Inside Box’s AI playbook with founder & CEO Aaron Levie

0:00We're going to look at the last year and the next, let's say, two to three years as probably the most defining periods of workplace technology change that we'll ever live through. What would happen if many parts of your business, you could start to do things in an hour or two hours that would have otherwise taken a week? Which part of your business do you expect to disappear or become unrecognizable in the next 12 months? I think actually very few roles will sort of disappear kind of outright. I think it's what we will be doing in those roles that will fundamentally shift. We should have three, five, 10x more leverage as individuals inside of an organization.

0:34Everything that we do will be accelerated. How should we think about a world of resourcing when agents start to appear and become more reliable? In that world, the IC is now a manager and there's sort of no upper limit of how many agents they could be deploying. Then the question is, what is that manager of human managers of agents? What do they do? Should they also be managing agents? Open question. I mean, this is in the category of things that will change in a five-year period that might redefine 100 years of management science. I mean, it's super complicated because you have model releases every two weeks right now.

1:09The velocity is extremely fast. It's this incredibly exciting, stressful, crazy time. But for those that enjoy learning and changing and evolving how they work, this is a very exciting time to be diving into that.

1:29Today, I'm really delighted to have Aaron Levy, the CEO and founder of Box as my guest. Box is a company, a product that I first came across, I reckon, 20 years ago. Before, it had the.com domain. It was one of the first cloud storage companies in the world. Of course, now it does much more for enterprises. And Aaron has been leading a transformation of Box into an AI-first company, both for the company itself and for its customers. And Aaron, you've been really public about the benefits that AI will bring to all of us. If Fox is fast becoming an AI-first company, which part of your business do you expect to disappear or become unrecognizable in the next 12 months?

2:15I think what's going to happen, the part that will be unrecognizable, I want to first caveat that I'm probably going to be wrong on 90 % of anything that is sort of 12 months out. You know, anything in AI that you can't like see and feel right now is just so hard to predict. And it's actually, I think, relatively apropos of the name of your core content right now. It is this idea that everything that we do will be accelerated. And so I somewhat try and readjust when we get asked like, okay, what roles won't exist, for instance. I think actually very few roles will sort of disappear kind of outright.

2:48Now, 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.

3:19Sci-fi doesn't sort of anticipate like dynamic economies. It usually says, OK, we're working in the factory, robots took the jobs, and now nobody's working. That's kind of the... It's the lump of labor fallacy, as the economists call it, right? That's exactly right. So like every sci-fi book ever written has a lump of labor fallacy, you know, 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?

3:55We'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 do 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.

4:32But use AI to actually move faster as an organization. So if you roll out a year from now, but then I think even probably, you know, it's almost easier to think about five years from now than one year. But at some kind of point in time in the not crazy amount of future, I would just argue that we should have, you know, three, five, 10x more leverage as individuals inside of an organization, which means that when we go and brainstorm a new marketing campaign to go do, instead of us having to have three brainstorms over a two week period and go in and, you know, talk to lots of other companies for best practices and benchmarks, that might be a 30-minute exercise, you know, just involving your marketing people and AI kind of, you know, coordinating on that.

5:14And then boom, you just, you know, shrank that process by a couple weeks into 10, 20, 30 minutes. And so imagine that across engineering, product development, marketing, you know, going and coming up with the sales plan for a customer. What would happen if many parts of your business, you could start to do things in an hour or two hours that would have otherwise, you know, taken a week. And what is that? Yeah. Sorry, pardon me. But there's this idea that embedded in that is that we all have big backlogs in our Kanban boards. And, you know, can you move through that backlog much, much more quickly, which, of course, talks about one of the behaviors that's important.

5:52Can you cultivate useful things to do further down the backlog? I think we'll get into that idea as well. So there is this notion of... Well, and to that on the lumber labor fallacy, like the campaign board might go off on a completely new direction as a result of this. I like as an example, I have personally and this is like to the chagrin of my my colleagues, I have lit up more projects internally because of my access to AI. Because what I do is I go experiment on some idea, then I then get convinced is much easier to go do now because AI kind of let me start to do the experiment on it. And then now all of a sudden, I've lit up a project that now people are working on.

6:34And that wasn't in their Kanban board a week ago. I think it's something you may have said on X. I think you said it makes it much easier to start projects. And I remember reading that X post thinking, yes, and who gets to finish them, Aaron? Right, no, 100%. I literally, so we have this project that we're doing right now on the tail end where basically I shaved about three days to a week off of the initial brainstorm process that would have taken. And I did that in a couple of minutes with AI. Then I rallied the team around it because the AI did the upfront part and it sort of showed what it might look like as a result.

7:09We still had another three weeks of work to go make it happen. I shaved off a week at the front end, but by shaving off the front end, I lowered the barrier to us sort of realizing what would be possible. But then I added three weeks of work to everybody else that wasn't on their plate. So AI is going to do that a lot more than we realize because what's going to happen is it's going to expand the aperture of now all the things we can go work on. I completely agree. And, you know, there's this idea of Armdahl's law, which is one of the famous computer science engineering laws, which says that, you know, if you have a process that's got a number of steps and you accelerate one part of the process, if that's only 10 % of the duration of the project, you've only shaved 10 % off the entire time.

7:53And so we have to turn that into reality. And I think there's this notion of what is the propagation curve of AI within an enterprise. So it feels like you've described individual productivity, your individual productivity, maybe it applies to my individual productivity as bosses who generate work for other people, accelerating. One of the things I found quite curious in talking to enterprises and CIOs around the world is that many of them report lots of individual improvements, right? Individual developers writing more code, whatever the metric happens to be, but they're not seeing the sum of the parts being necessarily greater than the individual contribution.

8:36There seems to be some mechanism that breaks down from individuals being able to do really well using AI and a team, a function or an enterprise being able to return the same result. Does that ring true in what you've seen within Box or your customers? I think embedded in there is an interesting kind of point about we will see stats of, okay, individual productivity goes up 10, 20, 30 % with AI. But like clearly at this stage in 2025, organization-wide productivity is not 25 or 30 % higher or already the economy would already be completely impacted. And so there's some kind of dilution that happens through each kind of turn of the crank of incorporating the AI productivity into the larger system.

9:18And similarly, there's, I don't know if you've ever read the book, The Goal, but it's all about basically process improvement. And the book basically goes through exactly what you just said, which is it sort of goes step by step and finds each of the individual bottlenecks in a particular kind of system. And until you sort of figure out where is the bottleneck as the next sort of gating factor in productivity, you don't get any benefit at the other end of the amount of productivity you get. So I can light up a project incredibly quickly. But if every other corresponding part of that process is not also benefiting from AI, then all I've done is in many cases actually added more work, which then won't inherently even show up in productivity metrics because I've actually now added even more tasks to the organization.

10:04And we haven't yet gotten efficient enough to then sort of see the productivity gains across the organization for that. So I think this is probably very much just a natural evolution of, I wasn't around for it, but I'm sure that like there was a multi, you know, probably decade plus evolution of like the first people with email in a corporation were like super productive, but then they were ultimately bottlenecked by everybody else that didn't have email. That was a probably a decade long process for everybody to finally get wired up where you could efficiently communicate with everybody to the point where that showed up as a productivity gain.

10:37And then reasonably quickly after that, we drowned in full inboxes because everyone had access to email. So you went through this sort of funny cycle. But you've raised something that I'm curious about. What is the balance between you as the CEO being good with these AI tools and coming up with new projects and needing your frontline workers to be really, really great at them? So sometimes we think of when it rolled out, the internet was very much in many companies sort of frontline driven and slowed by the center. If you look at things like ERP, that was driven from the top because frankly, who wants to live their life in an SAP interface and sort of forced down in the center?

11:17And you've got these two different models. To what extent do you need to enable the absolute frontline workers? And what's that balance between you as a boss leading them from the front? Yeah, so I benefit from just, I'm already pre-wired to just like love technology and always, you know, want to explore new things. That's why we created Box. And so I have a little bit of a natural advantage because like this is just this is like what I do for fun. These are like my hobbies usually are just like technology. Like it's not like I don't do I don't do fly fishing. So I already love technology. I love to play with technology.

11:49Most of my social friends are doing technology or AI. So I get it in every sort of part of my life. And so then the question is, how do you make sure that you're enabling all the folks that don't have that as sort of the same built in default way of way of operating? We spent a lot of time figuring out how do we enable kind of the front lines or the broader population of colleagues to become better and better at these tools. And it's interesting because this is a space that is moving so fast that, you know, most people are, you know, probably fatigued actually by the amount that's coming at them to try and figure out.

12:23And in particular, if you tried something with AI a year ago or six months ago and it didn't work, you might have written off that, well, okay, AI can't solve that particular thing where I want to review a contract or go and summarize 500 documents into a report. You might have been like, okay, AI doesn't do that. And actually, check back in today and it does. So the need to kind of stay current on everything that's happening is just unbelievable. So we're doing a lot of things like some of our practices are every Friday, we have an internal all hands, and we'll have somebody demonstrate how they're using AI.

12:59We're trying to make it more of a social collaborative exercise where you're demoing in front of your colleagues, how you're using AI to get some particular type of work done. We're working on more internal enablement, which would include kind of education. We're pushing everybody to read sub stacks and subscribe to newsletters and listen to podcasts so they can kind of stay as current as possible. I think about this as if you're working in technology, you know, in particular, but then probably the broader economy, certainly, you know, we're going to look at the last year in the next, let's say, two to three years as probably the most defining periods of workplace technology change that we'll ever live through.

13:36And so it's this, you know, incredibly exciting, stressful, crazy time. But for those that enjoy learning and changing and evolving how they work, this is a very exciting time to be diving into that. So there's a lot in that, a couple of different questions. The first one I wanted to pick up is give us a flavor of those Friday afternoon learnings. I mean, we do something similar with my team. In fact, starting in December 2022, we started to do a daily all hands, which is only a team of five, right? There's a smaller group, 15 minutes. What did you do the day before? And back in those days, of course, to show how random it was, it would be a bit of mid-journey.

14:17Well, I did this image in MidJourney. And now it's getting more and more sophisticated. You know, people are showing, you know, workflows that might involve eight or 10 agentic steps. They might involve decision-making by the agents and things that break rather randomly. Like, you don't know. It worked really well with the 2.0 version of Gemini Flash. And in the 2.5 version, it stopped working. And, you know, of course, but we're a small organization. We know each other very, very well. six people. Box is much, much larger. So what do those actually look like? And how do you get contributions?

14:54And is it still, oh, look, I've got a great prompt in Claude. Let me show you. Or is it we've built something in crew.ai that involves 500 steps? Yeah, the focus is we want to push the limits of our platform. So it's a narrowed scope, because it's just Box.ai functionality. All right, you've got agents and other things like that built into Box. Exactly. And so it's all going to be related to automating a document process, generating content, reviewing content, summarizing or adding intelligence on top of data as the benefit of the surface area is somewhat narrowed. But what happens is we'll have a sales rep come and it's all in Zoom.

15:35So come present for, you know, 500 plus people that tune in live and then thousands that will watch it. They'll present their workflow for, hey, here's how I take all of my transcripts from my customer conversations and I turn it into a summary. And then I sort of tune it for that customer's industry and I send off an email. or I take all of our sales material and I produce some best practice guide for my sales team or I'm in engineering and I want to take a chunk of code and have the AI look through it to improve it or do documentation. So these are the kind of use cases that are emerging organically and then we just have those basically boxers go and show that to everybody in the organization.

16:18And then for us, again, it's like very selfish because both we want to work in this new way so we can be helpful for our customers. But we also want to see then the upper limits of our own technology so then we know what to go improve on the product. If we can shorten the product feedback cycle that normally happens, which is you release something, you listen to customers, it takes a couple of months. If we can internally just learn those things very quickly, we can recycle that back into the product roadmap and then improve our own internal development velocity. So we're using it selfishly for our product teams to then also see, oh, wait a second, We ran into this issue where people want to share prompts, but we don't have a useful mechanism for sharing those prompts.

16:59Let's go build a prompt library, like those kind of things. Yeah, I could do with a prompt library. I mean, it sounds great. It sounds very, very inclusive. It sounds like there's a lot of activity, but activity doesn't necessarily beget results. So let's take that upper level to your board. They need clarity. They don't have a ton of time. So what is the single metric that cuts through all of this activity, all of this height, to really reveal benefits for Box from these activities that are showing the productivity? I think as an industry, we're very early in what is a normalized sort of metric to quantify AI-driven productivity.

17:37I think there's a range of approaches that you can take. We've actually explicitly said that right now we're still in the journey to figure out what metric we're going to land on. There's an easy one, which is sort of like, how much money did I save directly? Then there's another one, which is how much money in productivity or hours or system time did I have cost avoidance on? So that's like, if I had done this with human labor, it would have cost this much. And then a third easy one is just like, what are the hours, tokens, some metric of just sheer output coming from the AI that now you're utilizing?

18:13Right now, we're actually way more focused, and I'm very comfortable being more in the, we actually want like a thousand flowers to bloom mode. I don't know if I would feel comfortable if I were like at JP Morgan with that strategy, but being on the front lines of a software company that is fundamentally becoming an AI first company, I don't mind a little bit of a period of, let's just, let's let everybody go and test and push these systems. And I think the best scenario for us right now is this idea of reveal preference, right? Like, let's just like see what people actually do. And almost by definition, the market, you know, we set very high goals for anybody working in the company.

18:51And so it's quite easy just to then let the market decide how to use AI to accomplish those goals. And so if we're actually setting our goals properly, and if the managers or leaders know what AI is capable of, so if we know that AI is capable of making a product development process go 30 % faster, and we set that goal kind of built into that, then we don't need to tell people to use AI or how to use AI. By definition, the only way to hit that goal would be to use AI. So for us, at least, I'd rather ratchet up the goals. I'd rather accelerate the timelines, hold people to a high bar of how quickly things should happen.

19:27And then revealed preference will just be what tools do they use? How do they incorporate that in their workflows? We don't necessarily need to hand everybody the exact template to go follow. Do individual workers have a budget of tools that they can access? I mean, what we've done within my team is that everyone has a quite generous$1 ,000 a month budget for AI. So once you've got O1 Pro or whatever the chat GPT Pro thing is, that's 200 bucks out of the door, right? And then you need Claude and so on. But, you know, no one's really approaching that level right now. But the idea was to give people enough freedom to experiment.

20:03and then every three months you can do a triage and say, what worked, what didn't work, what don't we now need, what has fallen off the agenda, and what is working. But what is the right way to allow them to explore so you do have a thousand different flowers that are blooming, so you're exploring the possibility space for Box or any enterprise, but without losing sense of kind of financial control or security or data? Yeah, so I love that idea of a user budget or employee budget. And that's exactly probably what I'd recommend to anybody outside of our company. Right now, we have not kind of created any sort of stated limit.

20:42And mostly because I don't know what I would, I would have our organization do. And for example, so within Box, Box AI basically connects almost any leading AI model to your data. And so that means that as an employee, you can go into Box and let's say create a document and use Cloud 3.7 to generate, any of the content in that document. So you're effectively able to use any of the leading AI models within our company. And we don't have a budget limit only because I think it's very provocative and I think it's the right thing to do for us. We just said, go run wild. We want to learn what everybody's doing.

21:19We might now, who knows, if you could kind of like parallelize 100 coding agents all using Cloud 3.7 doing long running agentic coding tasks, maybe we'd be like, okay, sorry, you've just spent$200 ,000, you know, building some feature, like then that'll be a problem. We are not there yet. And so maybe we'll have to check in at some point if we've had to kind of evolve our practices on that. That's an important segue. Thank you. You're such a wonderful guest because we wanted to move towards what happens in a world of agents. And that has been the sort of the rhythm of 2025. I guess what happens with the world of AI agents is these things can spawn multiple instances.

21:59is they get to run much more autonomously because you move from the prompt respond, prompt respond, where the human is always in the loop. So that creates an issue around reliability and trust. But it also affects how you think about the design of the organization. I noticed that Moderna, which is the wonderful biotech firm, there was a story in the Wall Street Journal a few days ago saying they've merged their tech and HR under a single person so that you can align workforce planning with AI. Moderna had famously deployed more than 3 ,000 different GPT tasks in the previous couple of years. How should we think about a world of resourcing in general when agents start to appear and become more reliable?

22:49Yeah, I mean, this is definitely in the category of, again, things that will change in a five-year period that might redefine 100 years of management science, this is one of those. You know, if you think about like the Alfred Sloan typical management science approach of, okay, you know, we developed all these hierarchies and everybody's an expert and everybody has sort of division of labor and, you know, very clean systems. You know, this is sort of blowing that up a little bit because now you do have some fundamental questions of what happens when an IC or individual contributor effectively can become a manager of agents and there's sort of no upper limit of how many agents they could be deploying.

23:29In that world, the IC is now a manager. Then the question is, what is that manager of human managers of agents? What do they do? Should they also be managing agents? Open question. The other question is, how much is this the responsibility of a reinvented HR department? How much of it is a responsibility of a reinvented IT department where you can either have HR sort of thinking about, I have a new type of labor force a la agents, and I have to think about them in coordination and concert with people? Or is it the IT department saying, hey, we're like the technical experts. We're going to always be on the front lines of what's happening in the AI space.

24:10And we're going to bring that to the organization or the lines of business or to HR and say, hey, I have a new type of labor I can supply to the organization. Here's the latest set of offerings that we can bring to the business. I'm probably partial to the latter because the technology is moving so fast that I think you're going to need to have deep technical expertise to understand where this is all going and how to incorporate it into the rest of the business workflows. Because these AI systems will not show up in any kind of physical form for the foreseeable future. you know, like we can get into robots or whatever, but like that means that they're only going to be deployed from software and IT is going to manage that software.

24:51So, so I think that this puts IT in this unbelievably interesting role, which is you're now kind of responsible for the digital workforce of the company, which means that, that you need to then also be incredibly astute at the business processes of the company. You need to be incredibly astute at, at basically, you know, if I could go and add a workforce to the sales team to go in and do lead generation or lead review, what part of the sales productivity metric would that move? That's not usually a classic IT conversation that they would normally go in and be that partner on. In 5 % or 10 % of companies, definitely.