Box (BOX) Q4 2026 Earnings Call Transcript

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DATE

Tuesday, March 3, 2026 at 5 p.m. ET

CALL PARTICIPANTS

• Chief Executive Officer — Aaron Levie
• Chief Financial Officer — Dylan Smith
• Vice President, Investor Relations — Cynthia Hiponia

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TAKEAWAYS

• Revenue -- Box (NYSE:BOX) reported $306 million for the quarter, up 9% year over year, or 8% in constant currency, and $1.18 billion for the fiscal year, up 8% year over year.
• EPS -- $0.49 for the quarter, above guidance, with the CFO noting this "includes the benefit from several tax items."
• Operating Margin -- 28% for the fiscal year and 30.6% for the quarter, representing year-over-year expansion and surpassing Q4 guidance.
• Gross Margin -- 82.3% for the quarter, up 130 basis points year over year, and exceeding guidance.
• Free Cash Flow -- $313 million for the fiscal year, up 3% year over year, and a record $98 million in the quarter.
• RPO (Remaining Performance Obligations) -- $1.7 billion at quarter-end, up 17% year over year, with 55% expected to be recognized in the next twelve months.
• Billings -- $420 million for the quarter, up 5% year over year, primarily driven by strong bookings.
• Net Retention Rate -- 104% at quarter-end, up from 102% in the prior year, with expectations to remain at 104% in Q1 and reach 104%-105% by fiscal year end.
• Enterprise Advanced Contribution -- Now accounts for 10% of total revenue, with customers paying a 30%-40% price uplift per seat over Enterprise Plus.
• Suites Revenue Mix -- 66% of revenue now comes from Suites customers, up from 60% a year ago.
• Large Customer Growth -- Customers paying at least $100,000 annually grew by 9% year over year.
• Share Repurchase -- 4.4 million shares bought back in Q4 for approximately $126 million, totaling 9.7 million shares and $293 million for the fiscal year, representing over 90% of annual free cash flow.
• Cash Position -- $480 million in cash, cash equivalents, restricted cash, and short-term investments at quarter-end.
• FY 2027 Guidance -- Expected revenue of approximately $1.275 billion (8% year-over-year growth), operating margin of about 28%, EPS of approximately $1.55, and gross margin of roughly 81.5%.
• Q1 2027 Guidance -- Anticipates $304 million in revenue (10% year-over-year growth), gross margin of 81.5%, operating margin of 27.5%, and EPS of $0.36.
• Billings Currency Impact -- CFO Smith said, "digits, which includes an expected headwind from FX of approximately 530 basis points." For the full year, the FX headwind is expected to be 100 basis points.
• Enterprise Advanced Adoption Dynamics -- Most initial upgrades came from existing Enterprise Plus customers, while management noted "huge opportunity for those non-Enterprise Plus customers" in future cycles.
• Platform Monetization -- CEO Levie stated, "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," emphasizing both seat-based and consumption-based business models for agent use cases.
• Partner & Go-to-Market -- Strengthened partnerships with major systems integrators and increased momentum in regulated industries, with noted expansion through marketplaces such as GCP and AWS.
• Product Innovation -- General availability of Box Extract and rollout of Box Shield Pro in the quarter, serving key roles in intelligent document processing and advanced security.

SUMMARY

Management highlighted accelerating demand for AI-enhanced content workflows and cited strong adoption of Enterprise Advanced as a key revenue and pricing driver this quarter. The company delivered sequential revenue growth for the third consecutive quarter, supported by increased platform consumption and a higher pricing mix. Leadership emphasized plans for further investment in AI innovation, workflow automation, and ecosystem partnerships to capitalize on the current product cycle. Guidance reflects sustained margin discipline while allocating more resources to sales and product development, with careful attention to currency fluctuations and seasonality.

• Leadership expects new platform APIs and AI agents to catalyze additional enterprise use cases, with direct monetization through “API and AI unit consumption.”
• The CFO highlighted, “price per seat for Enterprise Advanced customers has commanded an average pricing uplift of 30% to 40% over Enterprise Plus.”
• Q4 marked a shift, as net retention rate gains are now described as “we are now seeing and expecting to see a more healthy mix between the two, with no expected change on the full churn rate on that side,” rather than being driven solely by price increases.
• Commercial (SMB and mid-market) segments, especially in Japan and certain U.S. regions, delivered “nice strength and really good momentum,” improving deal linearity and contributing to the quarter’s outperformance.
• Box Extract and Box Automate are positioned to address more complex, enterprise-wide automation use cases beyond initial document data extraction.
• Expenses related to the annual BoxWorks conference in Q4 will increase by approximately $3 million compared to the previous year, impacting margin seasonality.
• Management confirmed that operating margin improvements are a “strategic decision to put more dollars toward growth,” rather than a structural model constraint, with additional leverage anticipated as investments mature.

INDUSTRY GLOSSARY

• Enterprise Advanced: Box's highest-tier solution suite, bundling intelligent workflow automation, advanced AI capabilities, and enhanced content security, offered at a premium over prior plans.
• RPO (Remaining Performance Obligations): The total value of contracted revenue yet to be recognized, offering forward visibility into future revenue streams.
• Box Shield Pro: An advanced add-on for Box Shield, leveraging agentic AI for scalable, automated enterprise security and data governance controls.
• Box Extract: An AI-powered tool enabling automated extraction of structured data from unstructured documents stored in Box's platform.
• Box Automate: An automation feature for designing agent-assisted content workflows, including human- and machine-in-the-loop steps, set to launch in fiscal 2027.

Full Conference Call Transcript

Cynthia Hiponia: Good afternoon, and welcome to Box, Inc.'s Fourth Quarter and Fiscal Year 2026 Earnings Call. I am Cynthia Hiponia, Vice President, Investor Relations. On the call today, we have Aaron Levie, Box, Inc. Co-Founder and CEO, and Dylan Smith, Box, Inc. 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 2027 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 repurchases 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 filed 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. Forward-looking statements are being made as of today, 03/03/2026, 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 2027 guidance. Thank you. With that, let me turn the call over to Aaron Levie.

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 $306,000,000, 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, Inc. as we launched 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.

We are incredibly excited about this early traction and continued momentum. Examples of Enterprise Advanced customer wins include a leading biotech company that uses Box, Inc. 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, Inc. as the core platform for its revenue operations and content workflows. The company upgraded from Enterprise Plus to Enterprise Advanced to streamline quote creation and approvals with DocGen, 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 is driving the momentum with Box, Inc., it is 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, 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 roadmap, 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 hundredfold 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 task that they are 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 have required for people in the enterprise. As we have 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 are building at Box, Inc. with our intelligent content management platform. In FY 2026, it 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, Inc., 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 2026. Now looking forward, in FY 2027, we will be delivering the next generation of AI agent features within Box, Inc., enabling AI agents that can do more long-running tasks and advance work on enterprise information. Soon, you will 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 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 2027, 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, Inc. Finally, this is going to be a major year for the Box, Inc. 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 are making it as easy and secure as ever to leverage Box, Inc. 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, Inc.'s APIs, MCP server, and CLI support.

We are incredibly excited about this new array of use cases for the Box, Inc. 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 have noted, we are incredibly excited about the momentum we are seeing with Enterprise Advanced.

Across industries like financial services, legal, life sciences, and in the public sector, including other key industries, we are seeing growing momentum for enterprises to adopt Box, Inc.'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 selected Box Enterprise Advanced as the content layer for regulatory case management.

Working with a global systems integrator, Box, Inc. replaced a legacy system, enabling secure document intake, high-volume review, and AI-assisted classification, integrated into core case systems, positioning Box, Inc. 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 2026, and especially through the tail end of the year, in FY 2027, we believe it is critical to continue to strategically invest to build on this momentum and ensure we are capturing this market opportunity. We will continue to invest in our critical growth verticals, go-to-market capacity, and marketing efforts. We are bringing the full power of Box, Inc.'s Enterprise Advanced plan to customers through Box, Inc.'s solution offerings and key lines of business and industries. We are accelerating growth in large enterprises by deepening partnerships with major SIs like Deloitte, Solon, TCS, Databank, and more. We are 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 two 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, Inc., our opportunity has never been larger to transform how companies work with their content. We are entering FY 2027 with the strongest momentum I have ever seen as we become the platform that powers intelligent content workflows and automation in the enterprise.

I will now turn the call over to Dylan Smith for the financial results.

Dylan Smith: Thanks, Aaron. Good afternoon, everyone. Q4 capped off a year of strong execution against the three 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 $3,000,000 over the past year. In FY 2026, 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 2026, we generated record free cash flow of $313,000,000, 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 $306,000,000, 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 has 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 twelve months. Q4 billings of $420,000,000 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 2027. Q4 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 $94,000,000 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 2026 and on a go-forward basis. Excluding these tax benefits, EPS would have exceeded our guidance by $0.02. I will now turn to our cash flow and balance sheet. In Q4, we generated free cash flow of $98,000,000 and cash flow from operations of $110,000,000, up 78% year over year, respectively. We ended Q4 with $480,000,000 in cash, cash equivalents, restricted cash, and short-term investments. Our balance sheet reflects the cash settlement of debt principal related to our February 2021 convertible notes that matured on 01/15/2026. In Q4, we repurchased 4,400,000 shares for approximately $126,000,000.

For the full year of FY 2026, we repurchased approximately 9,700,000 shares for approximately $293,000,000, representing more than 90% of FY 2026 free cash flow generation. As of 01/31/2026, we had approximately $59,000,000 of remaining buyback under our current share repurchase plan. With that, let me now turn to our Q1 and FY 2027 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 2027 guidance reflects a lower expected GAAP and non-GAAP tax rate benefiting EPS. For 2027, we expect Q1 revenue to be approximately $304,000,000, 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 141,000,000. For the full fiscal year ending 01/31/2027, we expect our full-year revenue to be approximately $1,275,000,000, representing 8% year over year growth, or 9% in constant currency. We expect our FY 2027 billing growth rate to be roughly in line with revenue growth.

This includes an expected headwind of 100 basis points from FX. We expect FY 2027 gross margin to be approximately 81.5%. We expect our FY 2027 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. We remain committed to delivering significant margin expansion over the next few years.

As it relates to FY 2027 expense and margin seasonality, please note that our annual customer conference, BoxWorks, will take place in Q4. This will shift approximately $3,000,000 in expenses from Q3 into Q4 as compared to FY 2026. We expect FY 2027 EPS of approximately $1.55, or $1.58 in constant currency. Weighted average diluted shares are expected to be 141,000,000. In the era of AI agents, 2026 demonstrated the success of this strategy, including an acceleration in RPO growth and an improvement in our net retention rate. In FY 2027, we will continue to invest in our robust product roadmap 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. We will now open for questions. Operator?

Operator: Thank you, sir. And ladies and gentlemen, if you have a question, please press star one. Once again, that is star one if you have a question. We will take the first question from Steve Enders, Citi.

Steve Enders: Okay, great. Thanks for taking the questions here. I guess I just want to start on the opportunity first that you are maybe seeing from AI, and just how do you think about how the changes in the Gen AI landscape maybe impact the content layer and what this looks like moving forward with the agentic AI?

Aaron Levie: Yeah. So, thanks for the question. As you can tell from the remarks, we are unbelievably excited around the role that content plays in any kind of agentic system. There are 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 is a dramatic increase in software that enterprises build, I do not 100% agree with the thesis that they will build existing internal systems, but almost independent of what you believe, there is going to be vastly more software produced in the future, sometimes bespoke software, sometimes just more companies.

And for really any 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 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—we have seen a few examples of agents kind of break through recently, the Claude Cowork agent, the 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 are a lawyer, you are looking at contracts. If you are in banking, you are looking at lots of financial reports. If you are in pharma, you are looking at lots of both research and information coming in from lab tests. All of that is unstructured data.

To now replace a person with an agent in that example, agents will need that exact same data to work with. They are going to need the contract to look at. They are going to need the pharma research to touch. They are 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 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—it might disappear in a week or a month or a year from now. But what cannot disappear is the data that agent worked on. If, 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. The part that actually has to keep state forever, up to the point that the customer cares about working with the data, is the information that agent worked with.

So we really imagine a world where, let us say, you have 10 or 100 or 1,000 times more agents in 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 that work or go back and forth with the agent. Fundamentally, there needs to be some type of shared file system for them to be able to do that work. And that is 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 is our overall take. We are seeing this thesis continue to play out in the market. You are 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 are seeing already from our customer base and developer base, and so we are just excited to continue to make that as frictionless as possible and continue to pour fuel on that fire.

Steve Enders: Okay. No, that is great to hear. Maybe just on the Enterprise Advanced success so far, it is good to see you at 10% of revenue already so quickly. What are your expectations for what that will look like or where that is going to end up in fiscal 2027? What do you have embedded in the guide, and how are you viewing the uplift so far from customers that have taken on the Enterprise Advanced tier?

Dylan Smith: I would say we are certainly very excited about the momentum that we are 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 in the year ahead, and we will give more details in terms of what we are 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. In terms of the type of impact that we are seeing from customers, we mentioned being really pleased with just how much the value of these newer capabilities is resonating with customers.

So we have been seeing pricing uplifts 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 are 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 it is driving, which is one of the reasons that we are so excited about the path forward and the growth opportunity that it creates.

Steve Enders: Okay. Perfect. Thanks for taking the questions.

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

Rishi Jaluria: Wonderful. Thanks so much for taking my question. Maybe I want to start, Aaron, in your prepared remarks you talked a lot about many of the verticals, especially regulated verticals, where you are helping enable a lot of these AI use cases. Can you talk a little bit about 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 are seeing specifically out of more regulated industries? And then I have a quick follow-up.

Aaron Levie: Yeah. So great question. Obviously, I think right now you have a bit of a tale of two cities with AI adoption. You have a lot of these sort of deep engineering use cases—AI coding, etc.—that have obviously taken off because the users of these platforms are technical, they can adopt their own tools, the communities are pretty wired together. Then you have 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 work. At this point, it is safe to say every knowledge worker has some degree of access to a chat tool, either personally or professionally.

And so general purpose, “I am asking the internet” or some systems questions is increasingly growing. The real interesting part is can I actually go in and automate and accelerate and augment my workflows in an organization? With Enterprise Advanced, this is really an applied system for how 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. 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 with Box, Inc.

We are seeing a lot of growth in those use cases right now. As I mentioned on the call, we have a new product called Box Automate 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 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 task-specific applied use cases to increasingly more of the full business process with both agents and people showing up at the relevant point.

But we are 100% focused on applied AI use cases in an organization, and that is why we are seeing healthy adoption of both Enterprise Advanced as well as in regulated industries—maybe ones where it would not have been initially intuitive that they would be able to adopt so quickly. It is because these are applied use cases and our platform is purpose-built for security, compliance, and data governance issues that they are going to run into with AI.

Rishi Jaluria: Yep, got it. Thanks. That is really helpful. And then, Dylan, for you, just maybe a bit more of a housekeeping question. As you talked about your Q1 billings guide, you talked about FX as a—correct me if I am wrong—530 basis point headwind to growth. That seems a little bit high, especially in light of the rest of your as-reported and constant currency growth rates. Can you expand a little bit on 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 pretty significant movement in the U.S. dollar to yen exchange rate in that period. That is one of the reasons. Also, if you look at our Q1 results from this past year in FY 2026, it was really the reverse story and was one of the contributing factors to extremely strong billings growth. So it really is unique to just the movement that we saw in that exchange rate a year ago. And for the year, it is much more normalized. So you did hear that right in terms of the 530 basis points headwind for Q1.

For the year, we expect FX to be roughly a 100 basis points 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.

Rishi Jaluria: Alright. Understood. Thank you so much.

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

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

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

Brian Peterson: Yeah. Two parts, sorry. Yeah, for the fourth quarter. Two 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: Yeah. 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 and drive some of that upside. That was certainly a contributing factor to the underlying bookings strength and outperformance that we saw. At the same time, which also touches on your second question, we have seen nice strength and really good momentum in the performance of our commercial business—so SMB and 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. On top of those segments, 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 have seen over the past year, other than continued and additional strength on the commercial side, with everything at 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 10%. How many came in migrating from the existing base or net new? I would love to unpack that a bit. Thanks, guys.

Aaron Levie: Yep. Enterprise Advanced sets us up very nicely for net new conversations because it gets you into a workflow and particularly an agentic workflow conversation. So you could have never run into a use case that we previously would have been able to solve for you with Box, Inc., 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 two years ago we would have had no ability to play in. So this could be a contract automation process, a client onboarding workflow where we are doing more of the intelligence, it could be in a healthcare data processing workflow.

We have customers where we have had conversations where they want to rip and replace a legacy ECM system, and maybe they were starting to figure out if they could migrate that to the cloud or build out their own capability, and then all of a sudden they see the full depth of data governance, security, and compliance that they are going to need, especially in a world of agents, and decide that actually Box, Inc. is going to be the superior, more future-proof solution for that.

So in all of these examples, Enterprise Advanced is putting together a package between workflow, no-code apps, AI agents, and 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, Inc. We are 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.

Matt Bullock: Great. Thank you. I wanted to ask about revenue retention expectations. It looks like it is going to improve modestly in fiscal 2027, but I would be curious to hear if you could unpack the components of that across pricing per seat benefit and 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 one to two points of growth from platform?

Dylan Smith: Yeah. So in terms of drivers of the net retention rate, 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, when it was more so being driven by the pricing side. But we are now seeing and expecting to see a more healthy mix between the two, with no expected change on the full churn rate on that side.

And then in terms of the overall platform business, yeah, we could see that certainly contributing to the net retention equation and part of the overall pricing dynamic and that uplift that we would see there. But to your point, at least for the coming year, I do not expect that to be a material driver of any change in the net retention rate.

Matt 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 have seen consistent 30% to 40% uplift relative to Plus, already at 10% revenue mix here. You are innovating quite a bit. Do you foresee the pricing uplift for Enterprise Advanced potentially ticking above that 40% kind of baseline that it has tracked at so far over the next couple years as you continue to add value?

Dylan Smith: I would say we probably would not expect to see that move up too much in terms of the core upgrade. The 30% to 40% uplift is really specific to the apples-to-apples, “Hey, you have X seats, and now they are moving to Enterprise Advanced. What is the price per seat?” I do not 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 related levers.

Matt Bullock: Fantastic. Thank you.

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

Lucky Schreiner: Great. Thanks for taking my questions. Maybe a unique one, but over the course of the year, did you notice any change in behavior between the early adopters of Enterprise Advanced versus customers that maybe adopted in April, just given the vast improvements in the models that we have 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. Yeah, and some of the agentic abilities that you guys can provide on the platform.

Aaron Levie: It is a great question in terms of how you are characterizing it. I do not know that I would pinpoint any specific thing, but the general trend that is embedded in that question is actually correct, which is if I go back, let us say, fourteen months ago when Enterprise Advanced initially 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.

As each model family has its next upgrade in its lineage, we tend to see anywhere from single-digit to double-digit percentage points in accuracy and quality of the models on unstructured data.

That is just universally a good thing for us because it means there are 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 would say that 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 are already seeing that trajectory take off with our conversations. So it is a fantastic, universally good trend for us that we are going to keep riding.

Lucky Schreiner: Awesome. That makes a lot of sense. Then on the Enterprise Advanced customers, congrats on the percent of revenue—that is impressive. But 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. Is there anything about the non-Enterprise Plus customers that might be slower to upgrade to the higher tiers, and how are you thinking about that opportunity?

Dylan Smith: Yeah. I think that is right that the majority of the Enterprise Advanced customers who have upgraded were coming from our existing customer base and, more likely than not, coming from Enterprise Plus.

I would not say there is anything unique about the types of companies—whether it is company size or any unique dynamics by the actual company—but just from a use case point of view, certainly those customers who are more already bought into the value of Box, Inc.’s platform offerings and who have a lot of the use cases that would benefit the most from Enterprise Advanced capabilities, as you would expect and especially from an early adopter stage, is pretty strongly correlated with those customers who are already on Enterprise Plus, which was previously our highest-tier offering. So that is really, I would say, a function of timing and the specific customers.

It is almost self-selecting—if you are one of the early adopters of Enterprise Advanced, more likely than not, you are on Enterprise Plus. But we see a huge opportunity for those non-Enterprise Plus customers, just given the types of use cases and the types of conversations we are having and the potential there as well. So more of a timing thing than anything else is what we would 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: Yeah, thank you. Thank you, 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 has become back-end databases on which an intelligence layer like Claude sits and captures much of the value. And then second, that seat-based models face structural challenges because of knowledge worker job displacement.

Aaron Levie: Yeah. This might sound like a little bit of the first question, but there is almost nothing in that is bad for Box, Inc., ironically. I do not necessarily totally believe some of those components, especially the 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 and workforces. But what we are building as a platform is for 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 is simply no way around it.

You cannot have two agents that are maybe trying to coordinate a task for a lawyer be working off of two different sets of contracts. They fundamentally would need the same access to data. You need a shared file system. The shared file system has to be accessible to your agents and your people. Maybe the ratio changes over time of different roles in the economy in different parts, but no matter what, there will be some human in the loop at some part, so then the data has to be shared with a person.

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 are a large bank, and your bank is processing escrow documents or loan files from a client. That data will have to be governed just like when people went and reviewed those documents. They are going to need to sit around for ten years in some cases. You are going to need to see the exact traces of what the agent did and what decisions they made in that workflow. All of that is unstructured data.

It will all become content, whether it is markdown files or PDFs or Word documents. All enterprise content has to be secured and governed and controlled and protected in the exact same way that we have always been doing it because files are this natural medium by which people and agents share information. So I would just say that our platform story becomes increasingly the core of how we can power both agents, applications, and people.

So, in a scenario where you have maybe a seat decline because agents have grown so much—which let us posit as 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 if you have more and more, let us call it, AI-generated 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 is our platform business model.

So we can grow either through platform consumption or we grow through continued seat adoption, both of which we are seeing right now in the business. And it is 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; in fact, it probably becomes more important in a world of agents.

Because if you have 100 times more agents running around doing loan processes than you had people, the chance of a mistake happening and the risks of an agent revealing the wrong piece of information to a client goes up exponentially. Those agents do not have context for what they should or should not be sharing. It is very easy to prompt-inject those agents. There are 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, collaboration with the user. So that is what we are powering.

That is what our platform has always done for humans and for applications, and now we are adding agents into the mix, which is why we see this as just universally a good thing. So I think maybe the one thing where we sit around, we look at Claude Cowork, and we see OpenClaw—we are just incredibly happy for the existence of these things. We were a Claude Cowork partner on their plug-ins. The more knowledge work that happens agentically, it is 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 just as a quick one, could you talk about the AI API monetization in relation to that answer that you just gave?

Aaron Levie: Yeah. So there are a couple parts of the API monetization. There is a pure volume-based mechanic. So if you were to use Box, Inc. tomorrow and you deployed a fleet of agents, they were all running around, and you had 100 times more agents than people in your organization, each of those agents you would probably want to have a Box account of some sort. You can either have a headless Box account or you can have a regular Box account—you choose. You are going to want those agents to be writing, reading, storing data, sharing with other people.

If it is done in a headless capacity via our APIs, we have a platform business model which is consumption-oriented, and so you will just pay for the API calls that go into that. Then if you use our direct intelligence layer, which taps into Claude and GPT-5.2 or any new model like Gemini 3, then we also monetize that through AI units. So we have 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—we are still relatively early on total seat penetration.

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 did not previously solve. There still will be a human in the loop working with agents, but now we are able to capture more of the use cases than we would have for that particular knowledge worker five years ago. So it is multifaceted growth levers, but the simple concept here is 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 is always a file. Those files are going to get generated, they are going to need to get stored somewhere, they are going to need to be governed, and they are going to need to be shared with people. So that is the general tailwind that our platform is going to be able to support.

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

Seth Gilbert: Thanks for the questions. For the first one, you had the best greater-than-$100,000 customer growth in about eleven quarters. The question is on the customer adds front. Can you help us expand on where you are 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 am not sure I caught the answer. Maybe you can expand there as well. Thank you.

Aaron Levie: Yeah. I would say the $100,000-plus customer count growth is very much directly driven by the 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 see us on the right side of this AI curve. Actually, it is interesting—the neutrality piece. We have not talked about it too much on this call, but it is somewhat timely in the idea that at any given moment, you might want to use a different AI model for a different capability in your enterprise, and you do not want to be moving and shuffling around your content depending on that use case.

That is another benefit that you get with our overall platform. So there are a lot of these strategic tailwinds where our platform is positioned. Some customers might buy our platform, not yet Enterprise Advanced, but they are buying it because they recognize the importance of many of these aspects of our platform overall. That is also helping drive the growth. But Enterprise Advanced very much emphatically is helping lift that number up, and we are seeing it across industries right now.

Seth Gilbert: Got it. That is helpful. And then maybe as a follow-up, as you are marching towards the long-term guide of double-digit top-line growth, margins are remaining roughly flat for FY 2027. 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 are 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: I would say there is nothing—no required growth rate—to be improving operating margin at a greater clip versus the level of incremental improvement in constant currency that we are expecting to deliver this year. This year, as we have 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 are on the sales and marketing side. But if you look back over the last few years, we have generated significant margin expansion even while growing in the single-digit range.

In addition to all of the opportunities and efficiencies that we are driving around how we are deploying AI internally, including with Box, Inc.’s own product, some of the same areas that we have 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 is things like continuing to take advantage of our lower-cost workforce location strategy, a lot of the other areas that we have invested in that are generating stronger returns—whether that is 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 I would frame the operating margin and lower rate of improvements 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 would like to hand the conference back to Cynthia Hiponia for any additional or closing remarks.

Cynthia Hiponia: Great. Thank you, everyone, for joining us. 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 will 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.

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