AARON LEVIE: Having done this now for 20 years, starting right at the start of the cloud, seeing the iPhone, seeing the iPad, this is absolutely the fastest I’ve ever seen tech move by at least 5-10X. Every week something is happening that is causing this category to shift in some direction. Something will happen at 10:00 p.m., and there’ll be like a group chat with AI friends. Everybody’s blowing up like, “Oh my God, I can’t believe this just happened,” and then it’ll be an internal Slack with 15 people on the AI team of, “Oh gosh, we have to jump on this,” and it’s just like, “Hope everybody had their family dinner and that’s all behind them, because now we’re back, wired in on what’s happening.”

BOB SAFIAN: That’s Aaron Levie, founder and CEO of Box. I put Aaron on the cover of Fast Company a decade ago to represent how a generation of new leaders were embracing adaptability. I wanted to go back to Aaron now because his cloud storage firm is increasingly an AI firm, putting him at the heart of a new wave of chaotic change. Aaron gives us an insider’s roadmap on where AI is moving for enterprises, why there’s so much buzz about AI agents, and what it means to be an AI-first organization. Aaron isn’t shy about calling things as he sees them, whether that’s mistakes others are making with AI or critiques of both Trump and Biden.

So let’s get to it. I’m Bob Safian, and this is Rapid Response.

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I’m Bob Safian. I’m here with Aaron Levie, CEO of cloud storage and tools platform, Box. Aaron, great to see you. Thanks for being here.

LEVIE: Thanks, Bob. Good to be here.

Embracing the AI revolution

SAFIAN: So I went to your LinkedIn page just earlier, and I scrolled down your posts over the last few months, and it’s like AI, AI, AI, then AI agents, AI agents, AI agents. You are all in, aren’t you?

LEVIE: All in. All in. So when we saw that everybody kind of had their ChatGPT moment, and ours was like, “Wow, all of a sudden, we’re going to be able to use AI on top of all of this unstructured data that we have.” So in Box, it’s contracts, and invoices, and marketing assets, and research data, and so the initial breakthrough use case was, “Okay, we can now talk to our data, we can ask it questions, we can get insights from all this information.”

And then, somewhere about last year, there was this sort of emerging concept of agents, which is, “What if you actually had these AI models think longer, they could use tools, they could go back and double-check and answer, or kind of apply more judgment later in the stream of work?” And so we jumped full on on that, and so we’re kind of all in on AI agents right now.

SAFIAN: Now, I got to ask you, some folks murmur that AI’s business impact isn’t quite living up to the promise yet. The sellers of the picks-and-shovels of AI are making money, but few prospectors have struck gold with AI tools practically for real. Where are we on this effectiveness curve for AI?

LEVIE: Yeah. I would take the other side of that argument, the prospectors are, let’s say, Cursor or Windsurf for these AI products that automatically generate marketing content for you, or Figma, generating design assets and web pages. I think you certainly have the picks-and-shovels, all of the hyperscalers. That’s kind of always going to be the first phase of the rollout, but the prospectors in this analogy of, as the app layer, I think we’re seeing some of the fastest-growing companies in history get built on this AI foundation. As far as every stat I’ve seen, Cursor is the fastest-growing software company in history, at least in an enterprise context, and that is 100% due to having AI agents right next to you while you’re coding that can accelerate your code development.

On the enterprise front, in the customers we talk to, they are doing everything from saying, “Hey, I want to take 100,000 contracts and automatically review them with AI, and extract the most relevant data from those contracts,” or, “I want to take all of my sales presentations that I ever created, and I want new employees to be able to ask them questions so they can get the level of expertise of an existing employee that’s been at a company for a number of years.” And so this is already starting to roll out in large enterprises. The amount of time it takes for these AI products to get incorporated into people’s workflows naturally take some time.

How AI agents are set to disrupt enterprises

SAFIAN: I remember having a conversation with a CEO who, like you, is a tech person, and they were like, “I spent two weeks doing nothing but coding,” and it just blew my mind about what was possible. And I was like, “Well, I’m not a coder. How do I actually feel that?”

LEVIE: Yeah.

SAFIAN: And I think it’s sometimes hard for folks to sort of see that leverage, because that layer isn’t quite here yet.

LEVIE: I think that’s exactly right. GitHub Copilot was introduced about a year or two before ChatGPT. So developers actually had their ChatGPT moment at least 12 to 18 months before everybody had their ChatGPT moment on the consumer side. And so very similarly, Cursor, Windsurf, Replit, these products are now having their AI agent moments, and that is happening a year or a year and a half or two years before then. The general population is going to have their AI agent moment. Now, you can already see the very initial versions of this, so if you take something like Deep Research inside of ChatGPT, or inside of Grok, or inside of Perplexity, or Claude from Anthropic, this is the first agentic use case that I think the kind of regular knowledge worker will run into, which is, “Okay, I don’t just want a very quick answer to a question about some historical event.”

“I really want the AI to go out and research 100 different companies and give me all of the best practices in my particular field for a specific type of topic. I want to get the marketing strategies of the 100 companies in my industry.” So this is sort of deep research, and what’s happening is the AI isn’t just kind of very quickly in three seconds coming up with an answer, where there’s the risk of hallucination, or where it hasn’t had enough time to kind of go across the entire internet and find up-to-date sources for all of the questions. The ChatGPT moment was these very quick answers to moderately complex questions. The deep research moment of this paradigm is much longer answers in terms of the amount of content you get, takes about five or 10 minutes of kind of thinking time for these AI models, and they’re going across the entire up-to-date corpus of the world, which is the internet, to go get the answer.

And so I’m using this almost on a daily basis for every kind of question imaginable in the company. I want to figure out the pricing strategy for everybody’s AI products. And so late at night, I’ll be kind of alone working. There’s not somebody I can just go ping that says, “Hey, can you go do this research for me?,” and 15 minutes later, it’s in my queue, and it has come up with a full research document of every single company in our space, and what they’re all doing for pricing. And that just moves the project that I’m working on one step forward, by days faster than it would’ve been in a kind of non-AI world.

And so I think what will happen is as these types of products become more pervasive, everybody will have versions of that in their daily work, where you’re just going to be sending tasks off to AI agents that are just working on your behalf as you would’ve if everybody had a research assistant that was fully at their disposal for any kind of project work that they wanted.

SAFIAN: I talked with Marc Benioff at Salesforce several months ago about his embrace of AI agents, but the use of his agents hasn’t quite taken off the way he hoped. I know you launched Box AI Studio to help organizations build their own custom AI agents. I’m curious how that’s going.

LEVIE: Yeah. So far, it’s either at or exceeding our expectations on all the use cases that customers are coming up with. So we’re pretty blown away about what we’re starting to see. We’re still very early days to be clear, but the rate of adoption is going fairly exponential, and the imagination that customers now have on this is blowing us away. So you mean uses you didn’t anticipate for the way these agents work?

SAFIAN: Yeah.

LEVIE: Yeah, I’ve rarely been in a customer conversation either one-on-one or in a dinner where I’m not hearing about a new idea that the customer has for Box AI that we did not have on a whiteboard. And what’s exciting, and this is counterintuitive, I think, to a lot of folks outside of AI, you initially sort of see AI in sci-fi and sometimes in news headlines, New York Times or whatever as like, “Okay, it’s going after jobs. It’s going to replace these types of work.” From my anecdotes, I’ve had at least 100 interactions with customers in the first quarter of this year, the vast majority, 80%, I’m guessing, the bulk of the time of AI use case kind of conversation was spent on things that the company didn’t do before AI. So it wasn’t, “Hey, I want to take this type of work, and I want AI to go replace it.”

There’s a type of work that we never get around to in our company. I want AI to go and do that, because finally, it’s affordable for me to deploy AI agents at the kind of work that we could not fund before. It’s opening up people’s imagination to, “Hey, I’m like sitting on 50,000 customer contracts. What if I could have an AI agent go around all those customer contracts, and figure out which customers have the highest propensity to buy this next product from me?” And this is not something that they would have people ever do.

So it’s not replacing anybody’s job. They never said, “Oh, let’s have 50 people go read all the contracts again.” It just never happened. But now, if it only costs them $5,000 for an AI agent to go do that, they would do that all day long. And then guess what?

When they get those insights, they’re probably going to have now more work for the humans in their business to go and do as a result of this, that hopefully if it’s effective, drives more growth in their business, which then causes even more productivity, and then ultimately hiring and growth. And so it’s not kind of everybody’s first instinct, but most of the use cases that we’re hearing about are things where, “Because it is now affordable to deploy AI at a problem, I’m actually expanding the set of things my company can go do, and then the work that we can now execute on.” And that’s not only very, I think, exciting, but I think it’s going to be the default case for most AI adoption in the enterprise.

The ROI of implementing AI into the workplace

SAFIAN: It’s interesting, because in some of the conversations that I have, it feels almost like some of the businesses and leaders, they don’t really know what they’re looking for from AI. And hearing you, it sounds a little bit like you have to think about your mindset on it a little differently to open up and find those things that are most valuable to you.

LEVIE: Yes. Yeah, every business is going to be different because some of the upside is a virtue of your business model. What are the core parts of your business model that, as a result of access to information, can change or be modified or improved? If I am a law firm, I could either reduce my cost because now, AI is going to do more of the, let’s say, paralegal work, or I could expand my service offerings because now, all of a sudden, my team can venture into more domains because they can take their expertise and use AI to augment that. The default assumption is, “Oh, no, it’s going to go after the hours of a law firm,” but once this technology hits an individual business, they can actually decide to expand their customer base.

They can go after, previously, customers that would’ve been unprofitable for them to serve. So these industries are not as static and zero-sum, the software industry. On one hand, everybody says, “Okay, if AI can do coding, then will we hire fewer engineers?” And in general, my argument is that we’ll probably hire as many, if not, more engineers if AI can get really good at coding, because what will happen is the productivity rate of our engineer goes up, which means that we can then ascribe a higher degree of value per engineer in the company.

SAFIAN: So your ROI is even better on each of those positions?

LEVIE: Exactly. Exactly. And take something like sales. If we can make a sales rep able to sell 5% more, because we give them better data, and they can prepare for a customer meeting that much better, or they can understand exactly the best pitch because they have access to all of Box’s data and they can ask it questions, I’m not going to just bank that as 5% more profit, because what will happen is we’re going to internally, in some planning session, we’re going to get greedy, and we’re going to say, “Wait a second, that 5% gain that we just got in sales productivity, what if we reinvested that back into the sales team to grow even faster and get that much more market share?” And so you have an entire economy of companies making those individual decisions of, “Do you bank the profit, or do you use it to go and accelerate growth?”

And what we tend to know from history is that the companies that get too greedy on the profit side, you just end up leaving yourself vulnerable to being outflanked by competitors. So capitalism has a pretty convenient way of almost driving the sort of productivity gains of these types of innovations to get reinvested back into the business.

What it means to be an AI-first organization

SAFIAN: You’ve been talking about running Box in an AI-first way, and encouraging other leaders to do it. Are you like Shopify and Duolingo, who’ve announced that staffers have to justify anything that’s not AI-produced? What does AI-first mean?

LEVIE: Yeah. So for us, AI-first means that we want to use AI as a means of driving an acceleration of the customer outcome, an acceleration of decision-making, an acceleration of building new features. So just think about it as mostly a metric of speed. On one hand, you could think about AI as going after like a massive work, and you could say AI is going to remove some part of that massive work and do it instantly, so the massive work goes down, or think about work as a timeline, and not a mass. All we’re doing is trying to get through each step so that way, we can get to the next step and so on.

SAFIAN: And everything’s faster.

LEVIE: And everything’s faster. So I want to have us use AI to move faster down the timeline, not just purely to reduce the total mass of work that we’re doing. There’s probably one pronounced difference versus, let’s say, the Duolingo memo. There’s some emerging idea, which is sort of you have to prove that AI can’t do this thing for you to get then headcount, and our general instinct is actually the opposite. If you can prove that you can use AI, then that’s actually when you will get headcount, because what we want is we want the dollars of the business to go back into the areas that are the increasing areas of productivity gain, because those areas will then be higher ROI for us over time.

SAFIAN: I worked for a while at a place where our whole job was to create the piles of cash for us to bring over to someone else, and it was a frustrating way to be.

LEVIE: What you don’t want is you don’t want to develop any kind of accidental disincentive for AI adoption. If you make it so when AI can’t do something for you, you get this kind of benefit of more budget — that obviously would create a perverse incentive. You’d actually rather just say, “Okay, we want every org to be AI-first, and the ones that are even more AI-first will be the areas that we probably prioritize with additional resources.”

SAFIAN: I love how Aaron meshes his understanding of AI development with business realities, incentives, investments, how greed can propel both missteps and opportunities. I also love his personal stories about how he uses AI and how specific conversations with clients are shifting his priorities. So what kind of best practices does he offer for keeping up-to-date on AI shifts, and is China really an AI threat or not? We’ll talk about that and more after the break. Stay with us.

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Before the break, Aaron Levie of Box talked about how AI and AI agents are poised to change enterprises. Now, he talks about what it takes to keep up with a constant flood of AI advances, the risks posed by China and by tariffs, and how AI will change our society in the next 12 months. Let’s dive back in.

Keeping up with rapid AI advances

You guys work with everyone with all the models, OpenAI, Google, Amazon. New models, new products come out every day constantly. How do you personally stay caught up?

LEVIE: This part has exceeded my highest expectations of the amount of just dynamism in this space. Our only historical context for this many platforms competing are in these early stages of OS wars, device wars, and so on, and even then, there’s usually only two to three credible players that kind of take the attention of the market. We have somehow ended up in a category where there’s arguably five to six players, all of which you could throw a dart on a dartboard and they will have the leading AI model for some, at least brief kind of period of time, and the leapfrogging is sort of happening at no greater pace than on a monthly basis. So that means that you have every week, something is happening that is causing this category to shift in some direction. You could possibly just say, “You know what? Then, I’m just going to not pay attention because it’s moving so fast.”

We don’t have that benefit because our customers rely on us to know what the heck is going on. So then, you have to do the inverse, which is we are just drinking from the fire hose of constant information coming at us. I mean, we’ll be on at Saturday at 10:00 p.m., preparing for a Monday release of an AI model because we’re doing the finishing touches of our evaluation of that model, and we want to get in the hands of customers, and we want to make sure that everybody knows the benchmarks of it. Having done this now for 20 years, starting right at the start of the cloud, seeing the iPhone, seeing the iPad, this is absolutely the fastest I’ve ever seen tech move by at least five to 10X, the craziest I’ve ever seen this industry and the hardest, I think, anybody’s had to work just to stay up to speed with everything going on.

SAFIAN: And do you have a strategy about how you personally do that or you just don’t sleep?

LEVIE: It is possible to get eight hours of sleep in this environment, but it’s not possible to have any hobbies. So you can either choose hobbies or sleep, and most people are probably choosing sleep over hobbies. But something will happen at 10:00 p.m., and there’ll be like a group chat with AI friends. Everybody’s blowing up like, “Oh my God, I can’t believe this just happened,” and then it’ll be an internal Slack with 15 people on the AI team of, “Oh, gosh, we have to jump on this,” and it’s just like, “Hope everybody had their family dinner and that’s all behind them, because now we’re back, wired in on what’s happening.”

SAFIAN: And you’re not going to spend two hours working out that next morning. You just got to get right back to it.

LEVIE: No. I think if you have 12 minutes to lift some weights, you’re good, so-

Why Aaron Levie is critical of tariffs

SAFIAN: Amid all of this rapid and radical technology change, of course, we’re seeing a lot of other cultural change. Another topic I saw a lot in your social feeds, I guess on X, is tariffs.

LEVIE: Yeah.

SAFIAN: Now, you’re in digital products, so theoretically, you’d feel less whiplash about tariffs, but you’ve gone right at the Trump administration about them. Why? Is that because of what you hear from clients?

LEVIE: The reason why I was outspoken against them is I just fundamentally don’t like tariffs, Box or not Box. I think that the market does better with as few kind of market distortions as possible, or economic distortions as possible. Fortunately, things seem to be trending in a kind of winding down direction, but take any kind of punitive tariff above, I don’t know, 30% on a country, you’ve now inflated your cost of serving in a particular category or industry. So all of a sudden, the goods and services that you’re building, coming out of your country, now have this built-in cost increase that no other competitor deals with. Does that increase the odds that you win in a particular industry or decrease the odds? Anything that creates an artificial increase in costs, by definition, causes you to slow down relative to your alternative competitors, which is equally why I’m very much on the other side of the spectrum of, normally my Democrat views, on things like regulation, because regulation is equally an artificial increase in the cost of executing in a particular industry.

Tariffs are a way of increasing the costs. Regulations are a way of increasing the costs. I’m anti-cost increase. I certainly have found myself in this environment, being more libertarian than the people that I thought were libertarian, and I guess that’s one sort of virtue of the Trump administration so far.

SAFIAN: Yeah. I mean, there’s been talk about tech leaders sort of bending the knee of Trump, starting with the inauguration, maybe bending their values too. How do you calibrate sort of your personal views with what the company’s values are? It’s a question that some other CEOs sort of struggle with.

LEVIE: Yeah. I think maybe by being a founder, I have less of the struggle, because I can get away probably with more, or maybe even more than I should probably be able to get away with. In general, the default disclaimer is that these are my views. These are not the Box official, like put our logo on it views. These are just Aaron’s views about a thing, and so—

SAFIAN: And you’re not worried about the administration making trouble for you because of that.

LEVIE: I’m not worried in terms of I lose sleep over that, but I’ve evolved my personal ability to get, kind of, like aggravated quickly about everything happening. I’m speaking out on a handful of topics that, I think, matter to the country economically, but I’m trying to be balanced. I do think that we could spend less money in the government and get more out of it. Some components of DOGE I felt made sense, and then on areas like tariffs, where I just think it’s an economic disaster, I’m going to be clear that, I think, that’s a really bad idea.

How Trump is handling the AI race

SAFIAN: And do you have a conviction yet about what Trump’s impact on AI is going to be, whether that’s regulatory competition with China? I know you’ve been pretty positive about DeepSeek. Some people see that as evidence of China’s ascension, something to be afraid of.

LEVIE: Yeah. I’m weirdly less afraid of China. I have not gotten bitten by the sort of ‘be deeply afraid of China’ bug. People can definitely call me an idiot if things go really, really poorly with them. I think there are some hugely bad problems with China.

The hacking issues are a huge problem. IP issues in China are a huge problem. I don’t have the, “Oh my God, if they win AI, it’s all over.” I have the reverse though, which is, “We should win AI because economically, more of the profits are going to accrue to your economy.” But when I think about this administration’s approach to AI, there are some incremental positives relative to the Biden administration, so there’s a general bias toward supporting things like open source AI.

There’s a general bias toward not trying to overly lock down AI, but actually, let AI get more diffuse, because you eventually innovate faster when there’s more kind of angles testing your systems. I give this administration decently high marks on AI policy thus far. That could change, of course, but I feel more comfortable at the moment on AI than the number of other topics.

SAFIAN: Winning the AI war, how much of that is reliant on continuing to attract high-skilled immigration? I mean, the Trump administration’s immigration policy is sort of at the odds with the division of this being a destination.

LEVIE: So if you want to win an AI, my wish list is support open source AI, check, rapidly accelerate the development of chips in the U.S., and make sure we can control that infrastructure as much as possible over time, sort of check. Tariffs are actually a headwind to that. Don’t overregulate AI, so also check. But then, you need the best talent in the world, and we need a lot of it, and then that would be kind of neutral to negative so far. And to be clear, Biden didn’t do this either.

What you would do is you would just do the whole green card stamped on the diploma after college, and you would get anybody studying AI in the U.S., or even computer science in the U.S.. You would just be like, “We want you here. We’re going to build the best environment in the world for you. No need for you to go back to your kind of country of origin.”

SAFIAN: And the fear that those people are going to take American jobs, your point is it’s going to grow American jobs by having that kind of talent.

LEVIE: By having those amazing people not be in America, you, over a 10-year period will lose vastly more jobs than the incremental jobs that they are theoretically taking in the near term, because those people are going to be smart in our country or a different country, and they’re going to build AI in our country or a different country, and the country that has more of those, that flywheel of the better computer scientists doing the better algorithms, that need more compute, that build better products, the flywheels that happen in other countries will mean, over time, more jobs go to those countries. You want the Sergey Brins to build that company here. You want the Jensens to build that company here, and so you want the talent to stay here and grow here as much as possible.

Navigating chaos and finding optimism in tech changes

SAFIAN: You’ve been through so many waves of change running Box, and I’m curious if you have lessons or advice for other leaders today, who may be struggling with the pace, the sort of feeling of chaos that a lot of folks are experiencing.

LEVIE: I mean, I think, I’d probably credit to you, you kind of had this initial insight, right? The world is increasingly a world of acceleration. It’s highly dynamic. I do believe we’re in a globally interconnected world at this point. I think it’s a good thing.

I think it’s healthy for society. I’m firmly like a 99 percentile optimist of the benefit of all of this. It means we’ll get better cancer treatments, it means that people that aren’t mobile today will become mobile. We’re entering this incredible era of abundance and acceleration. And so I think the reason why I can stay up with it is because I’m excited by it all.

And so I think if it was draining and I felt like, “Wow, this is all bad,” I think I would be fatigued and stressed out and burned out, but to me, it’s kind of the opposite. I grew up with technology. I fell in love with technology. I think it’s this amazing gift, and so I’m only basically having fun. I mean, it’s stressful.

It’s stressful in the sense of I need to make sure that Box stays ahead of everybody else, and so that has anxiety-provoking feelings, but the excitement of the space in the field is what propels, I think, so much of my energy. And so to some extent, I think everybody has to kind of find their version of that to stay enthusiastic, to stay energized about what’s going on. I think for anybody in technology, that should almost be coming for free, because we’re in the period of the greatest amount of change in technology history, and you’re going to be able to say that you were at the center of it.

How will AI change over the next year?

SAFIAN: If we talk again in 12 months, or when we talk again in 12 months, what will have changed most about AI and the way we use it?

LEVIE: For consumers, I think our daily lives will still incrementally kind of evolve. Your AI assistant in the form of ChatGPT, or Perplexity, or Gemini, or Grok, or whatever you use is just going to be X more powerful. You’ll take an image of something, and it’ll instantly give you all of the analysis you’d ever want on it. It’ll generate images that are perfect, it’ll give you the perfect answer to your question. The consumer world has the playbook.

On the enterprise, I think the next 12 months, we should think about this as the period where we have our ChatGPT moments with AI agents. This is the first year where you could see the initial proof of concepts. But I think it’s worth noting that for the enterprise adoption of AI, this is going to be a decade-long journey. We thought that cloud computing was going to happen in three years or five years. We’re 20 years into cloud computing, and then the quarterly rate of cloud computing adoption is still growing at the same rates as ever before.

I think this will be much faster with AI to be very clear. But just so we shock ourselves, imagine we’re in 2045, and we’re still talking about, “Wow, AI was adopted in this enterprise for this thing.” Think about how unbelievably crazy that as a concept sounds. That’s how we are still talking about cloud today. When I go to a bank, they’ll still say, “We just deployed cloud for this trading platform” — 20 years, 20 years into this. So these things take a while. The change management takes a while. Partly this is why you’re seeing us and Shopify and others go in so hard on AI. You actually do have to kind of nudge, and accelerate, and create the permission to move faster.

That’s why moving AI-first now is a very relevant exercise, because you do want those learning cycles to happen in your company sooner and faster than it does outside your company, so you can be ahead of the curve. Society in a decade, decade and a half will look just completely different than it does today.

SAFIAN: Well, Aaron, thanks so much for doing this. This was great.

LEVIE: Thanks, Bob. Appreciate it. Good to see you.

SAFIAN: Aaron sees disruption as opportunity. Not that he thinks every disruption is good, tariffs are a case in point, but tech-driven disruption just gets him excited, and I think he’s right, we all have to find ways to be excited about AI, even if it scares us or feels alien, because it’s advancing at a pace that’s hard to get your mind around. The challenges for each of us are emotional, every bit as they are technological or intellectual. We may not want to sacrifice our sleep or our hobbies to stay up-to-date in these new areas, but those of us who do, who can make peace with the chaos and make it our friend, those people will be in the best position to thrive. That Fast Company cover story I referenced that included Aaron, it talked about a concept I called Generation Flux, a group of people, not defined by chronological age, but by the willingness to jump in and build new skills in an environment of uncertainty.

Today, because of AI and more, we all need to become part of Generation Flux. I’m Bob Safian, thanks for listening.