but that is the enemy of opinionated. It lacks the one thing that makes creative work land: a point of view.
For her team, Leah wants AI that absorbs the coordination overhead, the logistics, and the hundreds of small tasks that fill up a day and oversaturate their brains. Creative thinking requires energy, and she wants her team to spend time and brainpower on the work only they can do.
The Truth Behind the AI Jargon
Dolleen Cross, Director of Communications, has spent two years watching a new vernacular take shape: AI fatigue, AI brain fry, AI FOMO, AI anxiety, AI slop. These terms are signals, and they all point to the same root cause: AI is adding work before it removes it.
3 dynamics drive this compounding sense of friction:
- New tools are arriving at a rate that people cannot keep up with. 65% of marketers say their organization introduces new tools faster than they can learn them.
- As Leah's team experienced, when AI produces generic or off-brand outputs, the necessary reviews and tweaks that follow have their own cognitive cost.
- Productivity gains from AI don't actually translate into less work. Instead, they're being reinvested into more ambitious work, which keeps the ceiling moving and the exhaustion building.
For teams to genuinely adopt AI and find value in it, the training can't come from formal onboarding or company-wide mandates. Instead, it's peers sharing specific use cases, swapping workflows, and showing each other what works that actually get people to realize the value of these tools.
The products that earn real, lasting adoption fit so naturally into the work that people can't help but want to tell their colleagues about them.
Strong Brands Are Built by People, Not Prompts
From Erin Dame's vantage point, not all AI-generated content is bad, but bad AI-generated content has earned its name. AI slop is content that says a lot and somehow also says nothing at all. It could come from any brand, in any industry, on any given Tuesday. In her experience, that's almost always a prompt problem.
AI holds a megaphone up to whatever you hand it, meaning no amount of prompt finessing can fix a strategy that was never clear in the first place. When there's no strategic scaffolding, brands end up sounding like everyone else.
When Erin's team works with AI, they start by establishing a contextual and strategic foundation. They drop in outlines, stream-of-consciousness notes, and brainstorm fragments—everything messy, nothing polished—and use AI to shape and organize them into a concrete draft. The real work happens when they react to the output: clarifying points, pressure-testing arguments, and asking whether the strategy holds for a specific audience.
That process helps preserve the mental bandwidth needed to answer harder questions, like how a campaign fits into a broader ecosystem of marketing activities or whether the stories being told are actually consistent across channels and over time. That's the kind of thinking that can only come from people—and it's what makes the tools that earn their place different from the ones that simply add to the pile.
The question she'd ask any brand leader right now: do you know what you want to say? Because if you've done the work to know who you are and what you stand for, then, and only then, can AI multiply it.
