Lately, AI has started to resemble a duck on water. On the surface, it looks smooth, elegant, effortless. Underneath, there is frantic motion. Somewhere below, a lot of humans are paddling furiously so the whole thing can keep moving and still look effortless.
I keep seeing some version of the same AI success story: the founder or CEO with the four-hour workweek, who now has time to be with family, take a week's vacation every month, study ancient philosophy, casually pick up Italian, get healthier, think bigger. And some of that does seem true. There appears to be no shortage of C-suite travel, speaking, and beautifully packaged ideas about what all this is unlocking.
What seems less true, at least for now, is that this is a shared experience across the enterprise.
Beneath the C-suite, a different reality is taking shape. Teams are prompting, reviewing, checking, refining, and stitching outputs together to get from impressive to actually usable. And that work is increasingly falling to a new kind of employee: people with real subject matter expertise and real AI fluency. They know the domain well enough to spot what is wrong, and the tools well enough to push the output closer to right.
Which means a surprising amount of what looks like AI fluency is still human improvisation in nicer packaging.
None of that makes this moment any less exciting. Quite the opposite. The value is so real that people are willing to work through the mess. I have seen a version of this before. In the early digital music era, plenty of people underestimated how much effort ordinary consumers would put in if the payoff felt big enough. They assumed people were too lazy to rip CDs, upload songs, organize libraries, and change their behavior at scale. They were wrong. People worked very hard to enter a new world once they believed the return was worth it.
AI feels similar. The payoff is big enough that people are willing to work through the friction. The difference is that, for now, the friction and the upside are not yet being experienced equally.
At the same time, a new, highly valuable class of enterprise employee is emerging in real time: people who combine subject matter expertise with AI fluency and know how to turn promising output into something the business can actually use. Much of the real value seems to be getting created there, beneath the cleaner story on top. Right now, the AI story still glides a little too smoothly over the humans paddling underneath it.