Aaron Levie

Now, there are some that we can get through in a couple categories.

But for the most part, I think it's what we will be doing in those roles that will fundamentally shift.

And then ultimately, the amount of output that we get from many of these roles will be the biggest difference.

And so I think there's like two ways to think about AI.

I'm sure there's more, but like one is when you look at work, if you kind of imagine like a mass of work, and then you kind of think about AI taking part of that mass, that's sort of like I think our default instinct because of, you know, kind of what literature says and sci-fi.

Sci-fi doesn't sort of anticipate like dynamic economies.

It usually says, okay, we're working in the factory, robots took the jobs, and now nobody's working anymore.

That's exactly right.

So every sci-fi book ever written has a lump of labor fallacy built into it.

I think there's a different way to think about AI, which is imagine work is actually on a timeline.

If you kind of zoomed out over a 200-year period, let's say back 100 years, forward 100 years,

And you just sort of look at progress in society.

All we're really doing in work is sort of moving through some progress in society, right?

We're trying to like cure cancer faster.

We're trying to, you know, give people better transportation so they can get places.

We're trying to entertain people in new ways.

My view is AI is an accelerant to the timeline as opposed to a reduction of the kind of mass of work.

And so if you start to think about it more as an acceleration on the timeline, then it gives you a little bit of some instruction of then what to go focus on with AI, which is use AI to move faster as an organization.

If as a byproduct of that, you save money, fantastic.

Or if you can now do things that are now cheaper because you're moving faster, also fantastic.