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Box, Inc. beats earnings expectations. Reported EPS is $0.3, expectations were $0.25.
Operator: Ladies and gentlemen, thank you for standing by. My name is Krista, and I will be your conference operator today. At this time, I would like to welcome everyone to the Box, Inc. First Quarter Fiscal 2026 Earnings Conference Call. All lines have been placed on mute to prevent any background noise. [Operator Instructions] And I would now like to turn the conference over to Cynthia Hiponia, Vice President, Investor Relations. Please go ahead.
Cynthia Hiponia : Good afternoon and welcome to Box Inc’s First Quarter Fiscal 2026 Earnings Conference Call. I am Cynthia Hiponia, Vice President, Investor Relations. On the call today, we have Aaron Levie, Box’s co-founder and CEO, and Dylan Smith, Box’s 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 at www.boxinvestorrelations.com. Our webcast will be audio only. However supplemental slides are now available for download from our website. On this call, we will be making forward-looking statements including: Our second quarter and full year fiscal 2026 financial guidance, and our expectations regarding our financial performance for fiscal 2026 and future periods, including gross margins, operating margins, operating leverage, future profitability, net retention rates, remaining performance obligations, revenue and billings, and the impact of foreign currency exchange rates and deferred tax expenses; and our expectations regarding the size of our market opportunity; our planned investments, future product offerings, and growth strategies; our ability to achieve our revenue, operating margins and other operating model targets; the timing and market adoption of, and benefits from, our new products, pricing models, and partnerships; our ability to address enterprise challenges 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 in documents we file with the SEC, including our most recent Annual Report on Form 10-K 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, May 27, 2025, 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 our 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 on a non-GAAP basis. Thank you. With that, let me turn the call over to Aaron.
Aaron Levie : Thank you, Cynthia. Thank you all for joining the call today. We had a strong start to FY26, with results reflecting continued growth in customer demand for Box AI. In Q1 our revenue grew 4% year-over-year, or 5% in constant currency, RPO grew 21% year-over-year, and we saw strong outperformance on billings. We delivered operating margins of 25.3% and EPS of $0.30, $0.04 above our guidance. Following the launch of Enterprise Advanced late in Q4, in Q1 we saw strong momentum in customer adoption as enterprises look to Box to help them transform their AI-driven workflows around content. Examples include a leading University Hospital upgraded to Enterprise Advanced and significantly expanded their Box seats. Currently, content is siloed across the organization, and they aim to make Box their single source of truth while unlocking value through Box Apps and AI-driven metadata extraction.
An investment advisory firm who has already been leveraging the Box AI API for metadata extraction upgraded to Enterprise Advanced to expand their use of diverse AI models through the Box AI Studio. They also plan to use Box Apps dashboards to manage and organize critical business information more strategically and leverage Doc Gen to further streamline operations. A financial services firm and a new Box customer, purchased Enterprise Advanced to modernize and secure their critical business data by moving from an outdated on-prem system to Box. Looking to improve their control over sensitive content for personally identifiable information, enhance their user experience, and optimize their retention strategy, they needed a scalable, compliant platform supporting loan origination, HR, and legal functions.
In the first quarter I had the opportunity to meet with well over a hundred customers, and it’s incredibly clear that there is a fundamental shift in what business will look like in an AI-first world. In fact, tomorrow we are releasing our first State of AI in the Enterprise Survey, where we recently surveyed over 1,300 IT leaders across a range of industries and geographies. More than half of the respondents expect to see transformation from AI in the next two years, and nearly 90% are already using AI agents in some capacity. And many of the top desired use-cases for AI are around working with documents and unstructured data. What’s clear is that as companies increasingly go AI-first, they are beginning to rethink how they can take advantage of their enterprise content, from their contracts and invoices to their research data and marketing assets.
For years the value of this content has been limited to only what humans can do with this information. Which means most companies have never been able to truly tap into the full value of this information. But in a world of AI and AI Agents, this finally becomes possible. Inside of all this information are the answers to a company’s next product breakthrough, their customer upsell opportunity, how they can hire amazing new talent, or optimize their supply chains, AI Agents make this all possible. At Box, we’re building out the leading Intelligent Content Management Platform to help enterprises fully connect the power of AI to their content. Now to deliver on this strategy, at our Content+AI Summit in mid-May, we announced our biggest set of AI Agent updates ever, designed to transform how organizations work with their content.
We unveiled all new capabilities to support AI Agents that can do Deep Research, Search, and enhanced data extraction on content securely in Box. And all with a focus on openness and interoperability. Imagine being able to have AI Agents that can comb through any amount of your unstructured data contracts, research documents, marketing assets, film scripts, financial documents, invoices, and more to produce insights or automate work. Box AI Agents will enable enterprises to streamline a due diligence process on hundreds or thousands of documents in an M&A transaction, correlate customer trends amongst customer surveys and product research data, or analyze life sciences and medical research documents to generate reports on new drug discovery and development.
None of this would have been possible even a year ago. But with the cost of AI inference dropping, context windows expanding to support larger data sets, reasoning models handling much more complex tasks, and better understanding of designing agentic workflows, this all of a sudden becomes possible. Next, we believe in a world where AI Agents work together to complete tasks across platforms. So this means that an AI Agent from Box could work across an enterprise’s entire AI stack. In addition to our newly announced Box AI Agent for Microsoft 365 Copilot and IBM watsonx Orchestrate, Box AI Agents are available or in development with Google Agentspace, Salesforce Agentforce, Slack AI, ServiceNow AI Agent Fabric, and the Zoom AI Companion. Developers can also build custom agents that leverage Box content using the Box MCP server, the Google Agent SDK, and OpenAI Agents SDK, as well as through their preferred developer and data platforms.
Building on these announcements, just last week ChatGPT officially integrated Box, as a secure connected data source for their deep research AI Agent. Now, instead of moving your data around between each platform that you want to work in, you can just work where you want and have the AI agents coordinate together in the background to get the data that you need from Box. This is the future of software in an era of AI. Finally, we will continue to partner with the broader AI model ecosystem to ensure customers have the choice of any model provider they want to work with. Just in Q1 alone, we saw incredible examples of us sitting at the center of this industry, such as the recent Nvidia GTC keynote from Jensen, mentioning Box, Box joining OpenAI as a launch partner for their Agent SDK, Meta showcasing Box and IBM’s support for Llama at their latest AI developer event, Box serving as a day 1 Grok 3 API launch partner with xAI, and many more.
Being neutral to the AI models means that our customers get instant access to the best that AI has to offer on their content instead of having to keep their data stuck with just one particular AI provider, and this partner momentum will only increase in Q2 and beyond. Over the coming months, we’ll be gearing up for BoxWorks in September, which will include our biggest and most exciting announcements we’ve ever had on this platform. This is the year of AI Agents and the ability to drive automation around any kind of workflow with AI, and Box will be building out the leading capabilities to help our customers do this with their enterprise content at scale. We look forward to sharing more in early September at BoxWorks. Now, turning to Go-to-Market.
We’re continuing to drive Enterprise Advanced momentum across segments and geographies. Even after the large number of early adopters we saw in Q4 bring on Enterprise Advanced, we were pleased to see the continued growth in deals in Q1, our seasonally lowest quarter, with a strong pipeline continuing to build as customers look to drive intelligent workflows in Box. Additionally, we’re continuing to drive pricing improvements in our target 20% to 40% increase range for these Enterprise Advanced deals. As we’ve discussed, one of our key initiatives to drive growth is to expand and grow our partner ecosystem, particularly with global and regional systems integrators. In Q1 we are already seeing solid momentum in customer wins enabled by our partners.
After announcing our partnership with DataBank in March, we had a great win with a local government upgrading to Enterprise Advanced to replace a legacy enterprise content management system. We also partnered with regional SIs in financial services and life sciences, with partnered-enabled deals to replace legacy systems and automate processes to deliver secure, compliant solutions that are well-suited for regulated environments. Also, in the first quarter we were excited to announce that we received FedRAMP High Authorization, allowing U.S. government agencies and authorized government contractors the ability to leverage Box’s Intelligent Content Management platform for highly sensitive data. Finally, before I turn the call over to Dylan, let me discuss how we at Box are building an AI-first company.
As Customer Zero, we are driving an AI-first culture as we use Box AI to help us move faster, make better decisions and automate work. Not only will this drive productivity and innovation, going AI-first as a company is also important for our strategy of building the leading AI platform for enterprise content. Paul Graham famously gave the startup advice of live in the future, then build what’s missing. The idea behind this is that the teams that deeply figure out where the world is going will often see the new opportunities that arise far sooner than others. This is what we’re doing at Box. Across Box, we are seeing Box AI be leveraged to help transform how we work every day. Internally, we use AI-powered Hubs to help answer customer support questions, onboard new sales reps faster, get HR questions answered instantly, and much more.
Boxers can access every leading AI model alongside their content to streamline understanding data, reviewing code, or generating new content for marketing assets or product documentation. Boxers are creating custom AI Agents to generate call scripts, create more personalized sales materials, or answer RFPs. And we use AI Agents to extract metadata on policy documents to help streamline internal compliance and document management workflows. And finally, beyond Box AI, we use AI-first coding tools and customer service tools to augment our workforce and drive productivity. Importantly, our principal focus of going AI-first is to move faster and be able to deliver better for our customers. We want to ensure that every Boxer is fully equipped to be as productive as possible with AI, which is why we’re making it easy to experiment with AI across the company, and we’re highlighting best practices as they emerge, and driving as much upskilling of our workforce as possible.
And for new employees coming in, we will increasingly look for AI-first skills as a part of our hiring criteria. This is the biggest shift in work that we’ve ever seen in our lifetimes, and we’re excited to make sure that Box sits right at the center of it. With that, let me turn the call over to Dylan.
Dylan Smith : Thanks Aaron. Good afternoon everyone, and thank you for joining us today. Q1 was a strong start to the year as we exceeded all guidance while also delivering double digit billings and short-term RPO growth. These strong results enable us to deliver on our key FY26 priorities; investing in our Intelligent Content Management platform and key go-to-market initiatives, generating consistent operating leverage, and executing on our disciplined capital allocation strategy. Q1 revenue of $276 million was up 4% year-over-year and up 5% in constant currency. We now have approximately 1,940 total customers paying us at least $100,000 annually, up 8% year-over-year. Suites customers now represent 61% of our revenue, up from 56% a year ago.
Our continued Suites momentum was driven by early traction with Enterprise Advanced, and strong demand for our various AI capabilities. We ended Q1 with remaining performance obligations, or RPO, of $1.5 billion, a 21% year-over-year increase, and up 17% in constant currency. Our strong long-term RPO growth was driven by a continued lengthening in customer contract durations. We expect to recognize roughly 55% of our RPO over the next 12 months. Q1 billings of $242 million were up 27% year-over-year, and up 17% in constant currency. This result exceeded our expectations of low to mid-teens growth due to strong bookings, including a tailwind from early renewals of approximately 400 basis points. FX also provided a tailwind of 700 basis points versus our prior expectations.
We ended Q1 with a net retention rate of 102%, up from 101% a year ago, and in-line with our expectations. Our annualized full churn rate remained at a 3%, demonstrating the continued stickiness of our platform. We continue to expect our net retention rate to improve to 103% exiting FY26. We delivered Q1 gross margin of 80.5%, up 30 basis points year-over-year. As a reminder, in Q1 of last year our gross margin benefited by approximately 100 basis points due to data center equipment sales in the quarter. Q1 gross profit of $222 million was up 5% year-over-year, slightly exceeding our revenue growth rate. We delivered Q1 operating income of $70 million, and operating margin of 25.3%, versus 26.6% in the year ago period. Adjusting for the impact of datacenter equipment sales, the leap year, and FX, operating margin would have been up 90 basis points year-over-year.
As a result, we delivered EPS of $0.30 in Q1, $0.04 above the high-end of our guidance. This includes a positive impact of $0.01 from FX and a negative impact of $0.12 from non-cash deferred tax expenses. I’ll now turn to our cash flow and balance sheet. In Q1 we generated free cash flow of $118 million, and cash flow from operations of $127 million. We ended Q1 with $792 million in cash, cash equivalents, restricted cash, and short-term investments. In Q1 we repurchased 1.6 million shares for approximately $50 million. As of April 30, 2025, we had approximately $152 million of remaining buyback capacity under our current share repurchase plan. We remain committed to opportunistically returning capital to our shareholders through our ongoing stock repurchase program.
With that, let me now turn to our Q2 and FY26 guidance. As a reminder, approximately one third of our revenue is generated outside of the US, with roughly 65% of our international revenue coming from Japan. Before providing guidance, I wanted to remind you of the tax impacts we mentioned on our last call. We continue to expect that the non-cash deferred tax expenses will be an incremental non-GAAP EPS headwind of $0.52 in FY26. For the second quarter of fiscal 2026. We expect Q2 revenue to be in the range of $290 million to $291 million, representing approximately 8% year-over-year growth at the high end of the range, and 6% growth in constant currency. We anticipate our Q2 billings to be roughly flat year-over-year. This includes an expected tailwind from FX of approximately 70 basis points, as well as a roughly 230 basis point negative impact from Q1 early renewals.
We expect Q2 gross margin to be approximately 81%. We anticipate our Q2 non-GAAP operating margin to be approximately 28% versus 28.4% a year ago. Note that this includes the impact of a 70 basis point headwind from data center equipment sales in the year ago period, offset by an expected FX tailwind of approximately 80 basis points. We expect our Q2 non-GAAP EPS to be in the range of $0.30 to $0.31, which includes an expected tailwind of approximately $0.02 from FX. Weighted average diluted shares are expected to be approximately 150 million. For the full fiscal year ending January 31, 2026, while our strong Q1 results and Enterprise Advanced momentum give us confidence in our ability to execute, we are mindful of the macroeconomic uncertainty and potential impact to IT spending.
While this environment has not had a material impact on our business so far, we want to remain prudent in our outlook for the remainder of fiscal 2026. We now expect revenue to be in the range of $1.165 billion to $[1.17] (ph) billion, representing a $10 million increase versus our previous guidance and roughly consistent on a constant currency basis. This represents approximately 7% year-over-year growth or approximately 6% in constant currency. We now expect a tailwind of approximately 120 basis points from FX. We expect our FY ’26 billings growth to be approximately 9%, including a tailwind of approximately 340 basis points from FX. We expect FY ’26 gross margin to be approximately 81%. When adjusting for the impact from data center equipment sales last year, which also flows through to operating margin, this represents a year-over-year improvement of 40 basis points.
We expect our FY ’26 non-GAAP operating margin to be approximately 28%, including a tailwind of approximately 40 basis points from FX as we look at the linearity of operating margin in the second half of the year, please note that our annual customer conference Boxworks has moved from Q4 to Q3, shifting approximately $3 million in expenses in Q3. We now expect FY ’26 non-GAAP EPS to be in the range of $1.22 to $1.26, including an expected tailwind of approximately $0.07 from FX. This represents an increase of $0.09 or $0.02 on a constant currency basis. Weighted average diluted shares are expected to be approximately 151 million. FY ’26 is off to a strong start driven by continued growth in customer demand for Box AI. As we outlined at Financial Analyst Day, we are in the early innings of a once-in-a-generation opportunity that will revolutionize how AI can transform content in the enterprise.
We will continue to invest in our intelligent content management platform and key go-to-market initiatives to execute against this opportunity and we remain firmly committed to driving meaningful long-term improvements in our financial profile from top to bottom. With that, Aaron and I will be happy to take your questions. Operator?
Operator: Thank you. We will now begin question-and-answer session. [Operator Instructions] Your first question comes from George Kurosawa with Citi. Please go ahead.
Cynthia Hiponia: Actually, operator — pardon me, George — yes. One quick correction, Dylan go ahead.
Dylan Smith: Just wanted to note for our Q1 results for EPS that was — that had included a benefit of $0.01 from FX where as I mentioned that as a $0.01 negative impact. So it was actually a $0.01 tailwind of — due to FX in the quarter.
Cynthia Hiponia: Great. Thank you. George, you can go ahead with your questions.
George Kurosawa : Okay. Great. Thanks for taking my question, one for Steve. Maybe just to touch on the demand picture, kind of the topic of the quarter. It sounds like you’re not seeing much in the business, but maybe there’s a little bit incrementally baked into the guide. If you could just talk about how customer conversations have been and then help us frame what kind of incremental prudence you baked into the guidance?
Aaron Levie : Yes. So overall, very healthy robust customer conversations, as you saw in the Q1 results, we’re very happy with the Q1 performance, seeing strong momentum coming into Q2. The AI kind of first strategy that we’ve laid out for customers, I think, is resonating. All of our customer conversations are either starting with or at some point in the conversation turning into really AI-oriented conversations around how companies can get the most out of their unstructured data, automate workflows, bring intelligence to their content. So a lot of momentum on that front. And then overall, we wanted to just be prudent with the overall environment. Obviously, it’s a dynamic macro and so just trying to balance all those factors right now.
George Kurosawa : Okay. Great. That’s helpful. And then maybe just a follow-up. A question we are getting is billings and RPO growth, really strong 17% quarter-on-quarter. You guys are guiding to 6% for constant currency revenue growth. If you could just kind of help us bridge the gap there? It sounds like maybe there was a little timing in Q1. Just anything else we should keep in mind there.
Dylan Smith : Yes. So really primarily comes down to the timing. And we had even called out heading into the quarter that we did expect to see somewhat of a unique dynamic in the billings growth rate between Q1 and Q2, but with the first half and second half being relatively consistent. And then we saw that even a little bit more pronounced because of that early renewal dynamic. So we called that out. And in terms of the impact, we saw about $7 million in early renewals included in that benefit to Q1 billings. That represents the roughly 400 basis points impact that I mentioned. That’s where that $7 million is and about $6 million of that comes straight out of Q2. So basically making that Q1 to Q2 impact a little bit more pronounced.
And then in terms of the halves overall, can now see that we expect a little bit more strength in the first half because some of those dynamics as well as that incremental conservatism that we mentioned related to the macroeconomic environment. So no big change relative to our original expectations other than the early renewal dynamics between the first and the second quarter.
George Kurosawa: Super helpful color. Thanks for taking the questions.
Operator: Your next question comes from the line of Jason Ader with William Blair. Please go ahead.
Jason Ader: Hi, thank you good afternoon guys. I just want to ask about seats. I think you called out a customer where there was good seat growth. Can you just comment overall on what you’re seeing out of seat growth and even some — if there’s any downsell or how that has trended for some of your customers. Thank you.
Dylan Smith : Yes. So overall, the trends that we’re seeing and the dynamic between seat growth and then pricing improvements have been pretty consistent with what we’ve seen over the last several quarters where seats are growing on a net basis, but pretty minor contribution to growth, most of that customer expansion is being driven by pricing increases, and we’ve seen that continue and expected to be the same, especially with the impact of Enterprise Advanced and the healthy pricing uplift that we see as customers upsell into that suite. And so that’s really the dynamic that we’ve been seeing pretty consistent over the past few quarters. But there’s a lot that we’re doing, especially with a lot of these new enterprise advance and AI-driven use cases that we do think open up some new opportunities to expand across departments.
Jason Ader: Okay. So just to be clear, it sounds like price is going to be a bigger driver of growth, let’s call it, over the next several quarters than seats. And if so, what do you think you guys need to do? Or you need to see I guess, on the seat side for you to be able to say, okay, we are starting to see an inflection on seat growth.
Dylan Smith : Yes. So that’s exactly right in terms of what we’re baking in to our expectations for this year with pricing and driving the lion’s share of that expansion. And then on the seat side, a lot we’re doing again around kind of the use cases that we are pushing Enterprise Advanced enables as well as with new logos and some of the go-to-market investments that we’ve called out as a way to reach kind of new customers and grow the overall seat base from there. And then certainly, as that dynamic evolves, we’ll be sure to provide updates in terms of what we’re seeing in the business. And then I’d also note, and as we’ve called out in the past, that seat growth and that net seat growth tends to be more closely correlated with the economic environment, whereas in good and bad, we continue to see steady and strong pricing improvements that seat dynamic is a little bit more sensitive to the overall macroeconomic environment.
Jason Ader : Very helpful. Thank you.
Aaron Levie : And I would just note that overall, to Dylan’s point, obviously, Enterprise Advanced is the primary focus, which is both driving the price per seat increase as well as expanded use cases. So we feel pretty comfortable about the momentum and overall spot that we’re in.
Operator: Your next question comes from the line of Michael Funk with Bank of America.
Michael Funk : One follow-up on the early renewals you called out earlier, 400 basis points of help in the quarter. Can you remind us what you’re expecting during the quarter? And then also, what are you doing to catalyze early renewals?
Aaron Levie : Yes. So for early renewals, the biggest driver that we saw in Q1 was really around the adoption of customers looking to adopt our AI capabilities, both with Enterprise Plus and now more and more with Enterprise Advanced, even though we’re early days. So that was the majority of those Enterprise Advanced sales that we saw in the first quarter were customers early renewing, looking to move and bring on those capabilities sooner than their scheduled renewal date.
Michael Funk : And then on AI, you mentioned earlier in the call, cost of AI inferencing dropping, and that’s helpful. So maybe two questions there. First, how should we think about cost of AI and compute impacting margin? You made some margin expectation comments earlier. And then as you land with customers with AI, is it still primarily smaller seat counts or customers still doing smaller use case testing? Is there wider deployment? Really just want know where are we in the spectrum of adoption with AI as they adopt your products?
Aaron Levie : Yes. So there are two parts of that. So on the AI inference side, we’ve just been very happy about the rate of like-for-like AI model improvements that we’re seeing from a cost standpoint. And that can show up in 2 ways. The first is that you can take an existing use case and it might just on a one-to-one basis, be cheaper on a kind of pretty regular basis every kind of 6 to 12 months at a minimum. The alternative is that you get a new capability unlock because you can — you either get the base model just is getting much better or you can use an existing model and do multiple passes through the model for better accuracy or more complex use cases. So depending on the use case, we have some things that quite literally, just immediately get cheaper for us and then other use cases where we start to unlock more powerful capabilities.
Both of those are driven by inference prices going down, which I think we’ve all kind of collectively seen. And that trend is alive and well right now, which is fantastic to see. And then on the rollouts, It’s a broad mix. We have a couple of benefits in our platform. So we’ve given — we’ve made Box AI for sort of base use cases querying documents, asking questions of data generating summaries of content. That’s now an included capability in all of our business plans on above. So customers really have an easy way to start to try AI, deploy it for really kind of core end user productivity use cases. And then we’ve got multiple upsell vectors either for your entire enterprise instance to be upgraded with Enterprise Advanced, and we sort of talked about the early strong momentum we’re seeing there or AI unit volume consumption for more either complex use cases or much more kind of high-volume use cases.
So you can already start to try it quite easily by just using some of the included functionality. And then we’ve got, again, multiple upsell pads that we’re driving customers through. So I think we’ve landed on a very strategic pricing model for our customers that they’ve been quite happy about. We’ve generally had very, very strong positive interactions with customers on that upsell motion because it is very logical. Enterprise Advanced unlocks a whole new set of features as well as kind of core AI use cases.
Michael Funk: And just to clarify the first question, the price performance, are they largely offsetting, so you say, margin-neutral from rolling out AI? Or is one greater factor than the other?
Aaron Levie : Well, we’ve called out that we are aiming to have AI relatively margin-neutral over at least the medium term, and then I think it only gets better from there. And so — but there’s — because we’re not directly charging customers on a kind of a per use case basis because some of our core AI functionalities included, it is sort of hard to exactly parse something as margin neutral without a dedicated kind of pricing line for it. I would just say, overall, as a company, we are intending to remain more or less margin neutral even as we bake in more AI functionality. And the reason that we can do that is because the cost of inference is dropping even as we add more capabilities to our customers.
Michael Funk: Thank you so much for your time.
Operator: Your next question comes from the line of Lucky Schreiner with D.A. Davidson. Please go ahead.
Lucky Schreiner: Thanks for taking my question. Congrats on the great quarter. Maybe just with all the recent platform innovation and the rapid advancements across the ecosystem, how is that impacting your ability to win customers migrating away from the legacy ECM providers that typically aren’t able to keep pace? Are you noticing an uptick in win rates in those deals early on. And maybe as a follow-up, how have you noticed the improvement maybe in the Box — in the market overall from customers, just overall customer awareness? Thanks.
Aaron Levie : Yes. So I think great performance on both of those topics. We’re seeing more customers elect to move and migrate to modern platforms for driving AI-driven workflows on content. We announced this partnership with DataBank, as folks remember at our Financial Analyst Day. That is a great example of a partner who works with a lot of the traditional document management environments out there and really is in a position to help customers accelerate their move to the cloud, and we are seeing great momentum with them as an example. Similarly, we’ve had strong momentum with folks like [Slalom] (ph) and other system integrators on similar use cases of customers that want to migrate or modernize their IT infrastructure and get content to the cloud, to be able to use AI on that content.
So that’s the first part. And then on the second part, we — if you just look at Q1 alone, and I mentioned this in the call, but just to be redundant, if you look at the announcements of Quad 3.7 in Q1, Grok 3.0, OpenAIs, Agent SDK, NVIDIA at GTC and a number of other announcements in Q1 from the AI ecosystem. Box was included in every single one of those. And then right at the start of the quarter at the tail end of Q1, Lomicon announcing the work that IBM and Box are doing together to bring Llama 4.0 to customers. So we have — we are sitting very naturally at the center of so much of the innovation happening in AI right now. And I think it helps that we’re not competing with any of the AI model providers. We are bringing together an ecosystem of all the leading AI to our customers.
So we act as a very natural kind of convening point for these AI models when customers want to be able to use data on — with any of these leading platforms. So I think the momentum is building around Box AI as a platform. And that’s certainly starting to show up in our brand. We’re seeing strong enterprise advanced pipeline begin to build. That’s effectively all AI-driven pipeline in terms of the use cases customers are unlocking. So overall, we’re really happy with the momentum.
Lucky Schreiner: Awesome. And then last question from me. You had a nice diversity of wins and expansions across industries. Anything to call out. I think the early renewals were especially, I guess, impressive to hear given the April volatility that we all experienced. And so maybe anything to call out on the pipeline from an industry perspective, given the macro backdrop and your recent partner go-to-market improvements? Thanks.
Aaron Levie : I think from an industry standpoint, no major shifts. We’re continuing to see strength in a lot of our — the core industries that we’ve talked about, especially spaces where the customer is in a regulated environment. Data is mission-critical for them. So one thing that can’t be underscored enough is, as you want to do AI on your data, all of the things that we’ve gotten very good at over nearly 2 decades of working in the enterprise become mission-critical. So how do I secure my content? How do I make sure it’s compliant? How do I ensure that only the right people have access to the data, especially via agent interactions. Our CTO has a great quote of AI agents can’t keep a secret. And so you never want to put your security in the agent part of the infrastructure, you want to ensure that data access controls are actually maintaining the security of your information.
And so you don’t want to be in a position where you’re trying to pack too much of that intelligence into the model layer, you want to pack that into the data plane and the architecture around that, which is what Box provides customers. So that then means that companies in life sciences or banking and public sector, health care, all of these types of industries that really have sensitive, mission-critical use cases are able to thoughtfully and safely deploy AI to their end users.
Lucky Schreiner: Appreciate the questions.
Operator: Your next question comes from the line of Josh Baer with Morgan Stanley. Please go ahead.
Josh Baer: Thanks for the question. Congrats on a great quarter. Aaron, I was hoping you could talk a little bit more about platform revenue, sure it’s still early days for AI unit consumption. But I was hoping you could comment a little more on early traction as well as anything else driving that platform revenue, and yes, just thinking about the targets to grow that approximately 30% looking ahead and how we’re tracking to that goal.
Aaron Levie : Yes. So overall, still very early in the AI unit adoption. Obviously, this just became available to customers in the past quarter. So we’re in the very early days of what that volume looks like. The deals are kind of a pretty wide spectrum of deal sizes. So it’s still in the kind of lumpy territory. So we’re not at a kind of a normalized point. But in terms of the kinds of customers and the use cases, just as we kind of think about industries and scanned use cases, we have everything from legal industry. We have public sector, we have universities. We have financial services players, advisers so really across the continuum and the most common use case right now just based on where the functionality is most robust is, I have a set of data, and I want to be able to run an AI agent or many AI agents across all that data to do some form of data extraction, data parsing on my content.
And so that could be looking through contracts to pull out critical details from contracts, taking bank statements to read and validate the information in the bank statement — some customers are doing the very early phases of image extraction, where you give the AI model could be hand written content or images from a construction site and be able to label all that data. So we’re seeing kind of healthy, early adoption. This is going to be a continued focus of ours, and we expect it to be a healthy contributor to our overall top-line over the coming quarters and years.
Josh Baer: Great. Very clear. Dylan, I was hoping you could just comment on early renewals. I appreciate all the color in Q1. I’m really just wondering when you guide and like thinking about do you embed, like what’s the assumption? Is it just for on-time renewals? Just thinking about early renewals contributed in Q4 as well in a positive way? Just wondering if it’s a trend, if it’s something that can continue to benefit and what assumptions you have in guidance?
Dylan Smith : Sure. So we do assume that there is some volume of early renewals and because we don’t have perfect line of sight into those, we tend to be fairly conservative. And to your point, that has been an area of outperformance a few times over the past year or two. So we do assume that we’re going to have some early renewals but not at the same rate as we saw over the past couple of quarters, especially because some of those were just customers who were looking to get the Enterprise Advanced as quickly as possible. Some of our most loyal customers who have been more familiar with that, but certainly optimistic that we’ll continue to see higher than historical volumes in those early renewals. And to the extent that becomes more consistent trends, then we would update those assumptions around early renewal volume as it relates to our guidance as well.
Josh Baer : Great. Thanks.
Operator: Your next question comes from the line of Pinjalim Bora with JPMorgan. Please go ahead.
Pinjalim Bora: Great. One question then I have a follow-up for Dylan. Aaron, as Box kind of integrates with different AI partners, OpenAI from Deep Research others. How do you make sure that the engagement with some of these external vendors versus your keeping the engagement within the Box platform because your — Box is also thinking of coming out with deep research. Right now, you can actually do Deep Research with OpenAI. So how do you think of that bifurcation? How are you monetizing the people who are doing Deep Research on box through OpenAI, for instance? And has that kind of proliferates beyond OpenAI and some other AI partners?
Aaron Levie : Yes. Great question. Something we think quite a bit about and spend a lot of time on. There’s — just to get Pin, for 5 seconds, there’s going to be this question for years and years, I think in AI, around kind of which layer of the stack do you occupy and what’s everybody’s role in this. And we sort of are going to occupy two parts of the stack. So if there’s like 2 or 3 or 4 layers, going down to the infrastructure, we’re in about 2 of them, which is we’re in the software plane for the end user interaction at the SaaS level. And then we’re in the data kind of platform plane as well as an API, either agentic APIs or regular APIs. And we want to basically have both of those execute as fast as possible and as much in tandem as possible because we are not going to be — no single company is going to decide where all of the user does its work.
It’s just not possible. And Bill Joy had this famous quote 35 years ago or whatever that said there’s more developers outside of Sun than inside of Sun. And so — or more smart developers, with the implication being like you just have to let 1,000 flowers bloom, you do not want to be in a position where you’re trying to kind of king make any particular experience or platform or use case. There’s just simply too much innovation happening. And so kind of similarly, your data is going to eventually need to flow to wherever the work is getting done. And no one platform will be able to control where that work is getting done because the Internet’s large, companies have too many different use cases they want to go and solve. So because of that, our focus is ensuring that we can agentically bring information to wherever the user is doing their work.
So there’s like no game theory where you could ever kind of contemplate closing off access to a particular platform, simply because the users want to be able to do the work where they want. And so given that, we kind of flip it and we say, okay, so then we should be everywhere and ensure that the customer never has to make a sort of kind of a core decision about where their content can be managed by virtue of where they want users doing work. We want to make sure that you can manage your content one place and ensure that it works everywhere. From a monetization standpoint, there’s a few different ways that gets monetized. Certainly, the end user seat gets monetized. And so to the extent that you have a user on ChatGPT, asking a Deep Research question, by definition, they have a seat that is sort of processing that.
And that’s where I get into this idea of AI agents can’t manage security. The end user still has to have access controls that allow them to access the content that is relevant for that Deep Research query. So there is no way to sort of game the system and sort of have all the data in one-end user account and have that show up to multiple users in ChatGPT, by definition, you need those two things to be aligned to ensure the proper security. So that’s how you monetize via seats. And then in this case, deep research is using our direct APIs. But as more and more use cases emerge, where you have a third-party system that wants to use an AI agent within Box, where we’ve announced partnerships with Salesforce Agent force and Google agent space and IBM kind of watsonx Orchestrate, as you have those use cases, that will be monetized via our AI unit volume.
So as you have more queries going into Box that are agentic in nature, then we’ll just charge on a per volume basis for those. So let’s say, you’re inside of agent force, inside of Salesforce and you want an AI agent to go extract metadata from documents, we will monetize that exactly the same way that we would monetize that if that workflow was driven directly in the Box product from an end-user standpoint. So we think we’ve got our bases covered. Obviously, over time, you might be able to argue, Okay, well, there might be a slightly different margin depending on the modality of the usage. But overall, we’re just massive believers that an open Internet is a better one. And interoperability is long-term always going to be better for us because the more places people want to be able to do work from and the more places they can successfully do that work from, the more need they have for an open and interoperable data platform connected to all those systems.
So if you just kind of compare the alternative world where everything gets closed down, and you only have 1 or 2 providers that’s actually a worse world, and it’s the one that we don’t think is going to happen because of how much kind of agent interoperability is starting to emerge. So that’s a little bit of the philosophy that we’re running with.
Pinjalim Bora: Makes a lot of sense. Thank you for the detailed number. One for Dylan. Dylan, when I look at the billings guide for the year, if — I did this math pretty quickly, but it sounds like in the — when you first gave the guidance, it was about 7% USD with 30 basis points of tailwind from FX. Now it seems like 9% USD with 340 basis points of FX tailwind. So it sounds like on a constant currency basis, you’re guiding billings down. What am I reading wrong? Because you had a very strong Q1, and I understand the early renewals, but why would that impact the full year? So is that largely driven by some of the prudence that you’re talking about? Maybe talk about the timing for the year.
Dylan Smith : Yes, that’s exactly right. So on that constant currency basis, down about 1 point. And some of that is just we round as we give guidance on an as-reported basis and in round numbers. And then a portion of that is, as we discussed just that incremental conservatism around the back half. And so that is the exact dynamic. I think you’re doing the math right. But overall, very kind of optimistic about what we’re seeing in the business and the trends and how kind of customer conversations are materializing, but did want to be kind of prudent with what we’re assuming in the back half of the year.
Pinjalim Bora: All right. Thank you.
Operator: Your next question comes from the line of Brian Peterson with Raymond James. Please go ahead.
Brian Peterson: Congrats on the strong start to the year, guys. So I’ll keep it to one. I know you answered the questions on industries before, but I know there’s been a lot of debate on what’s going on in the federal vertical. Anything that you guys would call out in terms of customer trends or pipeline? Any color there? Thanks guys.
Aaron Levie : Yes. So still a bit of a dynamic where I think we expect a degree of kind of caution on the federal side. We’ve put a lot of emphasis in our kind of state and local part of the business in the meantime. FedRAMP High, which obviously, we just got certified for is clearly going to be a sort of a net helper to the overall dynamic in the federal side because a lot of the use cases that will continue to get funded are those out of DoD and much more kind of highly sensitive use cases. So we’re now in a better position to go capture those. So I would still say dynamic environment and — but we are happy with FedRAMP High as a way to bolster that position, and we’re very happy about the kind of overall AI momentum that we’re driving.
Brian Peterson: Thanks Aaron.
Operator: And that concludes our question — concludes our question-answer session. I will now turn the call back over to Cynthia Hiponia for closing comments.
Cynthia Hiponia: Great. Thank you, everyone, for joining us today, and we look forward to updating you again on our next earnings call.
Operator: And this concludes today’s conference call. Thank you for your participation, and you may now disconnect.