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DATE
Tuesday, Aug. 26, 2025 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-- $294 million (non-GAAP) for fiscal Q2 2026, up 9% year over year and 7% in constant currency, surpassing guidance. (Fiscal period ended July 31, 2025.)
Remaining Performance Obligations (RPO)-- $1.5 billion in remaining performance obligations (non-GAAP) for fiscal Q2 2026, with 16% year-over-year growth.
Short-term RPO-- Increased 12% year over year, with the company expecting to recognize about 55% of total RPO in the next twelve months (as of fiscal Q2 2026, non-GAAP).
Billings-- $265 million, up 3% year over year, and up 6% in constant currency, exceeding flat growth expectations despite a 320 basis point foreign exchange headwind (non-GAAP) in fiscal Q2 2026.
Gross Margin-- 81.4% non-GAAP gross margin for fiscal Q2 2026, reflecting a 40 basis point year-over-year improvement in non-GAAP gross margin when excluding the prior year's data center equipment sales tailwind.
Operating Margin-- 28.6% non-GAAP operating margin for fiscal Q2 2026, an improvement from the prior year, and above guidance.
Net Retention Rate-- 103%, an increase from 102% in Q1 and the year-ago period, driven by seat growth and premium suite adoption in fiscal Q2 2026 (non-GAAP).
Suite Revenue Mix-- Suite customers accounted for 63% of revenue (non-GAAP) for fiscal Q2 2026, up from 58% in the prior year.
Number of Large Customers-- Nearly 2,000 customers each paying at least $100,000 annually as of fiscal Q2 2026, up 8% year over year.
Free Cash Flow-- $36 million in free cash flow.
Share Repurchases-- 1.2 million shares repurchased for approximately $40 million in fiscal Q2 2026; $112 million in buyback capacity remained as of July 31, 2025.
Enterprise Advanced Deals-- The number of Enterprise Advanced deals closed nearly doubled sequentially from Q1 to fiscal Q2 2026, exceeding internal goals.
Pricing Uplift-- Stated price improvements for Enterprise Advanced over Enterprise Plus met or exceeded the 20%-40% target in fiscal Q2 2026.
AI Solutions Impact-- Adoption of Box AI and AI-powered workflow features cited as main drivers for upgrades, larger deal sizes, and new use cases across industries.
Product Announcements-- General availability of enhanced Box AI extract agent and beta launch of the MCP server were introduced, alongside updates to the admin console, Box AI Studio, and AI units.
Product Partnerships-- Box AI Studio added support forOpenAI(PRIVATE: OPENAI)'s GPT-5, Anthropix’s Claude 4.1, and xAI’s Grok 4; new integrations and partnerships launched withOpenAI(PRIVATE: OPENAI) (ChatGPT),Amazon Bedrock(NASDAQ: AMZN),Salesforce(NYSE: CRM),Snowflake(NYSE: SNOW),IBM(NYSE: IBM), andDeloitte(PRIVATE: DELOITTE).
Guidance Raised-- Full-year revenue guidance (non-GAAP, fiscal 2026) increased by $5 million to a new range of $1.17 billion to $1.175 billion (about 8% year-over-year growth, or 7% in constant currency (non-GAAP)).
Fiscal 2026 EPS Guidance-- Non-GAAP EPS raised to $1.26–$1.28 for fiscal 2026, including a $0.04 positive impact from foreign exchange on non-GAAP EPS; guidance for non-GAAP EPS reflects a $0.03 increase over prior expectations, or $0.06 when adjusting for currency movements.
Leadership Changes-- Mark Whalen retiring as CRO; Jeff Newsom, formerly ofGoogle Cloud(NASDAQ: GOOGL), appointed CRO and head of global sales organization.
SUMMARY
Management highlighted a broad expansion of use cases forBox(BOX -0.46%)’s AI-powered automation and workflow capabilities, citing customer adoption across legal, industrial, and hospitality sectors. The shift toward larger, more valuable deals in segments previously unaddressed was directly attributed to Enterprise Advanced and Box AI, with increased price per seat and net seat growth called out as key contributors (non-GAAP) in fiscal Q2 2026. New product features, such as the MCP server, were introduced to enable cross-platform AI agent workflows and integrations with leading model providers, positioning Box for increased adoption in complex enterprise environments. Customer commitments to multiyear contracts were described as strengthening, coinciding with record revenue contribution from suite customers in fiscal Q2 2026. Box outlined ongoing investments in security, compliance, and governance enhancements, emphasizing their role as differentiators for customers entrusting sensitive enterprise data. The call underscored a market-facing strategy centered on deepening AI partnerships, accelerating product development, and expanding API-driven workflow automation into customer and partner ecosystems.
Levie said, "Our pricing improvements for Enterprise Advanced over Enterprise Plus remain at or above our target of 20 to 40%."
Smith noted, "Q2 billings of $265 million were up 3% year over year and up 6% in constant currency, exceeding the company’s prior outlook for flat billings (non-GAAP)."
Demand from new and upgraded customers was supported by a doubling of Enterprise Advanced deals sequentially in fiscal Q2 2026 and a steady 3% annualized churn rate.
Box’s CFO confirmed a $0.58 non-cash deferred tax expense would be a non-GAAP EPS headwind.
Suite customers now contribute the majority of revenue, a structural shift up from 58% in the prior year to 63%.
INDUSTRY GLOSSARY
Remaining Performance Obligations (RPO): The sum of billed and unbilled revenue contractually committed by customers but not yet recognized, indicating future revenue visibility for SaaS companies.
MCP Server: Box’s Managed Content Platform server product enabling external AI agent systems to access unstructured data and content within the Box platform via APIs, supporting federated workflows across third-party AI environments.
FedRAMP High: The Federal Risk and Authorization Management Program’s highest security authorization, required for U.S. federal agencies managing highly sensitive data in the cloud.
AI Agent: Autonomous software powered by generative AI models tasked with performing or automating complex enterprise business workflows involving unstructured data.
Full Conference Call Transcript
Aaron Levie, Box Co-Founder and CEO, and Dylan Smith, Box Co-Founder and CFO. Following our prepared remarks, we will take your questions. Today's call is being webcast and will also be available for replay on our Investor Relations website. 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 third 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, and operating leverage, future profitability, net retention rates, remaining performance obligations, revenue and billing, 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, 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 and documents we filed with the Securities and Exchange Commission, including our most recent quarterly report on Form 10-Q for information on risk 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, August 26, 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 non-GAAP financial measures.
These non-GAAP financial measures should be considered in addition to and not as a substitute for, in isolation from, our GAAP results. You can find additional disclosures regarding these 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, and thanks, everyone, for joining us today. We delivered a strong second quarter with results above our guidance. Reflecting continued growth customer adoption of 9%, or 7% in constant currency, and RPO growth of 16%. Operating margins in the quarter were 29% with EPS of $0.33, $0.02 above the high end of our outlook. We had strong momentum in Q2 in customer adoption of Enterprise Advanced, which brings together our most powerful intelligent workflow capabilities in one plan. Examples include a prominent US law firm that became a new customer to Box, driven by enterprise advanced AI-powered metadata extraction capabilities and intelligent no-code apps to power its business processes.
This is an enterprise-wide agreement replacing both an existing cloud-based platform vendor and an eSignature company. In partnership with a systems integrator, a Fortune 500 hospitality chain upgraded from a non-suite plan into Enterprise Advanced as they move away from a manual process with multiple systems to manage global projects. The company is looking to use AI-powered metadata extraction, Box Hubs, DocGen, and Relay, in design and planning workflows to scale projects and streamline execution. And a global industrial automation company upgraded from Enterprise Plus to Enterprise Advanced and expanded seats as they look to centralize their contract management solutions, automate quote generations, and enhance cross-entity document searchability.
The company will use AI-powered metadata extraction to capture contract renewal dates and legal obligations to inform decision-making and ensure compliance. In addition to the accelerating momentum in Enterprise Advanced, Enterprise Plus continues to drive customer demand and remains a strong revenue growth driver for Box. In the second quarter, we saw customer upgrades and new logo wins, driven by our enhanced Box AI solutions, such as AI-driven multidot queries, Box AI content generation using advanced models, AI-powered content portals with intelligent hubs, and automated controls and protections against threats and data leaks. These Q2 wins demonstrate what I have heard from the hundreds of customer engagements that we had in the quarter.
Enterprises know that AI agents are going to bring a new level of automation and deliver deeper business insights to their businesses. Software has historically been good for automating that deal with structured data. Think payroll, CRM systems, accounting, HRIS, or supply chain workflows. This is where data fits neatly into rows and columns in a database. But the vast majority of enterprise workflows revolve around unstructured data, which actually represents about 90% of our corporate information. These are the workflows that drive client onboarding at a bank, M&A deals that get closed, contracts getting agreed on, clinical research advances, moving getting made, and so much more.
We've never been able to bring automation to these areas of work because they've been human-based, manual processes dealing primarily with unstructured data. Now for the first time ever, we can bring automation to this work with AI agents. With AI agents operating on unstructured data, enterprises can now accelerate product development processes, automate end-to-end hiring and training workflows, service insights, automate clinical studies, and speed up loan applications for better client engagement. We can imagine a future where there are over 100x more agents than people inside of an organization. Where any task you want done in a company is only a matter of how much compute you want to throw at the problem.
You'll have agents running in the background and in parallel, for any workflow around content that you can imagine. However, most companies can't tap into the full power of AI agents on their unstructured data because their enterprise content is fragmented or stuck in legacy repositories. And with this fragmentation, means that AI agents have no core source of truth from which to answer questions about critical topics. It also means there's a risk that access controls are unmaintained, which can lead to AI agents leaking data to the wrong users asking a question. And finally, it becomes a massive nightmare integrating systems that don't play nice with one another in the AI era.
With the Box intelligent content management platform, customers have a single source of truth to power the critical workflows for their most important content. And with an AI platform that delivers agents built right in and integrated all of our customers' agent ecosystem. Importantly, Box AI agents work directly on top of the workflows that customers have already built on Box. And we're only accelerating what these combined capabilities can deliver going forward. We're already seeing the power of AI agents with customers building Box AI agents that can review and summarize documents, answer questions from a large dataset, and extract critical details from enterprise documents like contracts or invoices. To orchestrate processes in legal, finance, healthcare, and more.
Now to build on this continued momentum, in Q2, we announced all new updates to Box AI capabilities. Including the general availability of Box's new enhanced extract agent, and the beta launch of Box's MCP server. These releases along with key updates to the Box AI admin console, the Box AI Studio, and AI units empower users to operationalize AI with the confidence and control that businesses demand. Our flexible and interoperable platform has been a major differentiator for Box and is just as important, if not more critical, in the age of AI. We partner with the broader AI model ecosystem to ensure customers have the choice of any model provider they want to work with.
Being neutral to the AI models means that our customers get access to the best AI capabilities applied directly to their content. We have announced support for OpenAI's GPT-5, Anthropix's Claude 4.1, and xAI's Grok 4 in the BoxAI Studio. Often on the day of the launch of this new model. In addition to supporting these new models on our platform, we've integrated with the broader product and partner ecosystems, OpenAI has integrated Box directly into ChatGPT for content access, Box partnered with Anthropics Financial Analysis Solution, We served as a launch partner for Snowflake's OpenFlow capability. Collaborated with AWS Bedrock agent core runtime, and partnered with Salesforce as a part of their MCP partner network.
We had a strong quarter of execution on our product roadmap and technology partnerships. But what I am most excited about is our journey ahead. We have quite the roadmap in store for the second half of the year. First, we will be delivering all new workflow and no-code app capabilities to help customers automate their most critical workflows around content enhanced by the power of AI agents. We are making it easier than ever for companies to leverage Box to power their business processes, whether that is automating how they work with their contracts and digital assets, or leases clinical research.
Next, we are continuing to enhance productivity by bringing the full power of Box AI to Box's core collaboration features. We will introduce all new AI features within Box Notes, continued improvements for leveraging Box Hubs, as an intelligent knowledge portal, and all new core Box AI experiences to make it easy for customers to interact with AI agents and find information across their Box accounts no matter what they're looking for. And all of these AI agent capabilities will be available via our API, so customers can take full advantage of summarizing, analyzing, and extracting data from their content any partner application.
Like Salesforce Agent Force, ServiceNow Agent Fabric, Google's agent space, ChatGPT, Claude, Copilot, IBM's Watson x Orchestrate, and more. And with our newly GA'd remote MCP server, customers can interact with the full Box API and AI agents as tools within their own AI-oriented applications. Finally, all of this is only possible because customers entrust Box with their most sensitive and important enterprise data. Especially in a world where AI agents can accidentally leak corporate data, when security permissions are not maintained, Box's security functionality will become even more important for our customers.
To continue to maintain and build that trust, we will advance our powerful security, governance, compliance, and data protection capabilities with all new features, core security improvements, archive updates, and more. We'll be sharing much more at this year's BoxWorks in San Francisco. And it's gearing up to deliver our biggest set of launches as a company. Now turning to go to market. We will be continuing to focus on driving the adoption of Enterprise Advanced, In Q2, we nearly doubled the amount of deals we closed over the prior quarter. Exceeding our internal goals. And our pipeline continues to build nicely.
Our pricing improvements for Enterprise Advanced over Enterprise Plus remains at or above our target of 20 to 40%. As we've discussed, going to market with partners remains a critical of our go-to-market strategy. As we power more advanced solutions for customers. We continue to see notable partner-led wins with enterprise advanced as we go deeper into our customers' critical business processes. As we continue to grow our relationship with important partners worldwide, we are pleased to announce that Deloitte will be a title sponsor for BoxWorks 2025. Other notable sponsors include AWS, Google Cloud, IBM, Salesforce, Swalom, and more. Finally, I want to share that our current CRO, Mark Whalen, has announced his retirement.
We are incredibly grateful for Mark's role in scaling Box to over $1 billion in annual revenue during his tenure. Helping us navigate the launch of suites, enterprise advanced, and much more. I'd like to share my deepest thanks to Mark for his incredible contributions over the past six years to Box, and for leading a smooth transition of the CRO role. With that, we are excited to welcome Jeff Newsom to Box as our new chief revenue officer. Heading our global sales org. Jeff is a highly regarded go-to-market executive with over two decades of experience leading sales organizations and enterprise software, cloud infrastructure, and AI.
Jeff is joining us from Google Cloud where he spent over six years as a key leader driving the business's rapid growth and scale. Driving new logo growth, and significant customer expansions of their portfolio, of cloud infrastructure and AI services. Jeff has also held various senior leadership roles at Oracle SAP, and Workday. Jeff is a perfect fit for the next chapter of Box's growth to $2 billion in revenue and beyond. He is joining us at a foundational moment for Box. As our platform evolves to deliver intelligent content management into our customers' most important workflows and processes all powered by AI.
Now before I turn it over to Dylan, I want to share how we're operating as an AI-first company. The objective of going AI-first is simple, move faster and deliver more value customers. We want to make decisions more effectively and quickly, drive more output, accelerate our roadmap, and better serve customers. To that end, we're equipping every boxer with the skills and tools to be productive with AI. Encouraging experimentation, scaling best practices across the company, and adding AI-first expectations in our hiring process. Across all of Box, we are using Box AI agents to augment our work in every area of the business.
From how we train and enable new sales or support reps to how we write product requirements or generate rapid account research industry insights for each customer we sell to. AI agents are being used all across Box, to help accelerate our workflows and drive increased productivity. We are incredibly excited about the opportunity ahead of us. And we will be discussing many more of our advanced features and the future of Box and our intelligent content management platform at our upcoming customer conference, BoxWorks, 2025 on September. In San Francisco. With that, let me turn the call over to Dylan.
Dylan Smith: Thanks, Aaron. Good afternoon, everyone. Q2 marked another quarter of strong execution as we exceeded guidance for all metrics, and delivered both double-digit short-term RPO growth and a sequential improvement in our net retention rate. We also made significant progress against our FY '26 priorities. We advanced our leading intelligent content management platform by enhancing our AI and agentic capabilities while investing in key go-to-market initiatives to drive enterprise advanced momentum. Finally, we're generating efficiencies across the business, and we continue to on our disciplined capital allocation strategy. As Aaron discussed, we have a significant opportunity to transform how enterprises work with their content and our Q2 results demonstrate the power of our balanced financial model.
We delivered Q2 revenue of $294 million above the high end of our guidance. This accelerating growth was up 9% year over year and up 7% in constant currency. We now have nearly 2,000 customers paying us at least $100,000 annually up 8% year over year. Suite customers now account for 63% of our revenue, up from 58% a year ago. This improvement was driven by momentum in Box AI and Enterprise Advanced, which enable more of our customers to adopt Box for higher value use cases. We ended Q2 with remaining performance obligations or RPO of $1.5 billion, a 16% year-over-year increase both as reported and in constant currency.
Short-term RPO grew 12% year over year as reported and in constant currency. These results reflect the impact of Box AI adoption on our business which is driving strong underlying business momentum and giving our customers the confidence to increasingly commit to multiyear contracts. We expect to recognize roughly 55% of our RPO over the next twelve months. Q2 billings of $265 million were up 3% year over year and up 6% in constant currency. This growth exceeded our expectations of flat year-over-year billings even as we absorbed an FX headwind of approximately 320 basis points versus our prior expectations. Q2 billing strength was driven by a combination of Q2 bookings, early renewals, and outperformance in our Box Consulting business.
We ended Q2 with a net retention rate of 103%, an improvement from 102% in Q1 and in the year-ago period. Our annualized full churn rate remained steady at 3%. We've been pleased to see customers upgrade and expand into our Enterprise Plus and Enterprise Advanced plans to gain access to our enterprise-grade AI and advanced workflow capabilities. As a result, our net retention rate continues to benefit from consistent price per seat increases and we're now seeing net seat growth contribute more materially as well. We continue to expect a net retention rate of 103% exiting FY 2026. Q2 gross margin was 81.4%.
Excluding the tailwind from data center equipment sales in Q2 of last year, this represents an increase of 40 basis points year over year. Q2 gross profit of $239 million was up 9% year over year, consistent with our revenue growth rate. We delivered Q2 operating income of $84 million and operating margin of 28.6% both above guidance and an improvement year over year, despite the tougher comparison due to data center equipment sales. In Q2, we delivered EPS of 33¢, $0.02 above the high end of our guidance. I'll now turn to our cash flow and balance sheet.
In Q2, we generated free cash flow of $36 million and cash flow from operations of $46 million up 927% year over year, respectively. We ended Q2 with $760 million in cash, cash equivalents, restricted cash, and short-term investments. In Q2, we repurchased 1.2 million shares for approximately $40 million. As of July 31, 2025, we had approximately $112 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 Q3 and FY 2026 guidance. As a reminder, approximately one-third of our revenue is generated outside of the U.S.
With roughly 65% of our international revenue coming from Japan. Before providing guidance, I wanted to remind you of tax impacts we mentioned on our last call. We expect that the noncash deferred tax expenses will be a non-GAAP EPS headwind of $0.58 in FY '26. For the 2026, we expect Q3 revenue to be in the range of $298 million to $299 million representing approximately 8% year-over-year growth. This includes an expected tailwind from FX of approximately 80 basis points. We anticipate our Q3 billings growth to be approximately 10%, This includes an expected tailwind from FX of approximately 200 basis points. We expect Q3 gross margin to be 81%.
Anticipate our Q3 non-GAAP operating margin to be approximately 28% versus 29.1% a year ago. Note that in Q3 of last year, operating margin included a 70 basis point benefit from data center equipment sales. As a reminder, this year, our annual customer conference, BoxWorks, has moved from Q4 to Q3. This shifts approximately $3 million in expenses into Q3 representing an additional 100 basis point headwinds to operating margin when comparing to the year-ago period. We expect our Q3 non-GAAP EPS to be in the range of $0.31 to $0.32 which includes an expected tailwind of approximately $0.01 from FX. Weighted average diluted shares are expected to be approximately 150 million.
For the full fiscal year ending January 31, 2026. We are proud to have delivered strong first-half results driven by customer demand for our enterprise-grade AI capabilities, translating into the momentum we're seeing in Enterprise Plus and Enterprise Advanced. As a result, we are raising our revenue expectations for the full year by $5 million to $1.17 to $1.175 billion, an increase of approximately $8 million adjusting for currency movements since our prior guidance. This represents approximately 8% year-over-year growth or 7% in constant currency. We now expect a tailwind of approximately 90 basis points from FX, 30 basis points lower than our previous expectations. We still expect our FY '26 billings growth rate to be approximately 9%.
This includes a tailwind of approximately 230 basis points from FX down from our previous expectations of a 340 basis point tailwind. 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 10 basis points from FX. We now expect FY 2026 non-GAAP EPS to be in the range of $1.26 to $1.28 including an expected tailwind of approximately 4¢ from FX.
This represents an increase of 3¢ for our prior expectations and an increase of 6¢ adjusting for currency movements since our previous guidance. Weighted average diluted shares are expected to be approximately 150 million. Our Q2 results demonstrate the strong business momentum we're seeing driven by customer demand for Box AI and Enterprise Advanced. This year, we will continue to invest in our intelligent content platform, key go-to-market initiatives, and our balanced financial model positions Box to capitalize on the AI-driven ahead in enterprise content. With that, Aaron and I will be happy to take your questions. Operator?
Operator: At this time, I would like to remind everyone, in order to ask a question, please press star then the number one on your telephone keypad. Your first question comes from the line of Steve Enders with Citi. Your line is open.
Steve Enders: Okay. Great. Thanks, Jerome. Thanks for taking the questions here. I guess maybe just to start on the momentum you're seeing in enterprise advance. I mean, how much of the billings upside should be kind of attributed to that or is this deal environment getting better? Can you just help us think through what actually drove the upper outperformance here?
Dylan Smith: Yeah. So I would say it's hard to parse out how much is coming from Enterprise Advanced and Enterprise Plus, as those are really the core drivers given the demand for AI around our overall business momentum. And has an impact on really all of the factors that we called out as what's driving the outperformance. So for billings in particular, came down to a combination of strong bookings overall, strong outcome in our Box Consulting professional services business, as well as some impact from early renewals. And all three of those factors are really influenced by the types of deals that we're increasingly selling because of our AI capabilities and Enterprise Advanced.
And so we'd really point to that momentum as the biggest change in what we're seeing around the business and really not a function of anything that we're seeing for an overall macroeconomic or deal environment standpoint.
Steve Enders: Okay. That's helpful. And then I guess, maybe thinking through some of the pipeline dynamics and thinking through the enterprise advanced opportunities you're seeing, just how is it maybe expanding the kinds of use cases? Or if you look through the pipeline and what's coming through, how are maybe the sizes of the opportunities different from what you've seen historically here?
Aaron Levie: Yeah. So I think the unique thing that we're seeing kind of across all of the Enterprise Advanced deals is really a core focus on being able to use some combination of AI agents and workflow automation together. And the first big use cases are really around things like data extraction. So you want to be able to take in a large amount of documents, invoices, contracts, lease agreements, and extract critical metadata from that and then be able to run some kind of workflow or have dashboards that let you go in and look at or analyze that data. So that's been a big use case.
There's been another kind of increasing use case around using the AI Studio to create custom agents for employees to be able to interact with knowledge or be able to interact with their data with those agents. And then what those have in combination or as an effect of those two capabilities is really things like the deals are now getting bigger in segments maybe where we wouldn't have even seen as larger deals. So we had some great examples of deal sizes that were multiples of what they could have been kind of pre-Enterprise Advanced because the customer wouldn't have had the types of use cases be solved in a prior plan.
So talk a lot about, obviously, the 20 to 40% price per seat uplift, but that doesn't fully even capture the fact that we might be doing deals that capture more users or that we wouldn't have even sold previously without Enterprise Advanced's functionality. So customers buying Box to be able to power again a contract management life cycle, digital asset management. Being able to process medical information and extract critical data from that. It's really going to get us into, I think, a much broader set of use cases. Where Box obviously traditionally has been for secure collaboration and document management. Now we can drive much more into intelligent workflows and automation as well.
Steve Enders: Okay. Perfect. That's great to hear. Thanks for taking the questions.
Operator: Your next question comes from the line of Lucky Schreiner with DA Davidson. Your line is open.
Lucky Schreiner: Great. Thanks for taking my questions, and congrats on the quarter. Maybe to start, it was interesting to hear that NetSeek growth is starting to contribute more materially, especially in this environment.
Dylan Smith: Is that really just because Enterprise Advanced is more relevant to more users across your customers, or help me understand what's driving that seat growth here this quarter?
Dylan Smith: Yeah. That's exactly right. Just as Aaron hit on, it really is the use cases and types of users and departments now that have really high-value use cases on Box because of both Enterprise Advanced as well as Enterprise Plus, both of which have pretty robust AI capabilities. So that's really the biggest dynamic we've been seeing recently that is causing a bit of a rebound in that net seat growth metric.
Lucky Schreiner: Awesome. And then the upgrade straight to Enterprise Advanced was also interesting to hear. Is that better than you expected? Like, how common are you seeing that? And are you able to provide any color on maybe the pricing uplift there when that happens?
Dylan Smith: Yeah. So when you have a straight upgrade to Enterprise Advanced, you know, we tend to see relative to just using the core service non-suites, call that rough doubling, sometimes a little more, a little less based on relative to what they'd be paying versus that 20 to 40% uplift when going from Enterprise Plus to Enterprise Advanced. And we have been pretty pleased with the momentum there, especially given how early we are in the overall rollout of Enterprise Advanced.
Aaron Levie: Having just made that generally available back in January. So we'd certainly expected and had seen the significant majority of those deals to be with existing successful Box customers who already had a lot of data and the sense of the types of workflows they put on the Box but certainly pleased with the momentum that we're seeing from customers who are going straight into Enterprise Advanced.
Lucky Schreiner: Great. For taking my questions.
Operator: Your next question comes from the line of Taylor McGinnis with UBS. Your line is open.
Taylor McGinnis: Yeah. Hi. Thanks so much for taking my questions. Maybe just when we think about the outperformance in 2Q, can you comment on how much of that might have been related to some of these early renewals? Because if I'm doing some of the math right, it looks like the implied constant currency guide assumes a bit lower of billings growth on a constant currency basis in the second half. So just given the momentum that we've seen in the first half of this year and some of the strength you guys are seeing on the AI side.
Maybe you could just walk us through then how we should think about that momentum as we head into the second half and what's implied in the guide especially in four keywords. Seems like there's a little bit more of a drop-off. Thanks.
Dylan Smith: Sure. So, looking at those three factors that we had mentioned in terms of what's driving the outperformance, the good thing about them is that all having a roughly similar size impact. You know, a few million dollars each, in terms of the outperformance. And then as it relates to the back half, I would say, you know, as always, we want to be prudent with respect to the expectations we set as much as we're really pleased with the momentum that we're seeing in the business. And you see some of that flowing through to our increased expectations for the full year, there's still a lot of moving pieces out there and a pretty challenging environment.
So I wanted to be prudent there, especially as we're always going to see some quarter-to-quarter variability with respect to overall billings.
Taylor McGinnis: Perfect. Thanks. And then just a follow-up would just be on the point uptick in NRR and the comments that you made earlier about seeing it sounds like a little bit of recovery on the seat expansion side. So just curious, like, you know, you think through the momentum that you're seeing on that front and how that could build as we move throughout the year and impact NRR, like any color you can give there. Like, when you look at going from 102 to 103, was that largely driven by an uptick in fee expansions and how do we think about that as we move throughout the year? Thanks so much.
Dylan Smith: Yeah. So the change, as mentioned, was driven by the seat growth and the recovery we're seeing there. We continue to see steady improvements in our pricing. Especially given the momentum that we're seeing with customers upgrading to our premium suites. And then over time, we do expect once we get through this year, for that net retention rate to continue to improve as we march down the path toward that double-digit overall growth.
Operator: Thank you so much. Your next question comes from the line of Matt Balik with Bank of America. Your line is open.
Matt Balik: Great. Excellent. Thanks for the question. It sounds like the metadata extraction capabilities are really resonating well. Some of those Enterprise Advanced early adopters. But curious if you could comment a little bit more understanding it's early. How are the use cases evolving as users of Enterprise Advanced get more comfortable? What do you see as the next natural step as customers get comfortable with the metadata extraction, etcetera?
Aaron Levie: Yeah. So some of this, we're going to have some and share some major announcements at Box so I'll have to keep it a little bit high level. But if you think about all of the unstructured data that an enterprise has, you can kind of almost just think about every job function in a business as a way to quickly understand the scale that we're talking about. It's in the legal team, it's contracts. In finance, it could be invoices. And any collections data and financial documents in product management and engineering, it's product specifications, code. In sales and marketing, it's marketing assets and sales pitches.
Well, all of that data has an immense amount of underlying value to the enterprise, but they can really only tap into it over and over again if they understand what's inside that information. And so many customers are coming to us and saying, okay. We'd like to be able to run AI agents on that data to extract the critical details from those contracts or those invoices or healthcare data that might be coming in. And then we want to be able to automate some of the workflow or business process that's tied to that data. So this could be a client onboarding process. Could be a lease agreement review process. It could be a loan origination process.
The first step is to get and extract the metadata from those documents. And put that into a structured database or data store, which is something that Box has had for many years. And then be able to go and automate a workflow. So the first step of that workflow automation is usually things like building a Box app, being able to view all that data, and then have users that can go and consume and analyze the information through the Box app.
But more and more, you're going to expect to actually run and automate the full workflow with agents running in the background moving documents through the various steps in that workflow, reviewing documents, probably making recommendations of what's the next step or what's the next best action for that document. And those are the next set of capabilities that we'll be sharing a bit more about later. But you can see how it's all coming together within this full ecosystem of AI agents plus workflow automation around all of your unstructured data.
Matt Balik: Really helpful. And then one just quick follow-up if I could here. It seems like you're doing a lot of great work on the MCP server side. Maybe just help us understand the broader for that in the medium term.
Aaron Levie: Yeah. So we kind of imagine a future where you might have dozens, if not on the upper end of a large enterprise, hundreds of different AI systems that people are going to be working from. We obviously want to be the absolute best place to have you work with agents and unstructured data, but there's going to be just a tremendous number of other AI systems. You might have some users in ChatGPT. You might have some users in Claude. You might have some users in Copilot. Some users might be in IBM Watson x Orchestrate. And so there's a very real chance of, again, dozens or hundreds of these systems inside of organizations.
So then you, as an enterprise, have a decision. Do you replicate your data, your unstructured data across all of those systems, which is not only an incredibly costly problem, but it's also one that would lead to security risks and you have outdated information across those technologies. Or do you have a central repository that has your most important information and unstructured data that people can tap into from across all of those other environments? And so MCP server is basically this really compelling abstraction layer that makes it easy for the AI agents or AI systems on those external products to tap into the data that's within Box or the agents that are within Box.
And so what we just launched it, GA'd in August. But the core idea is that you can be inside of Claude, and you could say, please summarize my meeting note from that one meeting or a contract that I was working on. And, again, instead of you having to upload your data to Claude, it will just tap into the BoxMC server, find the information you're looking for, and then right in line where you were doing your work, you can access your data. And so this really just reinforces the power of your unstructured data. And highlights how many different platforms you're going to want to access that information from.
So we are just in the very early stages of what this looks like, but super excited about MCP and making sure that it's available to all developers.
Matt Balik: Fantastic. Thank you.
Operator: Again, if you would like to ask a question, press 1 and your telephone keypad. Your next question comes from the line of Josh Baer with Morgan Stanley. Your line is open.
Chris Candero: Aaron. Hey, Dylan. This is Chris Candero on for Josh here. There was a controversial report that came out last week from MIT that said about 95% of Gen AI pilots at companies are failing due to flawed enterprise integration and misalignment in resource allocation. But it seems like you all are having some early success here with Box AI and clearly some good momentum with Enterprise Advanced adoption. So curious if you have a take on that and maybe what are some of the early lessons you all have learned at Box as you've driven this adoption of Box AI in advance so far?
Aaron Levie: Yeah. So a couple interesting things. So I think one of the it was actually interesting in that same report. It actually called out the delta between when customers adopted a sort of a best of breed or prebuilt solution versus when they tried to build their own homegrown AI system from scratch.
And that's sort of one thing that we've been trying to politely educate the market on for a year or two now, which is the idea that an enterprise with all of their data is going to get their data in a storage environment, do the vector embeddings on all of that data, put that into a vector data store, manage the permissions across every single user that needs access to that information, then have a user interface that is incredibly modern and up to speed with all of the latest breakthroughs in different UX paradigms. Then be able to stay on top of all of the different AI model breakthroughs across the four or five top model vendors.
You're talking about a very small number of enterprises that have the technology teams to be able to do that. And be able to justify the underlying ROI of making that work. Whereas with something like the Box AI platform, we just handle every single one of those capabilities in our platform. We obviously handle all the storage. We handle all of the getting the documents ready for AI. Putting them into a vector data store, doing the vector embeddings, working with every major lab for the latest AI model breakthroughs. And then we make that all available to you as an API. Or even more importantly as a simple end-user interface that anybody can interact with.
So you can just think about all of the different projects that are going on in enterprises. Where you have so many where people are trying to build up a lot of that infrastructure themselves. Or where you're deploying AI, potentially at not particularly high ROI use cases. Where then the adoption might not be there and people stop using it. We have been very focused on being hyper-targeted on things where we can either make end users just immediately more productive.
So asking questions across your data in a Box Hub, being able to summarize information very easily, or increasingly importantly, being able to extract that metadata at scale where we have customers obviously that are now beginning to do that at massive scale. So we've been very targeted. And, again, our solution out of the box really kind of derisks most of the reasons why AI projects will fail in an enterprise. I think that's led to certainly better, healthier conversations and early adoption rates on the platform.
But I do think that enterprises are going to spend quite a bit of time trying to figure out what is the right AI architecture, what are the AI solutions that are working, which ones actually are driving ROI? And our core focus is to make sure that we're continuing to partner with our customers on all of that.
Chris Candero: That's super helpful. Thanks, Aaron. And I also want to ask on the federal side. You all got the high authorization somewhat recently, and you had a federal summit. So I'm curious kind of what you're seeing within the public sector, the opportunities, how the pipeline is looking like?
Aaron Levie: Yeah. So I think things have our feeling is that things have, let's say, kind of settled down for maybe the first quarter or so of all of that broader transformation that we tended to hear about in the federal government. I think things are now aligned more toward a path of federal agencies being focused on IT modernization. You saw with the AI action plan from the federal government that there's a huge focus on bringing AI into the government. Box AI, as an approved service with FedRAMP high support working with all of the major model providers.
To be able to bring those models to work with enterprise content in the federal government, I think, is going to be extremely key. We're happy about the momentum and the conversations that we're having. We partner with the GSA to support their mission even further and make sure that we can make BoxAI and the Box platform available. Across our Enterprise Plus and Enterprise Advanced plans really specifically tailored to the federal government. And so I think we're in a good spot from a momentum standpoint from here. And we'll keep folks updated as that continues.
Chris Candero: Excellent. Thank you so much.
Operator: Our next question comes from the line of Brian Peterson with Raymond James. Your line is still open.
Brian Peterson: Thanks for taking the question and congrats on the strong performance this quarter. Aaron, I think you said that deals doubled sequentially. I'm curious, how does that normally compare second quarter to first quarter? And if we think about that step up, any perspective on how much of that was net new versus expansion, partner versus direct? Any perspective there?
Aaron Levie: Yeah. And just to clarify, that was the number of Enterprise Advanced deals that doubled. Ah. So early innings, but just the fact that we're seeing a nice compounding rate of growth, we're super happy about. And, again, it's across new logos and upsells, but we're just driving as much focus on Enterprise Advanced as possible.
Brian Peterson: Understood. I'll grab a coffee. Sorry about that. It's just all one, you know, as you think about adding to the platform, in AI, we're seeing all this adoption. I'm just curious if there's anything that's changed about your appetite for M&A. Thanks, guys.
Aaron Levie: Yeah. You know, we continue to always be super thoughtful about the product roadmap and where are the opportunities for additional M&A. As you know and everybody else on the call knows, we're very focused on being product-led as we think about our overall corporate strategy, but then even, especially our M&A strategy. So we think about what's our product roadmap, where do we believe we're better off with kind of organic development doubling down on our core architecture versus where do we really have a time to market requirement that necessitates doing M&A. And at the moment, I think we've largely been focused on that core doubling down.
We've got a great AI platform architecture that we're building off of. Even when we look at maybe startups in the space, we tend to find that our approach to the architecture is as modern as a startup that would be well-funded or getting started just today. So we have a very modern architecture for our AI agents. We're obviously partnered with all the major AI labs. We're building on a set of core workflow and automation scaffolding that will only get better and better. So we're pretty happy about the core platform that we're building on, and M&A would just be in areas, again, that we think we need to double down on or need extra support in.
So no change in strategy or appetite, and we'll keep you posted as things become relevant there.
Brian Peterson: Thanks, Aaron.
Operator: This concludes our Q&A session. I will turn the call over to Cynthia Hiponia for closing remarks.
Cynthia Hiponia: Great. Thank you, everyone. As a reminder, in conjunction with BoxWorks, our annual user conference on September 11, we are hosting an IR virtual investor product briefing from 1 to 2 PM Pacific time. This will feature Aaron and our senior product exec doing a deep dive on our product announcements from the day. And then we're hosting a live Q&A session directly after the presentation. Just go ahead and email Elaine or myself at [email protected] for further details, but we look forward to hearing from you there and talking again on our next call. Thank you.
Operator: Ladies and gentlemen, that concludes today's call. Thank you all for joining. You may now disconnect.