It feels like a strange moment for generative AI in marketing.
On one side, I hear the chorus: “If we’re not using AI to generate everything (blogs, decks, ads, videos), we’re already behind.”
According to that narrative, marketing jobs are becoming obsolete.
On the other side, I hear creative defiance or even outright refusal: “I’ll only use AI to summarize what I’ve already written.” Or, “Sure, I use it for first drafts — but never final work.”
Some corporate leaders ban AI use, waiting for copyright or IP safety solutions (and teams inevitably find workarounds to explore on their own).
Some marketers argue with the CSI: Em Dash Unit, chasing down copy crimes, one suspiciously punctuated sentence at a time. Others fork over $997 for a prompt-template PDF that promises to ensure that AI will only write the good stuff if you assign it a role.
Meanwhile, virtue signalers hand out artisanal “No AI used” badges for handcrafted, grass-fed, non-GMO social media posts.
Across all sides, people seem hyper-focused on one thing: creative throughput.
Whether they embrace or resist AI, everyone treats it as a production tool to help teams go faster, do more, and squeeze more output from fewer inputs.
But what if the real opportunity isn’t about acceleration at all?
What if generative AI is the first innovation (in a long time) that gives you time to slow down? To make room for:
Deeper thought
More curiosity
Better questions
Watch the video or keep reading to work through that question.
Rethink the intern metaphor
You’ve probably heard this claim: “AI is like having an intern.”
It’s a comforting metaphor that makes technology feel manageable. You get to hand off the tedious stuff (summarizing research, repurposing webinars, outlining presentation decks) so that you can get back to the “real” creative work.
And it’s precisely how many generative AI tools are marketed today. The pitch is simple:
Dump your data into our enterprise-grade AI blender, and — voilà — you get hyper-personalized content, frictionless workflows, real-time insights, and surprise revenue. No need to lift a finger!
In short, you picture a relentlessly productive intern who never sleeps, never pushes back, and quietly renders your whole marketing team unnecessary with a smile.
But there’s a tension in that narrative.
People say, “Let AI do the work.” Yet they worry that AI will take jobs and replace whole marketing teams or that it will take over the creative work while marketers are left with managing prompts and optimizing processes.
People say they don’t believe it could happen. And then, in the next breath, they ask, “But what if it does?”
So, we compromise. We experiment. We delegate to AI at the edges. Not because that’s where it’s best, but because that’s the safest way to feel like we’re keeping up with the need for speed.
And that’s what makes me wonder if we’re missing the point.
Droids don’t judge, people do
If you know your Star Wars lore, you’ll remember that droids are often treated with suspicion.
In Attack of the Clones, Obi-Wan Kenobi sits in a greasy-spoon diner with his friend Dexter Jettster, who explains why droids can’t be fully trusted: “They have no wisdom.”
Obi-Wan agrees: “If droids could think, there’d be none of us here.”
The subtext is clear: Droids have data but not discernment. They can execute, but they can’t judge. They can act, but they can’t choose.
That sounds a lot like the conversation we’re having about AI today.
Yes, AI can store knowledge and process patterns. But it can’t tell us why something matters or what to do when the data says one thing and the story says another.
But maybe that’s not a flaw. Maybe that’s a feature — because that’s the boundary where human judgment begins.
AI at the boundary of human creativity
Maybe the real opportunity with AI is neither where we’re most confident nor completely lost. Perhaps it lives at the boundary, where people still do the reasoning and exploring but use AI to help them see things they hadn’t noticed before.
If you think of AI as an intern focused on derivative output, you expect it to provide fast, helpful (but shallow and predictable) work.
If you treat AI as a full-on replacement, it still falls short. It lacks taste, judgment, and wisdom. At best, that thinking leads to the expectation of one mythical person — the so-called "vibe marketer" — wearing an augmented reality headset and orchestrating a swarm of agentic bots.
But what if you don’t think of generative AI as something to help us go faster or do more?
What if it’s the thing that lets you slow down? To pause. To reflect. To shape better questions. To think more deeply about what you’re making — and why.
Maybe this is the innovation that breaks the 20-year quest for more speed.
Maybe the true opportunity is to decelerate with intention.
Shift your AI goals from velocity to depth
Reframing your lens on generative AI changes how you use it and why.
The question isn’t, “What can AI help us execute?” And it’s not, “What can AI do that we can’t?”
It’s: “What might we explore now that we couldn’t see before?”
That’s the boundary. That’s where the strategy shifts from velocity to depth.
A core idea from epistemology, the philosophy of knowledge, is why we know what we know. It’s not only about accuracy but also about justification.
The question “Why do we believe this?” matters most at the boundary of understanding, where confidence is low and uncertainty is high.
Say you’re watching a medical documentary claiming a diet improves brain health. It sounds convincing with all the charts, expert quotes, and a cited study or two. Though you’re not a neurologist, you’ve read enough to ask questions like “Is this correlation or causation?” or “Was this a clinical trial or an observational study?”
That moment of questioning is epistemology in action. You’re not unquestioningly accepting what sounds smart. You’re interrogating what seems plausible.
But epistemology doesn’t stop at the question. It pushes us to evaluate the reasoning, seek context, and understand what evidence would justify belief.
That’s the part the current framing of AI skips over.
When AI surfaces a pattern or suggests a strategy, your job isn’t to take it at face value. It’s to ask, “Could this be right?”
That’s not outsourcing judgment. That’s practicing it. In this model, AI doesn’t think for you. It helps you think more completely.
How to use AI for depth
This approach has immediate implications for how people use AI in marketing and content today.
You could use AI to write ad copy faster. Or, you could ask it to offer five alternative framings (and three might be things you never would’ve considered).
You might ask a generative AI tool to summarize a sales report. Or, you could have it find patterns in lost deals and suggest a new segmentation approach.
You might use AI to churn out subject lines. Or you could ask it to analyze tone, pacing, and emotional resonance across your highest-performing subject lines.
You might use AI to draft an article. Or, as I did for this post, you could use it to challenge what you wrote and why. (Spoiler: This post took me twice as long to write.)
In each case, the AI output is the least interesting part. The value lies in the spark that helps you reach beyond what you already know.
In the twist we didn’t see coming, you can use AI to prompt yourself. The machine hands you the output. You decide what to make of it (and with it).
More humans needed
Let’s be clear: Through this lens of slowing down, we humans don’t fade back. We become more central.
Companies wouldn’t need fewer people. They’d need more. Not to generate more content, but to bring more perspectives, more reflection, and more context.
No vibe marketers. No one-person AI command centers.
Brands would need bigger, more diverse teams with judgment, taste, and shared wisdom — built for dialogue, not just throughput.
And it may already be happening.
A recent study found that AI saved companies, on average, only 2.8% of work time — about an hour per week. In some cases, workloads even increased as teams spent more time refining, validating, and reasoning through what AI produced.
Some media covering this research positioned it as a failure to deliver on AI’s promise. But I see something else.
That’s not failure. That’s friction. Maybe companies are finally getting it right. They’re not automating people’s thinking. They’re investing in it.
So, what is AI if not an intern?
If we let go of the intern metaphor (and the marketing replacement nightmare), what’s left?
Maybe AI is your analyst. Your fog light. Your tilted mirror. Maybe it’s the second brain in the room — unbound by your assumptions — but relying on your judgment to make meaning.
Or maybe it’s just a tool built not to automate creativity but to provoke it. A tool that helps marketers step out of the default drive for speed and gives them a reason to finally slow down.
To think more carefully. To ask better questions. To deepen the work itself.
Maybe that’s the real role of AI.
That feels like an opportunity.
Excuse me while I spend a bit more time figuring out why I believe this.
It’s your story. Tell it well.
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