AI’s brilliance isn’t imagination, it’s pattern mastery. The entire promise of Machine Learning is built on recognizing patterns and removing noise. It studies repetition, discards the outliers, and learns from what most people do most often. That’s not a flaw, it’s the point.
Every output, whether a headline, image, line of code, or strategy, is a reflection of what’s been done before. AI doesn’t invent; it averages. It finds the safest, most common path between your intent and the collective past, bringing everything closer to the middle.
That balance is its beauty and its risk.
The Paradox of Progress
AI gives us a way to instantly upskill in areas where we lack experience. A designer can write better emails. A strategist can generate visual mockups. A marketer can prototype a data model. In that sense, it’s a universal equalizer: an instant average that lifts everyone to a shared baseline of competence.
But what happens when we apply the same tool to areas where we already stand out? Where our instincts, taste, or perspective differ from the pack?
That’s when AI starts sanding down the edges that make us distinct.
If you let it, AI will take your most original angle and rewrite it into the statistically “right” one. The safe one. The common one. And in doing so, it quietly kills the spark that made your thinking yours.
The Autotune Effect
Listen to a pop song from before the 2000s and compare it to a contemporary one, and you’ll hear the same thing that’s happening in AI right now.
Autotune made everyone sound pitch-perfect, but it also made every voice start to sound the same. The imperfections, the small cracks, breaths, textures, and quirks that made each voice unique got scrubbed out. And with them went the individuality that made artists unmistakable.
AI writing works the same way.
Ask it to write a thought piece on “the future of marketing,” and it will give you something that sounds flawless: polished, professional, beautifully structured, and utterly hollow.
You’ll read it and think, this is good, but you’ll feel nothing. Because there’s nothing inside it.
It’s like music that hits every note, yet still leaves you cold.
Why This Matters for Leaders
In business, difference is the currency of attention. You don’t get rewarded for echoing what’s already known; you win by thinking outside the box.
AI can help you accelerate execution. It can summarize, visualize, and prototype faster than your team ever could. But it cannot create the deviation from the mean that defines true thought leadership or creative breakthrough. That’s still a human act.
The risk is subtle but real: if your people rely too heavily on AI in the spaces where originality matters, your brand voice, your strategic POV, your culture, you’ll end up with output that’s technically brilliant and emotionally invisible.
What Great AI Use Actually Looks Like
The smart play isn’t to reject AI’s averaging; it’s to use it intentionally.
Use it to:
- Get to good faster. Let AI surface the median so your experts can push past it.
- Spot patterns at scale. Have it analyze hundreds of inputs, then let humans identify the outliers worth amplifying.
- Automate the repetitive. Give it the dull, routine, low-judgment work so your people can focus on what actually moves the business forward.
- Polish, not create. Think of AI as a post-production tool, not a songwriter.
AI’s strength is convergence. Ours is divergence. Together, they can be extraordinary if we remember which is which.
The Takeaway
AI is the art of averaging: the science of finding what’s most common and amplifying it.
But leadership, creativity, and brand-building live in the opposite direction: in the courage to stand apart from the common.
— Yas Dalkilic
Head of AI, RAB2B