Box, Inc. (NYSE:BOX) Q4 2026 Earnings Call Transcript

Box, Inc. (NYSE:BOX) Q4 2026 Earnings Call Transcript March 4, 2026

Cynthia Hiponia: Good afternoon, and welcome to Box’s Fourth Quarter and Fiscal Year 2026 Earnings Call. I’m Cynthia Hiponia, Vice President, Investor Relations. On the call today, we have Aaron Levie, Box Co-Founder and CEO; Dylan Smith, Box Co-Founder and CFO. Following our prepared remarks, we will take your questions. Today’s call is being webcast and will also be available for replay on our Investor Relations website. Supplemental slides are now available on our website. On this call, we will be making forward-looking statements, including our first quarter and full fiscal year 2027 financial guidance and our expectations regarding our financial performance for fiscal ’27 and future periods, including gross margins, operating margins, operating leverage, future profitability, net retention rates, remaining performance obligations, revenue and billings, net tax benefits and the impact of foreign currency exchange rates, and our expectations regarding the size of our market opportunity; our planned investments, future product offerings and growth strategies; the timing and market adoption of and benefits from our new products, pricing models and partnerships; our ability to address enterprise challenges, enhance our product capabilities and deliver cost savings for our customers; the impact of the macro environment on our business and operating results; and our capital allocation strategies, including potential repurchase of our common stock.

These statements reflect our best judgment based on factors currently known to us, and actual events or results may differ materially. Please refer to our earnings press release filed today and the risk factors and documents we file with the SEC, including our most [ recent ] quarterly report on Form 10-Q for information on risks and uncertainties that may cause actual results to differ materially from statements made on this earnings call. These forward-looking statements are being made as of today, March 3, 2026, and we disclaim any obligation to update or revise them should they change or cease to be up-to-date. In addition, during today’s call, we will discuss non-GAAP financial measures. These non-GAAP financial measures should be considered in addition to and not as a substitute for or in isolation from our GAAP results.

You can find additional disclosures regarding these non-GAAP measures, including reconciliations with comparable GAAP results in our earnings press release and in the related supplemental slides, which can be found on the IR page of our website. Unless otherwise indicated, all references to financial measures are made on a non-GAAP basis. Finally, please see our earnings deck, again, posted on our IR website for a more detailed look at our Q1 and full year ’27 guidance. Thank you. With that, let me turn the call over to Aaron.

Aaron Levie: Thanks, Cynthia, and thank you all for joining the call today. We delivered strong Q4 operating results, reflecting continued growth in customer demand for Box AI and the success of our Enterprise Advanced offering. We achieved revenue of $306 million, up 9% year-over-year or 8% in constant currency and Q4 EPS of $0.49, above our guidance. In fiscal 2026, we drove revenue of $1.18 billion, up 8% year-over-year, with operating margins of 28%. It was a defining year for Box as we executed on the launch of Enterprise Advanced, which brings together our most powerful capabilities around intelligent workflow automation, advanced AI and secure content management to enterprises. Enterprise Advanced customers have reached 10% of revenue, and we’re incredibly excited about this early traction and continued momentum.

Examples of Enterprise Advanced customer wins include a leading biotech company uses Box to manage large volumes of commercial documents but currently relies on manual searches to find key information. By upgrading from Enterprise Plus to Enterprise Advanced, the company will use AI-powered data extraction and integrated apps to surface critical commercial data directly from documents. Next, a leading global robotics company uses Box as the core platform for its revenue operations and content workflows. The company upgraded from E Plus to Enterprise Advanced to streamline quote creation and approvals with Box Doc Gen, Box Sign and Box Apps to increase throughput and reduce errors. They also plan to apply metadata extraction and OCR to financial and legal documents to automate data capture and better manage contractual risk.

To understand what’s driving the momentum with Box, it’s important to think about the criticality of enterprise content when it comes to driving transformation with AI. Nearly every enterprise leader that I talk to today is looking to transform how their company operates with AI. They’re looking to accelerate tasks across their organizations, ranging from reviewing legal contracts and doing financial analysis to accelerating pharma research and spreading expertise across their organization. They quickly find that for AI agents to be effective in a workflow, agents need critical context about their business. They need to understand the company’s product road map, marketing strategy, HR policies, internal best practices, planning insights, strategy decisions and whatever else makes that business unique.

Much of that unique context lives inside of enterprise content, ranging from contracts and financial documents to research documents and marketing assets, all housed inside of PDFs, documents, media assets, collateral, spreadsheets and markdown files and more. All of this enterprise content is the digital brain of an organization, containing the most important insights precisely because of their unstructured nature. Files provide a universal way to create, capture and share information between systems and people, which is why the growth of content continues to explode. Yet the vast majority of this data, which makes up 90% of corporate data has been underutilized until today. Now AI agents can finally help us tap into this critical business information and use it to accelerate knowledge work that previously could never have been automated.

As we prepare for a world where there will be a 100-fold more agents inside of an enterprise than people, we will equally see incredible growth in unstructured data. Files are quite simply the native unit of work for agents. Agents use files to keep track of their work. They leverage files as context about the tasks that they’re doing and use files to share back and forth with their human counterparts. And as AI agents help us augment all of our work across industries like pharma or financial services, legal and healthcare or the public sector, these agents will need the same level of security, data governance, auditability, logging and access controls that we’ve required for people in the enterprise. As we’ve seen with the growth of products like OpenClaw or the launch of Claude Cowork and others, agents may spin up countless sessions and will need their own secure file systems and sandboxes while also being able to easily collaborate securely with other people and agents.

Thus, to have an effective AI agent strategy, companies fundamentally need a content strategy. They need a secure platform to manage critical content and ensure it can connect to all of their people, agents and applications. This is what we’re building at Box with our Intelligent Content Management Platform. And FY ’26 was another fantastic year of product innovation and momentum to ensure that we stay ahead of the market and power our customers’ most critical content workflows with AI. Just in the fourth quarter, we announced the general availability of Box Extract, enabling enterprises to intelligently and securely pull the most valuable information from content and save it as metadata in Box, all powered by leading AI models. With Box Extract, companies can turn their documents into data, pulling out the structured data from contracts, invoices, marketing assets, research, financial documents and any other file type to automate workflows or glean critical insights in their business.

In Q4, we also rolled out Box Shield Pro, a powerful new add-on that expands on existing Box Shield content protection and leverages agentic AI to bring new levels of scale, speed and automation to advanced security controls. We are also incredibly proud to have served as an early launch partner for Anthropic’s Claude Opus 4.5 and Opus 4.6 releases, Google’s Gemini 3.0 Flash and OpenAI’s GPT-5.2, all available in the Box AI Studio. These are many of the foundational elements in our Intelligent Content Management Platform that we delivered in FY ’26. Now looking forward, in FY ’27, we will be delivering the next generation of AI agent features within Box, enabling AI agents that can do more long-running tasks and advanced work on enterprise information.

Soon, you’ll be able to give AI agents complete projects, and they will go off and work through your enterprise information to complete those tasks, powering everything from writing out complex RFPs to analyzing your contracts and generating a new one with the most relevant clauses. We are also building the most advanced AI-powered workflow automation capabilities with enterprise content. We will keep rapidly enhancing Box Extract to support even more complex document processing use cases. And with Box Automate, which we will launch in the first half of this year, customers will be able to combine human and agent-powered workflows to automate any content business process in an enterprise. And combined with new features in Box Apps, we will deliver full no-code business workflows from contract management to digital asset management and more.

Throughout FY ’27, we will continue to advance our functionality across Box Shield to enable more intelligent threat prevention and data classification with new Box Zones sites for enhanced data residency, Box Governance to power deeper lifecycle management features and new functionality to help improve the security of AI agents in Box. Finally, this is going to be a major year for the Box Platform APIs. Catalyzed by the rise of AI, enterprises will need to further centralize their enterprise content and connect a single source of truth of content to their people, agents and applications. The same contract that an agent produces, a user may want to review inside of an end-user application and may want to show up inside of Salesforce or a custom app.

The same is true for every other type of enterprise content from marketing assets to financial documents. To support these growing AI use cases, we’re making it as easy and secure as ever to leverage Box as a platform to integrate content across the entire AI stack like Claude Cowork, Copilot, IBM watsonx, ChatGPT or custom agents that our customers build by leveraging Box’s APIs, MCP server and CLI support. We’re incredibly excited about this new array of use cases for the Box Platform to be used as the file system for agents. And we will monetize this through either end-user seats that interact with these agents or API and AI unit consumption when our platform is connected to these agents in a headless fashion. So we are covered either way.

Now turning to go-to-market. As I’ve noted, we are incredibly excited about the momentum we’re seeing with Enterprise Advanced. Across industries like financial services, legal, life sciences and in the public sector, including other key industries, we’re seeing growing momentum for enterprises to adopt Box’s most powerful set of capabilities with Enterprise Advanced customers now reaching 10% of revenue and driving an acceleration in our top line metrics. Our partner business also remains a critical part of our strategy as we deliver more advanced solutions for customers. And in Q4, we saw continued momentum with key partners, a large government regulator that selected Box Enterprise Advanced as the content layer for regulatory case management.

Working with a global systems integrator, Box replaced a legacy system, enabling secure document intake, high-volume review and AI-assisted classification integrated into core case systems, positioning Box as a foundational platform for the organization. Next, a global insurance organization upgraded to Enterprise Advanced as part of a legacy ECM modernization led by our partner, DataBank. Box AI now processes insurance policies and related documents at scale, extracting key data from large volumes of policies and endorsements to support underwriting and quoting, reduce manual review and improve operational efficiency. Given the strong results we saw in FY ’26 and especially through the tail end of the year, in FY ’27, we believe it’s critical to continue to strategically invest to build on this momentum and ensure we’re capturing this market opportunity.

We will continue to invest in our critical growth verticals with go-to-market capacity and marketing efforts. We’re bringing the full power of Box’s Enterprise Advanced plan to customers through Box’s solution offerings in key lines of business and industries. We’re accelerating growth in large enterprises by deepening partnerships with major SIs like Deloitte, Slalom, TCS, DataBank and more. We’re driving growth with key cloud marketplaces like GCP and AWS and much more. You will hear more about these go-to-market initiatives at our Financial Analyst Day in 2 weeks. As we enter a new era of work that is defined by AI agents, we are confident in the power that enterprise content plays in powering an agentic strategy in organizations and that enterprises will need a secure platform to connect their most important enterprise information to their people, agents and applications.

At Box, our opportunity has never been larger to transform how companies work with their content. We are entering FY ’27 with the strongest momentum I’ve ever seen as we become the platform that powers intelligent content workflows and automation in the enterprise. With that, I’ll hand it over to Dylan.

Dylan Smith: Thanks, Aaron. Good afternoon, everyone. Q4 capped off a year of strong execution against the 3 financial priorities we outlined heading into the year. First, we set the stage to accelerate top line growth by investing in key go-to-market initiatives and enhancing the AI capabilities of our Intelligent Content Management Platform. Second, we generated efficiencies across the business by advancing our AI-first efforts and workforce location strategy. Finally, we executed on our disciplined capital allocation strategy, reducing basic shares outstanding by more than 3 million over the past year. In FY ’26, we delivered revenue of $1.18 billion, up 8% year-over-year and up 7% in constant currency. We drove an acceleration in RPO growth to 17% year-over-year or 16% in constant currency.

Operating margin came in at 28.3%, up 50 basis points year-over-year and up 40 basis points in constant currency. Finally, in FY ’26, we generated record free cash flow of $313 million, up 3% year-over-year. Turning to Q4. We closed the year with very strong results, exceeding our guidance across all metrics. We delivered Q4 revenue of $306 million, up 9% year-over-year and up 8% in constant currency. This represents our third sequential quarter of accelerating revenue growth driven by strong AI and Enterprise Advanced momentum. Customers paying us at least $100,000 annually, grew 9% year-over-year. After launching Enterprise Advanced as our highest tier suite just a year ago, Enterprise Advanced customers already account for 10% of our revenue.

The intelligent workflow automation, advanced AI and secure content management that this plan offers are clearly resonating in the market. Over the past year, price per seat for Enterprise Advanced customers have commanded an average pricing uplift of 30% to 40% over Enterprise Plus at the high end of the 20% to 40% uplift we had initially anticipated. Going forward, we expect this 30% to 40% uplift to continue. Total Suites customers now account for 66% of our revenue, an increase from 60% a year ago. We ended Q4 with remaining performance obligations or RPO, of $1.7 billion, representing 17% year-over-year growth or 16% in constant currency and providing us with greater visibility into future revenue. Short-term RPO grew 12% year-over-year, both as reported and in constant currency.

Our strong RPO growth continues to benefit both from longer contract durations and from mid-contract upgrades to Enterprise Advanced. We expect to recognize roughly 55% of our RPO over the next 12 months. Q4 billings of $420 million, were up 5% year-over-year and up 4% in constant currency, ahead of our expectations of low single-digit billings growth. This outperformance was driven primarily by strong Q4 bookings. We ended Q4 with a net retention rate of 104%, up from 102% in the year ago period, driven by continued improvements in both pricing and net seat expansion trends. We expect our net retention rate to remain at 104% in Q1 and to land in the range of 104% to 105% at the end of FY ’27. Q4’s gross margin was 82.3%, exceeding our guidance of 82%.

This represents an increase of 130 basis points year-over-year. In Q4, we continued to drive cost discipline across the business, delivering record Q4 operating income of $94 million and operating margin of 30.6%, exceeding our guidance of 30%. In Q4, we delivered EPS of $0.49, well above our guidance of $0.33. This includes the benefit from several tax items, which reduces our effective tax rate in FY ’26 and on a go-forward basis. Excluding these tax benefits, EPS would have exceeded our guidance by $0.02. I’ll now turn to our cash flow and balance sheet. In Q4, we generated free cash flow of $98 million and cash flow from operations of $110 million, up 7% and 8% year-over-year, respectively. We ended Q4 with $480 million in cash, cash equivalents, restricted cash and short-term investments.

Our balance sheet reflects the cash settlement of debt principal related to our $205 million of 2021 convertible notes that matured on January 15, 2026. In Q4, we repurchased 4.4 million shares for approximately $126 million. For the full year of FY ’26, we repurchased approximately 9.7 million shares for approximately $293 million, representing more than 90% of FY ’26 free cash flow generation. As of January 31, 2026, we had approximately $59 million of remaining buyback capacity under our current share repurchase plan. With that, let me now turn to our Q1 and FY ’27 guidance. Please note that approximately 40% of our revenue is generated outside of the U.S. with approximately 65% of this international revenue coming from Japan. Note that our FY ’27 guidance reflects a lower expected GAAP and non-GAAP tax rate benefiting EPS.

For the first quarter of fiscal 2027, we expect Q1 revenue to be approximately $304 million, representing approximately 10% year-over-year growth or 9% in constant currency. We anticipate our Q1 billings growth to land in the low single digits, which includes an expected headwind from FX of approximately 530 basis points. We expect Q1 gross margin to be approximately 81.5%. We anticipate our Q1 operating margin to be approximately 27.5%, up 220 basis points year-over-year. We expect Q1 EPS to be approximately $0.36. Weighted average diluted shares are expected to be approximately 141 million. For the full fiscal year ending January 31, 2027, we expect our full year revenue to be approximately $1.275 billion, representing 8% year-over-year growth or 9% in constant currency.

We expect our FY ’27 billings growth rate to be roughly in line with revenue growth. This includes an expected headwind of approximately 100 basis points from FX. We expect FY ’27 gross margin to be approximately 81.5%. We expect our FY ’27 operating margin to be approximately 28% or 28.5% in constant currency. As we have discussed previously, given the momentum and demand we are seeing for Box AI and Enterprise Advanced, we are continuing to invest in strategic go-to-market initiatives to ensure we can reach customers at this critical technology juncture. We will continue to drive operating efficiency through cost discipline, AI-driven efficiencies and our workforce location strategy, and we remain committed to delivering significant margin expansion over the next few years.

As it relates to FY ’27 expense and margin seasonality, please note that our annual customer conference, BoxWorks, will take place in Q4. This will shift approximately $3 million in expenses from Q3 into Q4 as compared to FY ’26. We expect FY ’27 EPS of approximately $1.55 or $1.58 in constant currency. Weighted average diluted shares are expected to be approximately 141 million. In the era of AI agents, Box is powering the full lifecycle of content in a single platform with native enterprise-grade security and AI capabilities. Our strong results in fiscal 2026 demonstrate the success of this strategy, including an acceleration in RPO growth and an improvement in our net retention rate. In FY ’27, we will continue to invest in our robust product road map and strategic go-to-market initiatives, delivering accelerating revenue growth and higher operating profit.

We look forward to providing more details at our Financial Analyst Day later this month. With that, Aaron and I will be happy to take your questions. Operator?

Q&A Session

Operator: [Operator Instructions] We’ll take the first question from Steven Enders, Citi.

Steven Enders: Okay, great. I guess I just want to start on the opportunity for threat that you’re maybe seeing from AI. And just how do you think about how the changes in the GenAI landscape, maybe impacts the content layer and what this looks like moving forward with agentic AI?

Aaron Levie: Yes. So — thanks for the question. So we’re — as you can tell on the kind of remarks, we’re unbelievably excited around the role that content plays in any kind of agentic system. And so there’s a few different ways that this will show up. The first is we actually expect to see a major rise of software in general being generated through AI. So if you just imagine that there’s a dramatic increase in software that enterprises build, I don’t 100% agree with the thesis that they’ll build kind of existing in internal systems, but kind of almost independent of what you believe, there’s going to be vastly more software produced in the future, sometimes bespoke software, sometimes just more companies. And for really any kind of enterprise use case, the second that you need some form of unstructured data inside that software.

It could be a contract management system. It could be a pharma workflow. It could be a financial services onboarding system. It could be a client portal. All of those systems are going to need a secure place to be able to store the unstructured data that goes into that system. So the first piece is more software is just good for us because all of that software needs to eventually probably touch some type of unstructured data in an enterprise context. But probably the bigger play is as you have more and more agents doing work for us, and we’ve seen a few examples of agents kind of break through recently, the Claude Cowork agent, OpenClaw agent, these are great examples of agents that are doing kind of general-purpose knowledge work. And if you imagine the general-purpose knowledge work that most people do through their day, if you’re a lawyer, you’re looking at contracts; if you’re in banking, you’re looking at lots of financial reports; if you’re in pharma, you’re looking at lots of both research and kind of information coming in from lab tests.

All of that is unstructured data. To now replace a person with an agent in that example, and agents will need that exact same data to work with. They’re going to need the right contract to look at. They’re going to need the pharma research to touch. They’re going to need to be able to comb through financial information. And the enterprise is going to want a secure way to govern those workflows and govern the data that goes into them. If you imagine one of the kind of increasing kind of architectures emerging is these agents that have their own computers that they get to work with. Well, the computer will, to some degree, be stateless at some point, like it might disappear in a week or a month or a year from now. But what can’t disappear is the data that, that agent worked on.

If you’re in a regulated industry, you need to govern that data. You need to be able to have audit logs, you need to be able to have a place where you store and can go do discovery on that information. So the part that actually has to keep state forever up to the point that the customer cares about working with the data is your — is the information that, that agent worked with. And so we really imagine a world where, let’s say, you have 10 or 100 or 1,000x more agents than an enterprise, than people even, they will need to do work on this unstructured information. And importantly, when they do that work, oftentimes, an end user will actually need to see the results of that work or go back and forth with the agent. So fundamentally, there needs to be some type of shared file system for them to be able to do that work.

And that’s why we are in a very strong position as a platform for both agents and applications, both of which will grow due to AI to be able to manage that content. So that’s our overall take. We’re seeing this kind of thesis continue to kind of play out in the market. You’re going to see a number of developer tools launching over the coming days and weeks that will further support developers that are building on this, but this is directly what we’re seeing already from our customer base and developer base. And so we’re just excited to continue to make that as frictionless as possible and continue to kind of pour fuel on that fire.

Steven Enders: Okay. No, that’s great to hear. Maybe just on the Enterprise Advanced success so far. I think it’s good to see at a 10% of rev already so quickly. Just maybe kind of what are your expectations for what that will look like for — or where that is going to end up in fiscal ’27, like what do you have embedded in the guide? And just yes, how are you kind of viewing the, I guess, seat uplift so far from customers that have taken on the Enterprise Advanced tier?

Dylan Smith: Yes. So I would say certainly very excited about the momentum that we’re seeing in Enterprise Advanced and just scratching the surface of the opportunity. We do expect to see that continue to drive a lot of the growth for — in the year ahead. And we’ll give more details in terms of what we’re thinking and expecting around that momentum, not just for next year, but in the coming years in just a few weeks at our Financial Analyst Day. And then in terms of the type of impact that we’re seeing from customers, we mentioned we’ve been really pleased with just how much the value of these newer capabilities are resonating with customers. So we have been seeing pricing uplifts even just from Enterprise Plus to Enterprise Advanced in that 30% to 40% range alongside a lot of the use cases that Enterprise Advanced is enabling being a catalyst and one of the reasons that we’re seeing healthy dynamics around net seat expansion as well.

So a lot of different benefits in terms of not just the top line growth, but the underlying customer economics and stickiness that is driving, which is one of the reasons that we’re so excited about the path forward and the growth opportunity that creates.

Operator: The next question is from Rishi Jaluria from RBC.

Rishi Jaluria: Wonderful. Maybe I want to start, Aaron, in your prepared remarks, you talked a lot about many of the verticals, especially regulated verticals where you’re helping enable a lot of these AI use cases. Can you talk a little bit about kind of the state of enterprise AI adoption and the willingness to take AI from pilot and proof-of-concept into more widespread production and what you’re seeing specifically out of more regulated industries? And then I’ve got a quick follow-up.

Aaron Levie: Yes. So great question. Obviously, I think right now, you have a bit of a tale of 2 cities with AI adoption. You have a lot of these sort of deep engineering use cases, AI coding, et cetera, that have obviously taken off because the very users of these platforms are technical, they can adopt their own tools. The communities are pretty wired together. And then you have sort of, let’s say, the rest of knowledge work. And in the rest of knowledge work, I think what it often takes is applied use cases with AI that can actually bring real transformation to the workflow. There’s — I think at this point, it’s safe to say every knowledge worker has some degree of access to a chat tool either personally or professionally.

And so general purpose, I’m asking the Internet or some systems questions is I think increasingly growing. The real interesting part is can I actually go and automate and accelerate and augment my workflows in an organization. So with Enterprise Advanced, this is really an applied system for how do you bring AI and AI agents to enterprise content workflows. The biggest one that has taken off thus far is really data extraction. So you have a large repository of contracts or invoices or financial data and you want to be able to extract key details from that and then kick off some workflow or pump that data into a data lake and then query it or query it within Box. We are seeing a lot of growth in those use cases right now. There’s — as I kind of mentioned on the call, we have a new product called Box Automate that is coming.

We shared this with customers at the tail end of last year. Box Automate is sort of one click above data extraction, which is I might want to sort of design an entire workflow, a client onboarding process, a contract process, a digital asset review process. And at multiple steps in that process, I want agents to do certain amounts of work dealing with content. And so now we move from really kind of task-specific applied use cases to really increasingly more of the full business process with both agents and people kind of showing up at the relevant point. But we are 100% focused on applied AI use cases in an organization. And that’s, I think, why we’re seeing healthy adoption of both Enterprise Advanced as well as in regulated industries, maybe ones where it wouldn’t have been maybe initially intuitive that they would be able to adopt so quickly.

It’s because these are applied use cases and our platform is purpose-built for security, compliance, data governance issues that they’re going to run into with AI.

Rishi Jaluria: Yes, got it. That’s really helpful. And then, Dylan, for you, just maybe a bit more of a housekeeping. But as you talked about your Q1 billings guide, you talked about FX as a — correct me if I’m wrong, 530 basis point headwind to growth. That seems a little bit high, especially in light of the rest of your kind of as-reported and constant currency growth rates. Can you expand a little bit on just kind of the math behind that and why the headwind from FX is so extreme in Q1?

Dylan Smith: Yes. So if you look back to a year ago, there was just a pretty significant movement in the U.S. dollar to yen exchange rate in that period. That’s one of the reasons, also if you look at our Q1 results from this past year in FY ’26 was really the reverse story and was one of the contributing factors to extremely strong billings growth. So it really is a unique to just the movement that we saw in that exchange rate a year ago. And for the year, much more normalized. So you did hear that right in terms of the 530 basis point headwind for Q1. For the year, we expect FX to be a roughly 100 basis point headwind to our billings growth rate. So definitely a pretty unusual dynamic just in the first quarter based on those rate movements a year ago.

Operator: We’ll take the next question from Brian Peterson, Raymond James.

Brian Peterson: Congrats on a really strong quarter. Dylan, I’d love to understand as you went through the quarter, any help on how you’re thinking about linearity demand? And any perspective from a geo in terms of Japan, North America, anything you can call out there?

Dylan Smith: Do you mean linearity in terms of what we saw within the fourth quarter?

Brian Peterson: Yes, 2 parts, sorry. Yes, for the fourth quarter, but 2 parts. I would love to understand just the general linearity as you went through the quarter and anything you would call out in terms of strength by geo?

Dylan Smith: Yes. So linearity was really positive, both because I think the team has done a really nice job in terms of driving that and not letting everything sit to the last days or weeks of the quarter, which also gives us more cycles to bring in some of those deals, drive some of that upside, and that was certainly a contributing factor to the underlying bookings strength and outperformance that we saw. And at the same time, which also touches on your second question, we have seen a nice strength and really good momentum in the performance of our commercial business. So SMB, mid-market. And that is just inherently more linear typically than enterprise within the quarter. And so seeing that strength also contributed to the strong linearity that we saw.

And then on top of those segments, again, Japan was a strong performer for us. And then we have seen some of the regions in the U.S. really starting to hit their stride as well. But no really unusual trends in terms of what we’ve seen over the past year other than just continued and additional strength on the commercial side, but everything, just a higher overall level of performance across those different segments.

Brian Peterson: Got it. And Aaron, maybe one for you. You talked about some of the different end markets that might be coming to Enterprise Advanced. I’d love to maybe understand how do you think about the evolution of that ramp in terms of selling into the customer base, but also maybe coming in with net new to Enterprise Advanced. And I don’t know if you guys can share of that 10%, how many came in kind of migrating from the existing base or net new, but would love to unpack that a bit.

Aaron Levie: Yes. I mean Enterprise Advanced sets us up very nicely for net new conversations because it’s getting you into a workflow conversation and in particularly an agentic workflow conversation. So you could have — never had run into a use case that we previously would have been able to solve for you with Box, and we can come into your organization and instantly have a conversation around being able to start to drive automation in some process that, again, maybe 2 years ago, we’d have no ability to play in. So this could be a contract automation process, a client onboarding workflow where we’re doing more of the intelligence. It could be in a healthcare data processing workflow. We have customers where we’ve had conversations where they want to rip and replace a legacy ECM system and maybe they were starting to kind of figure out can they migrate that to the cloud or build out their own capability and then all of a sudden, they kind of see the full depth of data governance, security compliance that they’re going to need, especially in a world of agents and decide that actually Box is going to be the superior, more future-proof solution for that.

So in all of these examples, Enterprise Advanced is kind of putting together a package between workflow, no-code apps, AI agents and sort of metadata extraction, all backed by a level of data security with Shield Pro and other capabilities that allow you to move your mission-critical work and content to Box. So we’re seeing that again in a wide range of new logos as well as existing customer upsells.

Operator: Matt Bullock from Bank of America has the next question.

Matthew Bullock: Great. I wanted to ask about net revenue retention expectations. It looks like it’s going to improve modestly in fiscal ’27. But I’d be curious to hear if you could unpack the components of that across pricing per seat benefits, net seat expansion. And then it sounds like APIs and units are going to start coming into the model as well this year. I presume only marginally, but could that be something like 50 basis points of tailwinds to NRR this year as we progress towards that longer-term target of 1 to 2 points of growth from platform?

Dylan Smith: Yes. So in terms of drivers of the net retention rate, yes, both for the coming year and then the additional improvement that we expect to deliver in the coming years, we would expect to see that coming from the combination of slightly higher impact from pricing uplifts and continued momentum with net seat expansion being more of a driver, which is a change from looking back to a year ago, that was more so being driven by the pricing side, but we’re now seeing and expecting to see more kind of healthy mix between the 2 with no expected change on the full churn rate on that side. And then in terms of the overall platform business, yes, we could see that certainly contributing to the net retention equation and part of the overall pricing dynamic and that uplift that we’d see there. But to your point, at least for the coming year, I don’t expect that to be a material driver of any change in the net retention rate.

Matthew Bullock: Got it. Really helpful. And then just one quick follow-up, if I could. I wanted to ask about Enterprise Advanced pricing uplift. You’ve seen consistent 30% to 40% uplift relative to Plus, already at 10% revenue mix here, and you’re innovating quite a bit. So my question is, do you foresee the pricing uplift for Enterprise Advanced potentially ticking above that 40% kind of baseline that it’s tracked at so far over the next couple of years as you continue to add value?

Dylan Smith: I would say you probably wouldn’t set the expectation to see that move up too much in terms of the core upgrade from Enterprise Plus to Enterprise Advanced. Certainly, what we’re driving is to deliver more of an overall contract value increase when customers make that move through the combination of just increasingly monetizing those platform components that we’ve been talking about as well as and kind of in conjunction with opening up the new use cases to drive more seats because that 30% to 40% uplift is really specific to the apples-to-apples, hey, you have X seats and now they’re moving to Enterprise Advanced, what’s the price per seat? Don’t expect to see as much of the upside from the success and innovation of Enterprise Advanced show up in that specific metric, but more in the overall contract value through those other kind of related levers.

Operator: The next question will come from Lucky Schreiner, D.A. Davidson.

Lucky Schreiner: Maybe a unique one. But over the course of the year, did you notice any difference in behavior between the early adopters of Enterprise Advanced versus customers that maybe adopted in 4Q, just given the vast improvements in the models that we’ve seen over the course of 2025? And any way we should maybe be thinking about that for 2026?

Aaron Levie: And when you say the models, i.e., AI models, right?

Lucky Schreiner: Correct. Yes, and some of the agentic abilities that you guys can provide on the platform.

Aaron Levie: It’s a great question in terms of how you’re characterizing it. I don’t know that I could pinpoint — I don’t know that I would pinpoint any specific thing, but the general trend that is sort of embedded in that question is actually correct, which is, if I go back, let’s say, 14 months ago when Enterprise Advanced initially kind of hit the scene in conversations, there were still lots of use cases in mission-critical workflows where you would have to do a lot of work to make sure that the data extraction was as accurate as you needed. And as each model family kind of has its next upgrade in its lineage, we tend to see anywhere from single-digit to double-digit percentage points in accuracy and kind of quality of the models on unstructured data.

That’s just universally a good thing for us because it means there’s even more swaths of use cases that we can go after and say, “Hey, we can go and extract critical metadata from those even more complex contracts or financial documents or assets that you have.” So I’d say the general trajectory, again, without pinpointing Q4 specifically is that customers will get more and more comfortable automating more and more of these content workflows as these models continue to improve, and we’re already seeing that trajectory take off with our conversations. So it’s a fantastic, just like universally good trend for us that we’re going to keep riding.

Lucky Schreiner: Awesome. That makes a lot of sense. Then on the Enterprise Advanced customers, congrats on the 10% of revenue. That’s impressive. If I look at the percent of revenue coming from Suites, that implies nearly all of the revenue came from upgrades from Enterprise Plus customers to Enterprise Advanced, which makes a lot of sense. But is there anything about the non-enterprise Plus customers that might be slower to upgrade to the higher tiers? And maybe how are you thinking about that opportunity?

Dylan Smith: Yes. I think that’s right that the majority of the Enterprise Advanced customers who have upgraded were coming from existing customer base and more likely than not coming from Enterprise Plus and I wouldn’t say there’s anything unique about the types of companies, whether it’s company size or any unique dynamics by the actual company. But just from a use case point of view, certainly, those customers who would be more already bought into the value of Box’s platform offerings and who have a lot of the use cases that would benefit the most from Enterprise Advanced capabilities, as you’d expect and especially from an early adopter stage, there’s pretty strong correlation with those customers who are already on Enterprise Plus, which was previously our highest tier offering.

So that’s really, I would say, a function of timing and the specific customers who are almost — it’s almost a self-selecting if you’re one of the early adopters of Enterprise Advanced, more likely than not, you’re on Enterprise Plus. But we see a huge opportunity for those non-enterprise Plus customers just given the types of use cases, the types of conversations we’re having and the potential there as well. So more of a timing thing than anything else is what we’d point to.

Lucky Schreiner: Got it. Appreciate the color there and congrats on a record year.

Operator: Next up is Jason Ader from William Blair.

Jason Ader: Aaron, I wanted to give you the opportunity to address a couple of the bear narratives out there for SaaS. First is the fear that SaaS apps become back-end databases on which an intelligence layer like Claude sits and captures much of the value. And then second, the seat-based models face structural challenges because of knowledge worker job displacement.

Aaron Levie: Yes. So — and this might sound like a little bit of the first question, but we’re — I don’t — the — there’s almost nothing in that, that is bad for Box, I guess, ironically. I don’t necessarily totally believe some of those components, especially the kind of future of knowledge work and the volume of that. I think that most people are going to use AI to accelerate their work and augment their work — kind of workforces. But what we are building as a platform is when you have critical information, contracts, research data, marketing assets, HR files, financial documents, all of that content is going to need to be shared between agents, people and systems or applications. There’s simply no way around it. You can’t have 2 agents that are maybe trying to coordinate a task for a lawyer be working off of 2 different sets of contracts.

They fundamentally would need the same access to data. So you need a shared file system. That shared file system has to be accessible to your agents and your people. And maybe the ratio changes over time of different kind of roles in the economy in different parts. But no matter what, there’ll be some human in the loop at some part. So then the data has to be shared with a person. And ultimately, that company is going to need to have the same governance, the same security, the same controls on that information as they did with people. So imagine that you’re a large bank and your bank is processing escrow documents or loan kind of files from a client. That data will have to be governed just like when people went and review those documents. They’re going to need to sit around for 10 years in some cases.

You’re going to need to see the exact traces of what the agent did and what decisions they made in that workflow. Well, all of that is unstructured data. It will all become content, whether it’s markdown files or PDFs or word documents, that’s all enterprise content that has to be secured and governed and controlled and protected in the exact same way that we’ve always been doing it because files are the sort of this natural medium by which people and agents share information. So I would just say that our platform story becomes really increasingly the core of how we can power both, again, agents, applications and people. And so in a scenario where you have maybe a seat decline because agents have grown so much, which, let’s say, let’s positive is some potential scenario, the agents that are growing on the other end of that still need a place to then store their documents and their enterprise content.

And then I don’t know if you heard this answer, but if you have more and more, let’s call it, vibe-coded software or SaaS, those systems still also need repositories for being able to secure and protect and govern the content that gets generated. And we already have a business model for that. That’s our platform business model. So we can grow either through platform consumption or we grow through continued seat adoption, both of which we’re seeing right now in the business. And so I think we’re kind of protected on both dimensions there. And it’s really, again, because of the critical nature of how companies need to manage this information. You need data governance, you need data security, you need compliance, you need data residency. None of that can go away in a world of agents.

And in fact, probably it becomes more important in a world of agents because if you have 100x more agents running around doing loan processes than you had people, the chance of a mistake happening, the risks of an agent revealing the wrong piece of information to a client goes up exponentially. Those agents don’t have context for what they should or shouldn’t be sharing. It’s very easy to prompt inject those agents. There’s a lot of risks that can emerge. So you need to give them isolated environments, but those are isolated environments that need some degree of controls and mechanisms and in many cases, kind of collaboration with the user. So that’s what we’re powering. That’s what our platform has always done for humans and for applications, and now we’re adding agents into the mix.

And why we see this as, again, just universally a good thing. So I think maybe the one thing where we sit around and we look at Claude Cowork and we see OpenClaw, like we are just incredibly happy for the existence of these things. We were a Claude Cowork partner on their plug-ins like the more knowledge work that happens agentically, it’s all goodness for us. It just creates a tremendous amount of data that needs to get stored somewhere securely.

Jason Ader: Okay. Awesome. And then — sorry, just a quick follow-up. Could you just talk about the API monetization opportunity in relation to that answer that you just gave?

Aaron Levie: Yes. So there’s a couple of parts of the API monetization. So there’s a pure volume-based mechanic. So if you were to use Box tomorrow and you deployed a fleet of agents, and they were all running around, you had 100x more agents than people in your organization. And each of those agents, you would probably want to have a Box account of some sort. You can either have a headless Box account, you have a regular Box account you choose. And you’re going to want those agents to be writing, reading, storing data, sharing with other people. And if it’s done in a headless capacity via our APIs, we have a platform business model, which is consumption-oriented. And so you’ll just pay for the API calls that go into that. Then if you use our direct intelligence layer, which taps into Claude and ChatGPT — and GPT-5.2 or any new model, Gemini 3, then we also monetize that through AI units.

And so we’ve got dual consumption monetization levers that will basically grow somewhat correlated with just the growth of AI agents in the economy, assuming our customers are deploying those capabilities. And then, of course, seats still — like we’re still relatively early on total seat penetration. And so there will actually be a scenario where seats will grow because of agent growth because we will then tap into use cases that we didn’t previously solve where there still will be a human in the loop working with agents, but now we’re able to capture more of those use cases than we would have for that particular knowledge worker 5 years ago. And so there’s sort of just — it’s multifaceted sort of growth levers. But it’s like the simple — like if you just had to like — be like, okay, what’s the simple concept here?

It’s that agents use files. That is their core thing that they work with. Every time you hear any viral thing online about an agent, storing off its work, creating a memory, having documentation, having a specification to work off of, it’s always a file. And so that — those files are going to get generated. They’re going to need to get stored somewhere. They’re going to need to be governed. They’re going to be shared with people. And so that is just the general sort of tailwind that our platform is going to be able to support.

Operator: And Seth Gilbert from UBS has the next question.

Seth Gilbert: I guess for the first one, you had the best greater than $100,000 customer growth in about 11 quarters. So the question is on the customer adds front. Can you help us expand on where you’re winning? Is it Enterprise Advanced, other SKUs, other parts of the business? And then I believe someone else asked on the split of Enterprise Advanced new versus existing logos, but I’m not sure I caught the answer. Maybe you can expand there as well.

Aaron Levie: Yes. I would say the 100,000-plus customer count growth is very much directly driven by the sort of overall set of capabilities that are either a part of Enterprise Advanced or customers that are now getting more involved in our platform because they kind of see us obviously on the right side of this AI curve. And actually, it’s interesting, the neutrality piece, we haven’t talked about too much on this call, but it’s sort of somewhat timely in this idea that at any given moment, you might want to use a different AI model for a different capability in your enterprise. And you don’t want to be moving and shuffling around your content depending on that use case. And so that’s another benefit that you get with our overall platform.

And so there’s a lot of these sort of strategic tailwinds where our platform is positioned. And so some customers might buy our platform, not yet Enterprise Advanced, but they’re buying it because they recognize the sort of importance of many of these aspects of our platform overall. And so that’s also helping drive the growth. But Enterprise Advanced very much emphatically is helping lift that number up, and we’re seeing it just kind of across industry right now.

Seth Gilbert: Got it. That’s helpful. And then maybe as a follow-up, as you’re marching towards the long-term guide of double-digit top line growth, margins are remaining roughly flat for 2027 — FY ’27. I understand the drivers of these flat margins, but maybe you can talk about what has to happen for margin expansion in the future. Do we need to see top line growth above 10% to get margin expansion or maybe there’s some efficiencies on the S&M and R&D side that will kind of percolate through once the investment phase next year has taken shape?

Dylan Smith: Yes. So I would say there’s nothing — no required growth rate to be improving operating margin at a greater clip versus the kind of incremental improvement in constant currency that we’re expecting to deliver this year. This year, really, as we’ve talked about, is about doubling down and making sure that we invest to capture the market opportunity, just given where we are in the market evolution. So most of those investments on the sales and marketing side. But if you look back over the last few years, we’ve generated significant margin expansion even while growing in the single-digit range. And so in addition to all of the opportunities and efficiencies that we’re driving around kind of how we’re deploying AI internally, including with Box’s own product, some of the same areas that we’ve been driving operating margin up into the high 20s are the same things that are going to get us the next several points of growth.

So that’s things like continuing to take advantage of our lower-cost workforce location strategy, a lot of the other areas that we’ve invested in that are generating stronger returns, whether that’s with Salesforce productivity, the ROI of the marketing programs or just as a lot of these core strategic go-to-market investments mature, those will be able to generate more leverage as well, including through our partner ecosystem. So really, a lot of things across the board, but would really frame the operating margin and lower rate of improvement in the current moment more as a strategic decision to put more dollars toward growth versus anything about the model itself.

Operator: And everyone, at this time, there are no further questions. I’d like to hand the conference back to Cynthia Hiponia for any additional or closing remarks.

Cynthia Hiponia: Great. Thank you, everyone, for joining us. And to drill down deeper on our strategy and financial model, we are hosting a Financial Analyst Day on Thursday, March 19. Please go to our IR website to register. And hopefully, we’ll see most of you there in person in New York. Thank you very much.

Operator: Once again, everyone, that does conclude today’s conference. We would like to thank you all for your participation today. You may now disconnect.