Aaron Levie, CEO of Box, on Box AI, Enterprise Enthusiasm, and the Evolution of SaaS

**Aaron Levie** (0:00)
The rate of change that we're seeing, and the rate of just exponential improvement that we're seeing from AI models is incredible. And I would assume if we keep that pace up, I think these systems will increasingly be able to perform any kind of general task. Jensen at NVIDIA kind of put it the best, which is, you know, effectively the IT department becomes the HR department of AI. And that just opens up so many new questions about what the future of IT looks like. I think we're entering a new era with systems of intelligence that let us combine data, AI, and underlying enterprise software to go and automate, you know, really anything about our business. There's going to be a tremendous amount of AI startup opportunity, but it will not come from just doing, you know, an AI-first CRM system, because you should anticipate that Salesforce is an AI-first CRM system.

**Nathan Labenz** (0:52)
Hello, and welcome back to The Cognitive Revolution. Today, I'm excited to share my conversation with Aaron Levie, founder and CEO of Box, the Intelligent Content Cloud. Box powers secure collaboration, manages over 100 billion documents, and is now introducing AI-powered workflow automation for more than 100,000 customers globally, including such diverse household names as pharmaceutical giant AstraZeneca, legendary nonprofit Teach for America, investment bank Morgan Stanley, peer-to-peer rental market Airbnb, the $1 trillion chip maker Broadcom, and even the United States Air Force. As you'll hear, Aaron says that leadership at these organizations is now more energized about AI than they've ever been about any other technology in the history of his career, including cloud computing, where Box was an early enterprise SaaS pioneer. While cloud adoption faced initial skepticism and resistance around security and compliance and just needing to do things differently, enterprises today are eagerly exploring use cases for AI. In many cases, Aaron says, perhaps more than is immediately practical. Box is of course racing to meet the moment by building new AI functionality into all aspects of their platform, and they recently launched Box AI to help enterprises get more value from their unstructured data in a secure, controlled way. We discuss several key capabilities, including natural language querying across enterprise content, automated metadata extraction, and their vision for AI agents that can autonomously perform workflows like contract review and routing. Aaron shares a number of technical details on how Box is now layering foundation model capabilities onto their existing foundational features, like their Hubs product, which they originally developed before the current AI moment to allow users to curate canonical, authoritative versions of key documents, and which has proven to be the perfect base on which to build accurate, reliable, retrieval-augmented generation experiences at scale. We also dig into key questions facing enterprises and the software companies that serve them. Including how IT departments will need to evolve from supporting work to actually performing work with AI agents, the transition from per-seat to consumption-based and other pricing models, and whether startups can compete with incumbents who are racing to add AI capabilities. Aaron makes the case that while incumbents will continue to dominate many established markets, there is still massive opportunity for AI native startups to build fundamentally new products that work across platforms and address unmet needs.
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**Aaron Levie** (3:56)
Yeah, good to be here. A lot of stuff going on in AI land right now. How are you doing?

**Nathan Labenz** (4:00)
Never a dull moment, that is for sure. Let's do a quick warm up, and then we'll get into what's going on with AI in the enterprise, and then what you guys are bringing to the enterprise with your latest AI features. For starters, what are you doing with AI in your personal life, and what is your AI world view, particularly as it relates to like, are we going to get AGI soon, or what are you expecting over the next couple of years?

**Aaron Levie** (4:23)
Yeah. Well, I think, hard to obviously say based on the very amorphous definition of AGI, but so I'm like everybody else downstream of whatever Ilya or Sam or Greg are talking about. So I have no better ability to predict where that's going than I think anybody else right now. But all I would say is the rate of change that we're seeing and the rate of just exponential improvement that we're seeing from AI models is incredible. And I would assume if we keep that pace up, I think these systems will increasingly be able to perform any kind of general task that you give it. And with these reasoning models, I think we're seeing incredible results in math and very complex logic and obviously coding. So once you have those basic foundations, if we could continue to improve more and more in the benchmarks, that gives you the building blocks for basically models that can continue to learn on their own and get, you know, as advanced as we need them for basically any task that you'd want to give them. So it seems like within the next few years, we could be getting some form of whatever we would have previously defined AGI as.