Box CEO Aaron Levie on the AI Liability Paradox and the Future of Work

**Aaron Levie** (0:00)
Can we find a way to actually tell the optimistic story of AI, which is, yes, in some areas of the organization, we're going to slow down headcount growth. In other areas of the organization, maybe there'll be fewer people at the end of this. But in other areas, we're actually going to be growing, and we're going to be reinvesting and reallocating dollars.

**Alan Murray** (0:16)
The WSJ Leadership Institute Presents Leaders. I'm Alan Murray. For My Money, Box co-founder and CEO Aaron Levie is one of the smartest and most articulate leaders in Silicon Valley, particularly when it comes to enterprise technology. He's been at the center of every major revolution in how the world's largest companies manage data over the last two decades. That's cloud, mobile, AI. Now he says we're entering something even bigger.
Not AI as a tool, AI as your agent. He calls it the agentic era. And in his telling, it is very big.
So how will that agentic era change the way we work and live? Here's Aaron Levie after this short break.

**Jason Garzatis** (1:02)
I think the potential of agentic is to rethink how work gets done overall. It challenges all sorts of traditional orthodoxies around how organizations execute the work at hand.

**SPEAKER_4** (1:13)
That's Jason Garzatis, CEO of Deloitte US, talking about the transformational potential of agentic AI. Join him later to learn why agents are a game changer for businesses across industries.

**Alan Murray** (1:26)
I want to talk about agents, because you have very loudly and prominently declared that we are entering the agentic era.

**Aaron Levie** (1:36)
Yeah. I feel like that's a well-understood theme at this point in this. Well, there's a lot to talk about it.

**Alan Murray** (1:42)
But eras are a big thing. I mean, paleolithic, neolithic, iron age. Why do agents deserve their own era?
Yeah.

**Aaron Levie** (1:51)
I mean, it's, you know, I think we'll figure out if in time it's at that level of paleolithic.
But I mean, I think it's pretty obvious that there's a massive transformation in the world of work.
And basically, it's the shift of software has always been deterministic. So, you know, it kind of does exactly what you want to do every single time, and that has a lot of great properties. But it also has a lot of limitations. It can't adapt to new information. It can't adapt to any amount of unstructured data and input that it receives. It has to be highly, highly structured. And so we were able to automate 5% of a company's operations. We can automate the ERP operation. We can automate managing workflows around our CRM or IT workflows. But actually, most of work is this messy, unstructured, human, collaborative, lots of different data types coming in, and we've never been able to automate any of that. And so if you just did a heat map of all the work that happens in the world, the vast, vast, vast majority, probably like 90, 95 percent of the work that we do is inherently unstructured. And for the first time ever, AI allows us to bring automation to that part of the work. And so it just stands to reason that obviously that is the biggest shift that we'll ever see in kind of corporate work.

**Alan Murray** (3:14)
Bigger than previous ways of automation.

**Aaron Levie** (3:16)
Easily, by orders of magnitude.
And so it sort of certainly deserves its own way of kind of thinking about what that future of the information age is going to look like. It's actually interesting, we probably called the information age too early in retrospect. We thought computers would bring about the information age, and it kind of did, but it meant that people were always the dependency for actually working with the information. And now with agents, agents can work 24-7 in parallel on any amount of data. So that really starts to usher in the full potential of the information age.

**Alan Murray** (3:50)
Can you do a quick definition? Nicola Moreau was on the stage earlier. She said 95 percent of what people say is agents right now.

**Aaron Levie** (3:57)
Yeah.

**Alan Murray** (3:57)
Is it agents? Would you agree with that?

**Aaron Levie** (4:00)
Maybe like 92 percent. So I-

**Alan Murray** (4:03)
You guys can fight that one later.

**Aaron Levie** (4:05)
Yeah. I mean, I think there's going to be a lot of that. It's going to be very messy terminology wise, just for a variety of reasons. And but like, by virtue of me having the microphone right now, I'll make the real definition of agents.
But I think everybody can kind of feel it. Like when you go to a chat bot and you ask a question, you get an answer back, it's sort of, okay, it's kind of like an assistant chat bot thing. I think we are collectively as an industry agreeing that an agent is probably something that can do a bit more than that. And so the general architecture that you should expect from any kind of agentic system is, it's still an LLM by and large, behind the scenes. But that LLM or AI model has access to a set of tools.