Box at Citi TMT Conference: AI Strategies Drive Growth

On Wednesday, 03 September 2025, Box Inc (NYSE:BOX) presented at Citi’s 2025 Global Technology, Media and Telecommunications Conference. The company highlighted its strategic focus on artificial intelligence (AI) as a key growth driver, amidst a stable macroeconomic environment. While Box’s AI initiatives are propelling its performance, the company remains cautious about broader market conditions.

Key Takeaways

• Box is positioning itself as an "AI-first" company, embedding AI across all offerings.
• AI capabilities are significantly contributing to revenue growth, with plans to increase AI’s revenue share from 5% to over 10% in the coming years.
• The company is seeing increased seat growth and stabilization in churn rates.
• Box supports multiple AI models, offering flexibility to customers.
• New partnerships and integrations are expanding Box’s market reach.

Financial Results

• Box’s AI-driven products, particularly Enterprise Plus and Enterprise Advanced, are resonating with customers and driving financial outperformance.
• The company has achieved its year-end target for net retention rate ahead of schedule, with an increase of one point quarter over quarter.
• Enterprise Advanced plans provide a 20% to 40% revenue uplift over Enterprise Plus.
• AI is currently contributing to 5% of Box’s revenue, with expectations to surpass 10% in the next few years.

Operational Updates

• Box is focused on leveraging AI to unlock the potential of unstructured data, enhancing workflows and efficiency.
• The company is embedding AI across its platform, supporting models like Gemini, Anthropic Cloud, GPT, and Llama.
• AI certification is mandatory for all employees, ensuring internal expertise.
• Box is doubling its Enterprise Advanced deals quarter over quarter, driven by AI integration.

Future Outlook

• Box aims to continue its AI-driven innovation, developing new features and capabilities within its Enterprise Advanced plans.
• The company is expanding its partner ecosystem, targeting legacy ECM vendors to capture market share.
• A new Chief Revenue Officer, Jeff Newsom, is focusing on scaling existing strategies to enhance Box’s market position.
• Box plans to build an AI agentic layer to enhance its capabilities, allowing deep research and comprehensive data analysis.

Q&A Highlights

• The deal environment remains stable, with customers showing interest in AI solutions.
• Box’s new products are key drivers of performance, with AI enabling more complex use cases.
• Customers are seeking platforms that can keep pace with AI trends, with Box providing expert guidance and support for multiple AI models.

In conclusion, Box’s presentation at the Citi TMT Conference underscores its commitment to AI as a transformative force in content management. For further details, readers are invited to refer to the full transcript.

Full transcript - Citi’s 2025 Global Technology, Media and Telecommunications Conference:

Steve Vendors, Software Research Team, Citi: Alright. Awesome. Thanks everybody for for being here for day one of the Citi TMT conference. I’m Steve Vendors, part of the software research team here. And with us today, we have the team from Box.

We have Ben and Dylan. Wanna thank you both so much for for being here. Thanks. Maybe just to start, just I think probably most people know Box. It’s been around for, I think, public for almost ten years now.

But maybe just talk about, you know, takeaways from the recent quarter and also introduce introduce yourself, especially Ben. I don’t know how much how often you’re doing these kind of things.

Ben Koos, Chief Technology Officer, Box: But Sure. So Ben Koos, chief technology officer at Box, and I’m helping to lead some more AI initiatives. Yep.

Dylan Smith, Cofounder, CFO, Box: Dylan Smith, cofounder, CFO. And I would say in terms of just takeaways from the most recent quarter, really, our excitement around the way that our newer AI capabilities are resonating with customers. That shows up in a lot of the financial results as well as kind of the tone and tone of the conversation we’ve been having. That’s both with Enterprise Plus and also with Enterprise Advanced, which is our newest plan that we launched just back in January. And we’re really pleased with the initial adoption, which is what drove a lot of the outperformance that we’re seeing in various top line metrics.

So really excited about what’s to come in the road map and the journey down that path, and we’ll be sharing more on that in just about a week at BoxWorks, our annual customer conference.

Steve Vendors, Software Research Team, Citi: All right. That’s a great place to start off. I wanna start on the macro side first, and then, Ben, I I swear we’re gonna get to a lot of AI and product stuff after that. But just in in deal environment, like, are you seeing out there right now? You know, how are things maybe a little bit different this past quarter?

Because I think to your point, the metrics look pretty solid. But what are you actually seeing? Maybe what’s what are you seeing across verticals, geography, segments, all that?

Dylan Smith, Cofounder, CFO, Box: Yes. So I’d say would actually describe the environment as relatively stable versus this past quarter. So I think customers are certainly still making decisions and buying, and there’s a lot of excitement about AI. But it’s it remains a pretty cautious and somewhat challenging environment. Nothing too unique to verticals or geographies other than there’s probably less of a maybe freak out on the public sector side, still a pretty challenging environment.

But I think a quarter ago, we were much more in the thick of things, and there was even more uncertainty. So that has steady kind of settled down a bit. But overall, I would say the most recent Gorgias performance was more probably box specific factors and some of the newer products driving that versus any real discernible change from a macroeconomic standpoint.

Steve Vendors, Software Research Team, Citi: Okay. That’s that’s great to hear. I do wanna talk about suites. I think it’s been a big point of focus for for you all for a while. But just maybe how are the use cases that you’re seeing different from that perspective?

How are you, I guess, leveraging AI those kind of use cases as you expand that product set?

Ben Koos, Chief Technology Officer, Box: Yeah. So one of the things that we’re noticing with customers is that many of them, when you ask them, like, how will AI actually provide value to your enterprise? One of the top things they’ll talk about is their unstructured data. And and we think a big reason for this is that we’ve had about, like, you know, ten or twenty years of customers, like, going through and optimizing their structured data, getting new tools, getting new capabilities, new technologies. But then usually anything that was data would be something that required just usually intense, like, work from a a person to understand, to create.

And with generative AI basically being born on this class of data, there’s a lot of opportunities that customers are thinking about, which are things around how can I better make use of some of my most valuable content? It’s typically about 90% of what what customers have is their unstructured content. And so then in terms of the Box offerings, we had created this set of capabilities around our enterprise advanced suites, the ability to do box apps, the ability to do more advanced workflows, the ability to do things like forms and document generation. And and and so when you add in the power of generative AI, in particular around the idea of structuring unstructured data, suddenly you can start to do things that you couldn’t really do before. For instance, companies that have a lot of unstructured data for something like like leases for commercial real estate or if they’re talking about their their client files for customers who are doing, like, wealth management or for companies that are, like, doing life sciences reports.

And on and on, every company has a set of very, very critical data they call them structured data. And our enterprise advanced capabilities let them manage that. And then what AI does is then allows them to be able to marry their their unstructured data, which is typically authoritative with the idea of the structured data, less inquiry it, less understand it better, less than draw trends. And then when you put that into boxes enterprise advanced capabilities, you get this sort of new way to interact with oftentimes in a very a much more productive, much more efficient way. And so we’re seeing a lot of customers who are doing things like, you know, loan origination or handling processing of of medical documents, handling processing of, like, life science and materials.

They’re seeing efficiencies not only with just time spent, but also delivering better results to their to their clients. Processing those loans faster, you know, dealing with their customers more efficiently, and so on and so on.

Steve Vendors, Software Research Team, Citi: Okay. I mean, it sounds like the use cases, I think, that you’ve called out, especially in the earnings call the past couple of quarters, sound pretty different than maybe maybe what we’ve seen historically from from from Box. Maybe what has how are those use cases evolving? How are you kind of seeing the opportunity around some of kind of the the workflow automation slash content, capabilities kinda coming together and and and marrying that together.

Ben Koos, Chief Technology Officer, Box: I I think this is the, not only has the sort of the box product set evolved to be able to handle these and what we we call our advanced suite, but then also this is, AI has now matured to the point where it can handle these kind of use cases better than before. So you especially with some of the newer, more sophisticated models, the ones that have introduced the concept of thinking abilities in addition to the idea of using the sort of agentic paradigms, like, where you have AI agents not just do one thing for you, give you the answer quickly, but then also do more complex tasks and try and you you give an objective. You’re like, I’m trying to accomplish this, and AI agents can, like, sort of work with you and work with other agents to make this happen. Like, these are the areas that people are starting to say, like like, these these were previously unexplored. And so, again, because a lot of it revolves around our structured data, then our customers are coming to us and saying, can you help me work on on this internal process that we have to try to make sure that make this work better in different ways?

And so this is where the features that we’ve building for many years are directly playing together with the new AI capabilities and sort of letting people start to get this, like, new technology disruption, but in a form that they can utilize without having to build it

Steve Vendors, Software Research Team, Citi: all themselves. Okay. I guess from a budgeting perspective or, I guess, the use cases you’re going after, how much of it is having to coach the customer along and tell them that this is something that they you know, need this, or is it kind of a replacement of something that they were trying to do historically? Just what does that what does that look like?

Ben Koos, Chief Technology Officer, Box: I think a lot of, like, the the concept that AI is going to be very valuable enterprises is something that every single customer that we to is very aware of. And in many cases, they’re trying some some of them are trying to build it themselves. Some of them are looking at different platforms that can can do can do this together. So many times when we’re working with customers, they have an idea about the kind of thing that they want. Maybe they’ve been experimenting with it.

Maybe they’ve building some things themselves. But many of them come and say, I don’t want to be in a world where they have to maintain everything that they have to make sure they handle. Like like, in the world of of of unstructured data, there’s just a ton of things you have to do to prepare the data, to make it able to be, you know, through the embedding so you can retrieve it using retrieve augment generation, using vector databases, and all these underlying technical aspects that make it so that you can get really quality answers, what we call enterprise grade security in addition to just making everything work. That many of our customers are asking, what is the platform of the future that will let me do these kind of capabilities that I can rely upon, not only today to do these use cases, but then also be able to keep up with ongoing trends? Like, if you just look across most the the top model providers these days, I think there’s been 15 models in the last twelve months that have been, like, arguably the most intelligent piece of software that has ever existed in the history of a civilization.

But most people have a hard time even naming the them because things have changed so many seemingly every week. And so being able to keep up with that so that they can just make choices as opposed to trying to, like, support all that, it becomes something that we need less support of these enterprise grade platforms.

Dylan Smith, Cofounder, CFO, Box: Okay.

Steve Vendors, Software Research Team, Citi: I know I think Aaron has been I think you’ve been pretty prolific out there talking about the future of AI and and and what that looks like. I guess, what does that mean for for Box? And, I guess, secondarily, you know, to your point that the model changes so quickly and, you know, there’s something new that comes along that’s better. How difficult is it?

How easy is it to actually hot swap models and figure out kind of the best model for a use case that you might be using?

Ben Koos, Chief Technology Officer, Box: Yeah. I mean, it’s it’s one of the challenges is that although there are a lot of very good models in the world at any given time, some of them are better than others. Mhmm. And especially and some of them will be better than others for the thing you wanna do at that that moment. And and then you see with some of the, you know, it’s almost rare for especially some of the bigger organizations to, like, offer you the full suite of models.

Oftentimes, they have a preference in one way or another because maybe they provide it. So so for Box, we support Gemini based models. We support Anthropic Cloud based models. We support GPT models from from OpenAI. We support law based models from Meta in in addition to some others.

And so our job is to make sure that we can not only provide them to customers so they can pick and switch if they decide that one of them works better for the use case, no promise, an option in Box. But if they but we don’t make them have to know everything. So we have it we’re opinionated and they say, well, we found that this works well. So the default out of the box, you have to do no work to configure. Maybe you never heard the name Gemini.

Don’t doesn’t matter. You can still get the the that you want. And and so we’re we’re part of our value as a unstructured data platform and as a company that caters to making everything straightforward is to say, we’ll make the decision for you if you don’t in the best that we know, but then allow you to both swap it, but also customize it to get the best for whatever use case is.

Steve Vendors, Software Research Team, Citi: Okay. That makes some that makes sense. I guess tying it maybe back to the model to the financial financial side of the house. Just how are you thinking about maybe where the AI kind of revenue base is today? How do you think about what that maybe looks like in in the future?

And I think I think you have a medium term model out there. And what are you kind of embedding assumption wise into into that?

Dylan Smith, Cofounder, CFO, Box: Yeah. So I think about it, you know, we we don’t really think about the kinda AI revenue because, you know, Box is really an AI first company, and and we have different levels of capability, but we include, you know, some pretty compelling AI functionality to all of our plans. As it relates to kind of the model change and impact that’s also pretty closely tied AI, we certainly have our enterprise advance plan that’s been in the market since January. Really pleased with the early momentum there. We expect that to be a driver not just to kind of sustain and deliver the steady improvements in price per seat that we’ve been seeing, But we’re really encouraged and called this out in our most recent earnings call that it’s because the use cases that it’s enabling, we’re starting to see seat growth have a bigger impact and pick up a bit, which is what drove our net retention rate up one point quarter on quarter and got there to that year end target earlier than we’d expected, just halfway through the year.

So ultimately, think the impact of AI, it’s really going to show up in both through the impact on our net retention rate, just giving customers more to buy, more use cases to make it compelling and applicable to a broader set of users in our enterprise customers’ organizations as well as the different ways that we’re monetizing our high value AI capability separately. So there’s this concept of AI units for these really high value use cases on top of what customers we’re paying to get into Enterprise Advanced, which is a 20% to 40% uplift beyond Enterprise Plus. We’re also monetizing the through AI units. So that is a variety of different ways that our customers will be using the platform, and we expect that to contribute from about 5% of our revenue today to 10% plus a few years from now. So those are kind of the biggest, you know, drivers we think about bridging the AI impact on our overall top line growth.

Steve Vendors, Software Research Team, Citi: Okay. Alright. That’s I think that’s that’s pretty clear pretty clear there. Do wanna dig into the seat dynamic again, which I mean, great to see it’s it’s growing. How much of that is from, you know, expanding use cases, capturing new users versus maybe churn dynamics improving?

Or I think there’s been some, seat based headwinds in the model. Like, is that beginning to stabilize? Just how do we think about those various factors that are starting to support that seat growth again?

Dylan Smith, Cofounder, CFO, Box: Yes. So really more about the use cases and the actual seat ads is what’s been driving that. What we did see, looking back a couple of years, was some seat pressures, reductions as customers were going through a pretty jarring economic shift, and that caused some of that. But that’s actually stabilized and been stable for several quarters now. And so our churn rate has been stable as well.

And the more recent trend has really been about adding back versus stabilizing any losses.

Steve Vendors, Software Research Team, Citi: Okay. Alright. That’s, very clear on that on that side. Maybe going back to the the the product side and and and talking about AI a little bit more. You know, how are you thinking about the future road map in the in the product side of where it makes sense to kinda layer in more gen a GenAI capabilities.

Maybe what is the the future of content management look like in a in a gentic world, and and what is Box’s, you know, Box’s place there?

Ben Koos, Chief Technology Officer, Box: Yeah. Sometimes internally, we talk about the idea that if we were rebuilding Box today, then what would we do? And then, of course, the thing we would do would be to make it an an AI first company in in platform. And that’s how we are actually approaching everything we’re doing is to think of it in those terms. So one of the most important things for us is that not only do we have AI features that are helpful, but we also have an AI agentic layer on top of our platform to be able to provide all of the latest AI capabilities with the latest AI technology paradigm so that we can then be able to handle almost anything that a customer might want to do with unstructured data, then we’ll provide to that.

We’ll provide it in the form where they have the ability to use it directly in our product, but then also power integration so that that you could have your structured data stored in Box, use it on our system, and then also something they can build on top of it themselves. And so this this is across the board from things like doing retrieve on that generation securely based on your permissions on your data so that you can find information, not just search for data, but find ask a question. AI will figure out the answer and tell it to you and tell you where that came from. In addition to things like extracting, unstructured data from unstructured data, Data extraction is one of the most important things that our customers are talking about. They’re thinking about all the benefits that they have when a data is in a database, in a in a a in a set of of the tables that they can query, that they can run advanced analysis on, but then also tie that to the unstructured data.

So the the AI can go through and basically represent in both ways so that you can get the best of both worlds there. And so having these capabilities where you have AI that continues to evolve to do this is very critical And you’ll see things that we’ve we’ve talked about previously, like our deep research ability where you can actually give the box a whole bunch of data and ask the AI to do not just answer a question, but do deep research, prepare a very comprehensive report like you would get from an anal like a somebody who spent, you know, days or weeks looking through this kind of information. And these are the kind of capabilities we build an agent form that can do more and more over time, agents working together, agents working with the agents from other platforms, and then AI ecosystem. And and we believe this is going to be the future evolution of the way that these enterprise platforms work together.

Steve Vendors, Software Research Team, Citi: Okay. I think we’ve we’ve heard a lot about, like, MCP and utilizing that as kind of the the next kind of, I guess, evolution of this. Yep. How do you think about what that enables, and and maybe how does that kind of further, evolve the opportunity for for you all?

Ben Koos, Chief Technology Officer, Box: Yeah. I I mean, m c the MCP protocol is is just kind of amazing for this exact reason, which is that, previously, if you wanted to have two platforms work together, they had to, like, sit down and do a bunch of engineering work together. And that limits roughly like, this is why some enterprise customers historically have been always wanting more integrations that work better together. And then with MCP, though, the actual hard work of what it takes to integrate two systems together starts to be more of asking the agents to figure it out based on these published protocols in their MCP servers. You get this big benefit of enterprise platform.

But then also customers who say, I want to use these platforms instead of it being, you know, find some team who are dedicated, who are really good at coding, who can do these things. They can start to say, I have, you know, their own either internal or or take one off the the shelf of an MCP client. And you can say, can you do this? And then the AI agent will look through all of the the things the the MCP service that has access to, and it can just do it for you. And it’s this really amazing moment where you’re like, I just accomplished something that used to actually take giant amounts of coding, maintenance, work, testing, and then the AI agents with this how this protocol can figure out how to do these very advanced tasks.

And that’s something that I mean, it’s part of the reason that MCP is very everybody wants to talk about it is because it really enables this integration across platforms in a much more rapid and sophisticated way.

Steve Vendors, Software Research Team, Citi: Okay. And it’s still early. I’m sure it’s very baked into the product road map and how you’re thinking about that. Yeah. What does that look like?

Yeah.

Ben Koos, Chief Technology Officer, Box: So we we so the way it works is you have either the low what they call local MCP servers or remote ones. We’ve offered The the we’ve offered all of our early like, all the the functionality of Box baked into this MCP server that customers are asking for. Over time, we would see that you would have more and more functionality going into this used in more and more ways. But the the value of an MCP server is that once you make it available, people can just start to use it and find a lot of value from just the the the things that are that are out there right now.

Steve Vendors, Software Research Team, Citi: Okay. And I guess from monetization perspective, it’s about driving consumption, driving that element of it? Yep. Okay. I’m gonna pause there and see if there’s any any any questions in in the room.

And, otherwise, I have a lot more that you can dig into here. Okay. I know you have I think your Boxworks conference is next week. Is that right?

Ben Koos, Chief Technology Officer, Box: Yep.

Steve Vendors, Software Research Team, Citi: From a a product perspective, I don’t want you to, you know, give everything away here. But, you know, how should we think about, you know, what that looks like or or maybe what the high level feature of a a Box looks like?

Ben Koos, Chief Technology Officer, Box: I think in many ways, you’ve seen that we’ve talked about over the last year that a lot of the focus is continuing down this idea of enterprise advanced, the features and capabilities that we’ve launched there, things like Box apps, things like our our workflow system, things like our forms and our doc gen. These kind of next generation of the not just content, but your most valuable content organization and how you manage that. And then using the capabilities of of AI, both from, like, the capability we provide in addition to customizable agents. And and then and then for all of those, there’s a very long road map associated with all those capabilities, and we’ll be announcing new capabilities that that are part of of of sort of a cross box all all of these kind of areas. Okay.

And so these are the the ongoing set of both now with these announcements and going forward, the kinds of things that we’re we’re committed to do, which is to provide to you all every everything that an enterprise customer would need to be able to do AI on their unstructured data.

Steve Vendors, Software Research Team, Citi: Okay. That makes that makes sense. Maybe shifting gears in terms of, you know, the internal use of of AI at Box. Just how are you all leveraging AI internally? I think you’ve made a big pivot towards being an AI first company and and trying to to do that.

But what does that actually mean from a a day to day perspective, and what are kind of the core use cases that you’ve you’ve seen you’ve been utilizing?

Ben Koos, Chief Technology Officer, Box: Can talk from the the engineering side. Is it’s, of course, one of the early great use cases of AI just in general has been the ability for it to code. And so one of the things that we do is we we look to utilize wherever possible the the the coding assistant tools or the or the coding agents that can help you generate code ongoing. And and in addition to not just generating the code, but then also the other aspects of the coding ecosystem. For us, this has been a big great success because and then the majority of our of our engineers utilize this in some forms.

We use multiple tools, and we’re always experimenting with the latest. But we see productivity benefits, which then, for us, turns directly into providing more capabilities for our customers, being able to accelerate some of the road map items. So we definitely see that faster time to create product is is is we we we want more. We want it to be even faster. We we we want to we even wanna hire more people to even make it even faster so that we’re able to then continue down this path of being able to deliver more of this, like, long road map that us and companies like us have.

Steve Vendors, Software Research Team, Citi: Sure. Yeah.

Dylan Smith, Cofounder, CFO, Box: And then I would say, I mean, it’s really showing up across the company. And just to get a sense of, you know, the type of, you know, excitement and commitment we have to it around AI, you know, versus we are are making it mandatory. Everyone at Box is gonna be AI certified just on the basics, how to use it, lot of things like that. Just like we have, you know, security and data privacy training, this will be the second, you know, mandatory thing just because it’s that important that everyone deeply understands, you know, AI, how to use it, Box’s capabilities, etcetera. And we recently what the heck was two weeks ago, something like that?

A couple weeks ago, had our hackathon and and can speak from a you know, the person responsible for our g and a organization, we had dozens of submissions and people participating, which is, you know, not usual for a bunch of, you know, finance people and, you know, HR people to be, like, actually, you know, developing these applications and then pushing the limits of what bots can do, which I think speaks to both the accessibility as well as just the excitement and the groundswell that we’re seeing. And so I think a lot of those things. And then the way it just shows up in in other use cases, I mean, Ben spoke to the the coding side, but, you know, we have a data insights portal that everyone in our sales organization is is looking at to say, okay. Which of my customers might be the best candidates for, you know, this feature? Or, you know, who basically, who should I spending where should I be spending my time?

Ben Koos, Chief Technology Officer, Box: Mhmm.

Dylan Smith, Cofounder, CFO, Box: And so they go there. And based on all the different, you know, analytics that we have as well as running, you know, kind of some of these prebuilt queries that we’ve come up with, that really informs, you know, the best way to be spending, you know, their time and energy. And then, you know, we also kinda structure all the information as a service organization in BoxHubs just to make it that much easier for all employees to get access to information without necessarily having to, you know, write an email to, you know, our payroll alias or, you know, business operations or whatever else. And so, you know, really changing in a in a bunch of different ways. Those are just some examples, of the way that we’re using it on a daily basis.

Steve Vendors, Software Research Team, Citi: Okay. No. That’s great to, great to hear. I guess, any way to think about maybe the efficiencies or, like, the the margin gains that you’re seeing from from utilizing this? Or are you kind of reinvesting those savings back into the business and, in trying to, I guess, push faster on on the growth side?

Dylan Smith, Cofounder, CFO, Box: Yeah. So let’s say, you know, in the, you know, kind of current course speed in the first first for the foreseeable future, really more the latter, where we are seeing some some real gains, especially in certain parts of the organization, but really using it just to say, hey. How do we ship, you know, more products faster, you know, get more done, you know, keep this team that, you know, can now scale really effectively with the organization and just get more done, provide a deeper level of insights has been the approach, you know, currently. And then I guess these things build, you know, that may evolve. But right now, really just focused because of the massive opportunity in front of us.

You know, we’re much more focused on, you know, kinda reinvesting those savings, those efficiencies, to get the message, get more products in front of more customers faster.

Ben Koos, Chief Technology Officer, Box: Okay.

Steve Vendors, Software Research Team, Citi: Maybe going back to enterprise advanced, and I think you said number of deals doubled or roughly doubled quarter over quarter. I guess what’s the what use cases have you been seeing? Maybe what’s been surprising from the way customers are utilizing Box versus maybe what you were kind of expecting from it?

Ben Koos, Chief Technology Officer, Box: Yeah. So one of the things that we’ve been surprised about was how customers, how quickly they’ve gone from a the world of saying, I wonder if this is possible to actually trying it out, using it, putting it in in into production about and for and and and this is typically an area where you’d see, like, customers, like, didn’t know if it was possible beforehand. So certain things, like like, even even, like, ideas, like, we we have a a company we work with who’s they do loan origination. And so they had this this process that was complicated where they had to have the loan people verifying all of the documents to figure out how whether or not they were valid so they could then approve the loan. It turned out this was the number one thing that slowed down the loan processing in this in this example.

And so but they were they were skeptical because they had tried in the past to do things like be able to automate it because every time, you know, you can need, like, a utility bill or if you need, like, all these different things. Like, they came in different formats. Things changed. The scan was different. It was backwards.

It was upside down. And so when they were able to just apply the simplest of, like, data extraction to that to that to that that area immediately, then the AI could come back and say, like, you know, this is the data that can be verified in real time and by either by the the automatically or by the the loan originator. And they can either tell them, hey. This is not valid. It’s too old or whatever, or they’ll be able just have it then be ready to be approved.

And so stuff like that across the different industries, across different use cases, across the different business, these were all the things that people were saying, like, this is, a whole new era of me being able to apply this idea of of structures, unstructured data, and then using it to then perform, like, an efficiency. Oftentimes, it it it ends up with their customers are happier now because things went faster. And so this is seeing a company do this and then immediately start to replicate that over and over to different parts of the business. That has been something that we were building towards, but we were also surprised in some cases by how quickly they were able to, like, fully get that all working. And and, historically, this was something that would take a long time, but then if if this was something that they were able to get working fairly fairly quickly.

Steve Vendors, Software Research Team, Citi: Okay. That’s interesting. I guess as you think about some of those use cases, I mean, it seems like it’s either displacing something different than maybe what you were seeing in the past Yeah. And probably TAM expansive for you. Yeah.

How do you think about, you know, what is completely new greenfield for you versus

Ben Koos, Chief Technology Officer, Box: Yeah. I I talked to a customer who had I think they had a million contracts, and then somebody had to pose them a question, which was like, I which of these contracts had a clause? And then and so we we have ability to do that kind of stuff in Box where it’s it’s a it’s a byproduct of our of our AI and data extraction. And so we were talking to them, and and and we’re like, well, how did you do this before? And they’re like, well, before, I would have had to hire an RA of paralegals to come and and go to do this.

And we’re like, oh, what’s the RN? I’m like, well, I never would have done that. It would be way too expensive. Then we never would have contemplated even doing that. We would have had to do some other techniques to to guess the risk.

And so in this case, they were able to not they they were able to get a fundamentally new approach to to to this problem that this so it it was that was just novel to them. It was it was it was technology disruption in this particular area of of this this thing. Or we have another customer who was going through, and they were they were they were looking through these medical charts to see if there was a certain procedures there. They were all very valuable for them to get completely accurate. And then they having AI double check it to catch things that maybe somebody had missed along the way was extremely valuable to them.

And that was the kind of thing that was a net new way that they approached this particular kind of as opposed to before they it wouldn’t have made sense for them to, like like there there was no technology available for them to automate that kind of thing. Sure.

Steve Vendors, Software Research Team, Citi: I think one of the questions we tend to get from investors is just around, I guess, the competitive landscape. And, I guess, what kind of gives Box the right to win for, you know, capturing some of these, you know, agentic agentic use cases? Just how do you think about that, where it makes sense for for you all to kind of own that versus, you know, maybe or I guess, maybe what are investors kinda getting wrong about that that perception?

Ben Koos, Chief Technology Officer, Box: I think one of the ongoing questions and challenges is that at some point, like, AI is such a powerful technology that some people might say, like, I wonder if there’s going to be one AI agent or one AI technology that, like, rules them all from the perspective of just can do everything. But from our view, in practice, it’s actually quite hard to make sure that you’re doing safe and secure and compliant and high accuracy AI on something like unstructured data. And it’s different for your CRM data, and it’s different for your structured data, and it’s different for HR data. And so when we we we we spend an awful lot of time making this not only work, but work well. And so we see that there’s, like, a focus aspect of making sure that you not only have AI and AI applied to your these these enterprise grade platforms, but then also doing all the other things that we’ve done for twenty years, the things that people love about Box, making it secure, making it compliant, making sure that it has internal external collaboration, making sure that it has all of the full services suite.

So so for us, we see it as the AI can enhance the idea of what it means to be a good enterprise platform. And then that’s the key focus of many customers because they don’t wanna build all the stuff themselves. They don’t wanna have to invest in all the things it takes to make this work well. And similarly, if there’s there’s an element of trust and focus that goes in into this. And this is what our customers will tell us is I can’t I I’m I really want to make sure that all of the things that I’d use internally are enterprise grade and then also are I can bet on for the future as being able to keep up with the rapid pace of change.

Steve Vendors, Software Research Team, Citi: Don’t anything? Nope. Killed it. Yeah. Great answer.

Dylan Smith, Cofounder, CFO, Box: I got another to add.

Steve Vendors, Software Research Team, Citi: Yeah. I do wanna ask on you have a new CRO coming in, Jeff Newsom. I guess, what will he be focusing on? Maybe how is he gonna be different or targeting things differently than how Mark was before this?

Dylan Smith, Cofounder, CFO, Box: Yeah. So really coming in to to just scale, I don’t think double down in a lot of the, you know, parts of the strategy that have been working that we’ve called out as really strategic investment areas. And we think about the background he has just, you know, team at at massive, you know, larger scale, deep on the platform side, deep experience with enterprise customers, you know, really perfect fit for the next chapter. So not necessarily to, you know, kinda change anything about the strategy that we feel really good about. Although, obviously, he’s a very senior executive who’s gonna come in, you know, just this week and and start, you know, kinda diagnosing, seeing where he can add the most value and more about just, you know, how do we take everything that we’ve laid out and kinda supercharge it.

So really excited to have him on board and, you know, deeply appreciative to Mark, for everything that he did getting us up to this, this point.

Steve Vendors, Software Research Team, Citi: Yeah. We only got a couple of minutes left here. I wanna do one last scan of the room, see if there’s any any questions. I do wanna ask on the partner strategy. It seems like that’s been a a bigger point of focus kinda moving forward.

How do you view that, and maybe how do do some of the AI capabilities kinda fit into that strategy?

Dylan Smith, Cofounder, CFO, Box: Yeah. So I would say that, our ultimately, I think we have a much bigger opportunity now to work with partners, SIs, in particular, not because of, like, any, you know, stronger will that we have, but more because now they actually want to work with Box. Right? I think because they are seeing if you think about the types of, you know, kind of client engagements they have, the types of conversations they’re having, many of them, the existing ECM businesses, enterprise content management, businesses and portfolios that they have, I think the writing is is kind of on the wall. They’re hearing day in, day out from their clients that they need to rethink these things, how important AI is.

And so they’re looking for opportunities and and partners who can really help their con their their clients transform the way they work with content, and that’s where Box comes in. So AI is absolutely fundamental and the reason that we see such a big opportunity that we’re now, you know, kinda seeing this sort of demand from these partners. And it’s really just you know, to us, it’s about why it’s so important. And I know Ben did a really good job speaking to some of the use cases that are jumping out. Sure.

That’s absolutely critical to make these partnerships successful to be able to develop those repeatable those repeatable playbooks, use cases, and then work with partners to implement them so they can scale their practices and just get that message, that technology in front of as many, you know, kind of new customers as possible is a huge opportunity for us.

Steve Vendors, Software Research Team, Citi: I know we’re almost near time here, but I do wanna ask on just the ECM legacy landscape. Lot of lot of vendors out there that I don’t know how innovative they’ve they’ve been, but how do you kind of see that opportunity to go take share and maybe kinda where are we in terms of those those potential opportunities coming up?

Dylan Smith, Cofounder, CFO, Box: Yeah. So you have much bigger opportunity, again, I think, for similar reasons. Yeah. I mean, basically, the exact same dynamic of the inertia of, yeah, this is probably not the system I’m gonna be on. You know, we’ve been with them for twenty five years.

They haven’t innovated in the last twenty of those years. You know, is now, I think, AI is just a fundamental it’s pretty black and white. Like, if it’s sitting in an on premises system or you have fragmented solid data, you just cannot get the types of insights and and value out of AI that you can with Box. And so, you know, it’s a much bigger opportunity for us. Still pretty early days.

We are starting to win some of those deals, but it’s still the minority of the sales cycles that we’re in. We expect that to kinda continually evolve over time and for that to be a bigger and bigger part of our business just given the road map and even the capabilities today.

Steve Vendors, Software Research Team, Citi: Awesome. That’s that’s great to hear. I think we’re we’re out of time. So, Ben, Dylan, I thank you both for being here, and I wanna thank everybody in the room for for being here as well. So thanks so much.

Dylan Smith, Cofounder, CFO, Box: Thank you.

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