Asana, Inc.

Good day, and thank you for standing by. Welcome to the Asana first quarter fiscal year 2027 earnings conference call. At this time, all participants are in a listen-only mode. After the speaker's presentation, there'll be a question and answer session. To ask a question during the session, you'll need to press star 11 on your telephone. You will then hear an automated message advising your hand is raised. To withdraw your question, please press star 11 again. Please be advised that today's conference is being recorded. I would now like to turn the conference over to your speaker for today. Eva, Head of Investor Relations, please go ahead.

Good afternoon, and thank you for joining us on today's conference call to discuss the financial result for Asana's first quarter fiscal year 2027. With me on today's call are Dan Rogers, our Chief Executive Officer, and Asis Maggi, our Chief Financial Officer. Today's call will include forward-looking statements, including statements regarding the expected release and benefit of our product offerings and our expectation for revenue to be generated by those offerings, our retention and expansion opportunities, our expectation for our financial outlook, including our FY27 four-year guidance, strategic plans, including with respect to current or future M&A activity, our market position and growth opportunities, and our capital allocation, including our stock repurchase program, among other items. Forward-looking statements include risks, uncertainties, and assumptions that may cause our actual result to be materially different from those expressed or implied by the forward-looking statements. Please refer to our filings with the SEC, including our most recent annual report on Form 10-K, and quarterly report on Form 10-Q for additional information on risks, uncertainties, and assumptions that might cause actual results to differ materially from those set forth in such statements. In addition, during today's call, we will discuss non-GAAP financial measures. These non-GAAP financial measures are in addition to and not a substitute for or superior to measures of financial performance prepared in accordance with GAAP. Reconciliation between GAAP and non-GAAP financial measures and a discussion of the limitations of using non-GAAP measures versus the closest GAAP equivalents are available in our earnings release, which is posted on our investor relation webpage at investors.asana.com. And with that, I'd like to turn the call over to Dan.

We delivered a strong start to the year. With revenue of $205.1 million, up 9.5% year over year, and above the hand of our guidance. We also exceeded expectations on profitability with non-GAAP operating margin expanding up to 11.5%, up 720 basis points year over year. This reflects continued progress in driving both growth and operating efficiency across the business. Importantly, we're seeing positive trends across customer retention, expansion, and AI product adoption. We believe these are encouraging indicators of improving business health. One of the clearest indicators of this progress is net retention rate, or NRR. Our reported rolling four-quarter NRRs improved across all cohorts, while overall in-quarter NRR improved for the fourth consecutive quarter to 97%. This improvement was broad-based across both gross retention and expansion activity. This reflects a healthier seat adoption trend, improved customer engagement, and continued early traction from our AI products. In the technology sector, we returned to positive year-over-year growth for the first time in eight quarters. This is an encouraging sign that this vertical, that has been a headwind over the past couple of years, is now seeing improvement, driven by adoption across multiple products. Customers such as Corweave and Epson expanded with additional seats and AI products this quarter. Growth in non-tech sectors continue to outpace overall company growth. This reflects our diversification across industries and customer use cases. We continue to see strong engagement, where we tailor our solutions to customer-specific ICPs and industry workflows. During the quarter, customers, like one of the nation's premier consulting firms and a Fortune 500 industrial technology company, both expanded their seat deployment and adopted our AI products. International revenue grew 12% year over year, which outpaced the overall business, led by strong performance in both EMEA and APAC. We also added several notable customers during the quarter, including a British athletic apparel brand and IKEA Australia. These underscore the growing global demand for our platform and AI solutions. On reflection, our Q1 performance reflects the deliberate choices we made across go-to-market, and product strategies over the past several quarters. We're beginning to see measurable benefits from initiatives that have been focused on area monetization, customer retention, sales productivity, and operational efficiency. Within our product-led motion, while the business remains a near-term headwind to growth, our ongoing initiatives have us well-positioned for stronger long-term acceleration. Asana's strategy is to become the operating system for human agent teams. We've all experienced the personal productivity uplift from working with AI chatbots. But for many organizations, that has not yet translated into real productive uplift for their teams or their company. This is the great AI gap today. At Asana, we believe this real enterprise productivity unlock comes from humans and agents working together on critical workflows that run the business. We see four reasons. why most companies haven't yet crossed this great AI gap. Firstly, it's hard for teams to discover agents and to visualize their current processes and workflows. Number two, there's really no framework for individuals to interact with agents in a multiplayer mode with the rest of their teams. Number three, most agents aren't onboarded with context of how their teams operate and what they care about. Number four, CAOs and IT leaders are very worried about Agent Palooza. This is agents running a mock with full access to data and with very limited cost oversight. Asana is the solution. We are the operating system for humans and agents to workflow together. Let's address each of these four blockers. Firstly, with Asana, our agents, Asana teammates, they make themselves known offering to help you as you work so you can easily discover them and quickly visualize your workflows with no code builders. Architecturally, Asana is multiplayer from the get-go. This is a fundamentally hard concept to deliver. With Asana, it means all teammates can now train and improve the agents they work with, while agents learn ambiently from tasks and conversations with all of their human teammates. Number three, with shared memory and more than 20 ready-to-go agents across marketing, IT and operations, our teammates can scan all of the existing work in your work graph to pre-train themselves. Then, over time, they compound their learning, operating on a common enterprise ledger to stay coordinated. And fourth, because of our agents operating on the same coordination paradigm built for human collaboration, it's very easy to manage their data access. approve their actions, and provide cost guardrails. So what does this look like in practice? Imagine a manufacturing team launching a new product with Asana. Program manager might kick off a new product introduction process using our AI Studio workflow. Then that might invoke an AI teammate to create the project, draft the plan, and assign the workout. Some of those tasks might end up with humans engineers for example some might be delegated to agents to handle spec reviews and supplier checks as decisions get made the team teaches the agents what good look like and the next launch runs that much sharper this is engineering operations and marketing and agents all working of the same plan and moving together humans and agents moving work faster Looking at our AI products, it's been roughly one year since AI Studio became generally available, and the adoption trends continue to strengthen. Customers are embedding automations into their core operational workflows. AI Studio automates the repeatable work, like intake, classification, routing, quality checks, and reporting. And because AI Studio is no code and embedded directly into existing workflows, customers can deploy and scale it quickly. In fact, customers are embedding AI Studio automations into their business-critical workflows today, and this contributes to strong retention dynamics. Early data shows customers adopting AI Studio have higher retention and stronger net revenue retention relative to the broader customer base. The primary driver of NRR outperformance is seed expansion, not simply lower churn. Customers who embed AI Studio into their workflows are not only staying, they're expanding, adding seats, and deepening their investment in the platform. During the quarter, the number of customers spending over $100,000 annually on AI Studio nearly doubled. This includes expansion with one of the largest managed healthcare companies in the US and a multinational media and entertainment conglomerate. Now let's talk about AI teammates. Remember, these are the shared agents assigned to real projects, working alongside real people. What differentiates AI teammates is they operate within the shared context of Asana's enterprise work graph, with shared memory, governance coordination, and multiplayer mode across teams. These capabilities become increasingly important as enterprises move from experimenting with AI to operationalizing it across real businesses to deliver real productivity. While still early, we're encouraged by the initial customer response. Paid conversion from our beta cohort has been strong, and the productivity impact is tangible. In fact, tasks involving the AI teammate are now completed nearly nine times faster. Today, we offer more than 20 out-of-the-box teammates across functions including marketing, operations, and planning. Taken together, our AI product bookings now represent 17% of net new ARR in Q1. This is ahead of the pace required to achieve our 15% full-year target. What is particularly encouraging is the level of engagement we're seeing with our AI products across some of the leading innovators in AI, including Anthropic and CoreWeave. Anthropic has grown with Asana as they have scaled as a company. Building on their existing investments in AI Studio, Anthropic is also one of our newest AI teammates customers. and employees are now connecting CLAW directly into the work graph through Asana's MCP integration. CoreWave, a leading AI cloud provider, has expanded its use of Asana over the past two years, growing from 15 seats to more than 1,000 across teams. And they're now an AI teammates customer. CoreWave uses Asana across data center operations, IT, supply chain, technical program management, and marketing. In the next two customer examples, FedEx and COS, will demonstrate the operating system for human agent teams and what that looks like in practice. In both cases, Sana's powering business-critical workflows where humans and AI teammates work together with a shared context, shared memory, multiplayer mode, and governance enterprises require. FedEx purchased AI Studio last year. They joined the AI teammates beta at inception. and they've since deployed AI-powered workflows across marketing, sales, strategy, product, and operations, driving a 9x improvement in speed to market and hundreds of thousands of dollars of operational savings. Here's how it works in practice. FedEx Marketing uses AI Studio to consolidate intake from more than 24 forms into a single, intelligent workflow that analyzes submissions, removes duplicate work, and routes requests to the right strategy lead. AI TeamMates then picks up the work. It drafts go-to-market plans and creative briefs, reducing cycle time from weeks to days and reclaiming over 1,200 hours annually. Looking at sales enablement, FedEx Sales was fielding high-volume requests from global teams. With no standardized process for evaluating or sequencing work, requests were assessed manually and in isolation. making it nearly impossible to identify redundant efforts or coordinate across markets. With AI Studio, incoming requests are now automatically matched against the work graph to flag overlapping work and bundle together related initiatives before any human review. Intake review time dropped from 90 minutes to 30 minutes per request. From there, an embedded AI teammate generates go-to-market materials, competitive intelligence materials automatically. while automated portfolios handle cross-region sequencing in real time, so seller capacity flows to the highest priority launches rather than being managed through spreadsheets. And at the leadership level, FedEx deployed AI teammates across their global portfolios, achieving 100% visibility into global initiatives and reclaiming over 300 hours per year previously spent on manual alignment, compressing planning timelines from weeks to days. Looking at Coz. Coz is the global fashion brand within the H&M group. They deployed AI Studio and AI Teammates to automate campaign production across marketing, e-commerce, and regional teams worldwide. Using AI-powered intake and workflow automation, Coz automatically generates full campaign projects with more than 50 structured subtasks. They dynamically assign work based on asset type, region, and team capacity. And they manage cascading deadlines across the product lifecycle. preserving workflow context as work moves between departments. The quality check AI teammate then proactively reviews all completed assets, identifies issues before they cascade, and helps coordinate execution across their global teams. This results in a 90% reduction in campaign setup time for them, a doubling of asset output to more than 1,000 assets per campaign, and adds up to nearly 3,000 hours of annual manual work eliminated. to focus on strategic and creative execution. As Kost described it, Asana hasn't merely improved our processes, it has redefined how we work. We've established a unified and transparent ecosystem where all work is seamlessly visible. At Asana, we believe the great productivity unlock from AI comes when humans and agents work together in your business critical workflows. The stories we just heard from customers like FedEx and KOS show the huge increase in velocity and output that's possible when real workflows are optimized to the AI era. And as we all know, the most complex workflows don't stay with inside a single system. They span CRMs, contracts, ERPs, collaboration tools, and every platform where work actually lives. And that is why today we're announcing the acquisition of Stack AI. Stack AI is a privately held AI software company that offers a no-code AI workflow platform that enables organizations to design, test, deploy, and govern custom AI agents and intelligent automations within business-critical workflows. This platform connects workflows, data, and actions across enterprise systems to automate complex operational processes, such as customer support, IT service requests, compliance workflows, and broader cross-functional business operations at scale. Their customers range from small businesses to large global enterprises, with deployments spanning to more than 1,000 workflows running on the platform. Based in San Francisco, Stack AI has achieved commercial traction and built a strong roster of enterprise customers across industries, including within highly regulated industries where security, governance, reliability, and enterprise-grade controls are critical. Stack AI is the logical evolution of AI Studio and accelerates our roadmap by over a year. While AI Studio made it easy to create powerful automations around intake, routing, and request processing, Stack AI extends those workflows across the enterprise and data sources, enabling customers to orchestrate and automate more complex cross-functional workflows that span CRMs, ERPs, databases, support systems, contracts, and custom infrastructure. Now, Our customers are going to be able to quickly recruit ramped agents into their everyday work with AI teammates, create simple AI rules and automations with AI Studio, and orchestrate whole processes end-to-end with the power of Stack AI. Together, this allows us to deliver the operating system for human agent teams, delivering on the real productivity promise of AI. Now proof of concept with the Stack AI team. Our marketing team were able to gentrify a really complex SEO process. They created bi-directional integrations with five marketing data stores, summarized insights, then handed over to an AI teammate that had been trained by their human teammates to take action. Powerful stuff. We hope our customers are going to be as wowed as we were. The company is led by co-founders Tony Rossignol and Bernard Acetuno. both MIT PhDs and two of the sharpest minds shaping the future of the agentic enterprise. I couldn't be more excited to welcome Tony and Bernard and the entire Stack AI team to Asana. And I'm even more excited to introduce Stack AI to our customers. This is the orchestration capability enterprises have been asking for as their workflows grow more complex, more cross-functional, and more agent-driven. It's been almost a year since I joined Asana. And when I look at the business today, we're making meaningful progress against a very ambitious vision. Asana pioneered collaborative work management. Our next category defining opportunity is becoming the operating system for human agent teams. As organizations increasingly rethink how work gets coordinated and executed in a genetic world. We're executing with significantly greater focus, velocity, and operating discipline. We're shipping products faster, improving sales productivity, expanding margins, and going deeper with customers than ever before, which is reflected in our improving retention rates. And within the last year, we've become a true multi-product AI platform with the launch of AI studios, AI teammates, and now adding Stack AI into our portfolio. On June 4th, we're going to host our annual Marquee customer event, the Work Innovation Summit in London. There, we'll unveil our vision for the agentic enterprise, showcase the next generation of innovations across our AI products and our broader AI platform roadmap. We believe Wiz will mark an important moment in how customers in the market understand Asana's role as the OS for human agent teams. Following Wiz on June 8th, we'll host a webinar for investors and analysts focused on the future of human agent work and the role Asana's OS for human agent teams is going to play in enabling the self-driving enterprise. We'll showcase our latest product innovations and roadmap and demonstrate how customers are already realizing value from AI Studio, AI Teammates, and Stack AI. Additional details about the webinar will be available on our investor relations website shortly. With that, I'll turn things over to Aziz.

Thanks, Dan. Let me highlight the financial results for the first quarter and then comment on the outlook. Q1 revenues were at $205.1 million, up 9.5% year over year. This includes an approximately 70 basis point tailwind to revenue growth on a constant currency basis, 10 basis points higher than our original guidance. We have 26,103 core customers, which we define as customers spending $5,000 or more on an annualized basis. Revenues from core customers grew 10% year over year. This cohort represented 76% of our revenues in Q1. We have 817 customers spending $100,000 or more on an annualized basis, And this customer cohort grew 12% year-over-year. As a reminder, these customer cohorts are defined based on annualized gap revenues in a given quarter. Our overall dollar-based net retention rate was 96%. Core customer NRR was 97%. And among customers spending $100,000 or more, NRR was 96%. And as a reminder, our NRR is a trailing four-quarter average, and therefore a lagging indicator of more recent trends. As Dan mentioned earlier, we saw rolling four-quarter NRR improve across all cohorts, with in-quarter overall NRR of 97% improving for the fourth consecutive quarter. The improvement was driven by continued strength in gross retention and healthier expansion trends, reflecting broader multi-product adoption across the customer base, growing contribution from AI products, and continued seed expansion within our enterprise customers. We also continue to see benefits from the investments we have made in engaging customers more proactively earlier in the renewal process, driving higher seat utilization, mitigating downgrade risk with AI products, and ongoing improvements in CSAP, all of which are contributing positively to retention trends across our customer cohorts. Turning to our self-service business, our guidance continues to assume approximately a two-point drag on ARR growth from PLG, reflecting the ongoing shift in how customers discover and evaluate software as AI search and LLM-driven experiences continue to evolve. we're beginning to see encouraging early signals from the initiatives we've been driving over the past six plus months. This includes organizational trial starts trending up sequentially for the first time in over five quarters, alongside improved trial conversion and stronger product qualified lead performance. Our focus has been on improving acquisition quality, aligning the funnel toward customers with stronger collaborative intent and longer term retention characteristics and accelerating time to value. We also continue to see improving productivity across our sales organization. This is driven in part by investments in AI-powered prospecting and account planning tools. This also contributed to stronger sales efficiency and improved inbound pipeline generation. We also saw continued strong synergy between our product-led and sales-led motions through more targeted, higher-converting product-qualified leads that are being passed to our sales teams. Now moving to profitability, where I'll be discussing non-GAAP results in year-over-year comparisons. Our gross margin was 88%. R&D expenses were $47.5 million, or 23% of revenue, down 270 basis points. Sales and marketing expenses were $83.5 million, or 41% of revenue, an improvement of 20 basis points. And G&A expenses were $26.7 million, or 13% of revenue, an improvement of 360 basis points. We delivered an 11.5% non-GAAP operating margin, or $23.6 million of operating income. This represented a 720 basis point improvement year over year. Our results also benefited from approximately $3 million of operating expenses that shifted from Q1 into the second half due to the timing of spend related to our Work Innovation Summit events and their associated marketing campaigns. Net income was $24.4 million, or 10 cents per share, on a diluted basis. Our profitability improvements continue to be driven by operating leverage, disciplined allocation of spend toward our highest return go-to-market motions, optimization of infrastructure and cloud costs, and discipline around backfilling and headcount growth as we realize increasing efficiency benefits from AI across the business. In R&D, sales, marketing, support, and G&A workflows, we are deploying AI Studio, AI Teamates, and third-party AI tools to automate work, accelerate execution, and reduce manual coordination. One example is in our security team. The team could not scale headcount fast enough to keep pace with engineering, so they embedded AI teammates directly into their review processes. When a new feature is proposed, AI teammates automatically surfaces risks, prioritizes fixes, and collaborates with engineers before code is even written, with human reviewers finalizing each assessment. The result is 10 to 15 times greater security coverage without a corresponding increase in headcount. And at the same time, we continue to align our talent footprint with more cost-effective regions and organizational structures, creating a strong foundation for sustained efficiency, operating leverage, and multi-year margin expansion. Moving on to the balance sheet and cash flow. At the end of Q1, cash, cash equivalents, and marketable securities were approximately $424.6 million. Our remaining performance obligations, or RPO, were $518.1 million, up 23% year over year, and current RPO grew 18% year over year. This represents 79% of total RPO and will be recognized over the next 12 months. Year over year growth rates accelerated for both RPO and CRRPO relative to last quarter. Our total ending Q1 deferred revenue was $323.1 million, up 11% year over year. Building on our operating margins strength in Q1, adjusted free cash flow was $34.4 million in the quarter, or 17% of revenue on a margin basis. The stronger than expected free cash flow was partly due to earlier than expected collection activities in Q1, which we expect to normalize over the course of the year. This quarter, we bought back 45 million of our Class A common stock, or 7.4 million shares, at an average price of $6.11 per share. As of April 30, we have roughly $155 million available on our current program for future repurchases. We continue to believe repurchasing shares at current levels represents an attractive use of capital relative to the long-term value creation opportunity. We believe we can buy back shares while preserving the financial flexibility to invest in innovation, growth, and strategic opportunities. Now turning to our acquisition of Stack AI. We are excited about the long-term growth opportunity as we enable our go-to-market organization to bring these cross-system AI workflows to our customer base over time. The transaction includes approximately $75 million in upfront cash consideration, along with an additional equity-based earn-out opportunity. The structure was designed to support long-term retention and align performance with long-term incentives. The acquisition also adds approximately 50 highly talented employees across engineering and AI-focused go-to-market functions. This significantly strengthens our technical and go-to-market capabilities and accelerates execution against our AI roadmap. Importantly, even after adjusting our Q1 cash balance for the transaction, we would have over $350 million in cash and cash equivalents and marketable securities remaining on the balance sheet, which includes an assumption of $3 million of cash on Stack AI's balance sheet. Transaction does not change our existing share repurchase authorization or plans to buy back stock or retire our outstanding term loan at maturity. The transaction also does not change the directional assumptions we provided for stock-based compensation, which remain in the low 20s as a percentage of revenue for the fiscal year. We recognize that stock-based compensation and dilution remain elevated as we balance driving toward GAAP profitability, attracting and retaining top talent, and executing against what we believe is the strongest product roadmap in the company's history remain focused on proving our stock-based compensation as a percentage of revenue. The same operational improvements driving margin expansion combined with discipline around equity grants should drive down SPC and dilution over time. Before I walk through the guidance in detail, I want to reiterate that the core assumptions underlying the FY27 outlook we shared last quarter remain largely unchanged. First, PLG remains a near-term headwind, and our guidance still assumes approximately a two-point drag on ARR growth from this notion. Second, we continue to assume only modest improvement in net retention rates over the course of the year. Third, our guidance does not factor in the improvement we have seen in the tech vertical over the past two quarters, including the return to positive year-over-year growth we saw in Q1. Lastly, we are maintaining our expectation that AI product bookings contribution to net new ARR will represent approximately 15% in FY27. We are encouraged by the momentum we're seeing across our AI products with Q1 AI product bookings contribution to net new ARR coming in ahead of our expectations and Stack AI expected to provide incremental AI contribution going forward. Instead of making incremental updates to our full year AI product contribution assumptions each quarter, We will provide a comprehensive outlook during our Q2 call. This timing allows us to evaluate a full quarter of AI teammates in the market, evaluate the launch of AI teammates into our PLG motion, which will happen in the beginning of the second half, and advance our go-to-market integration and enablement of Stack AI. Now turning to margins. We believe the structural efficiency improvements we have made and continue to make across the business create capacity to invest beyond our AI products while still expanding profitability. We expect Q4 exit operating margin for FY27 to be above our full year operating margin guidance. Stack AI is expected to represent approximately a one percentage point drag on operating margins in Q2 and the second half of FY27. This is fully reflected in our guidance. Now moving to guidance. For Q2 fiscal year 2027, we expect Revenue of $213 million to $215 million, representing 8.2% to 9.2% growth year over year. Our guidance includes an expected contribution from Stack AI of approximately 50 basis points to growth. We expect an immaterial impact from currency this quarter. Non-GAAP operating income, we expect to be in the range of $18 million to $20 million, representing an operating margin of 8.5% to 9.3%. Non-GAAP net income per share, we expect to be in the range of $0.08 to $0.09, assuming diluted fully weighted average shares outstanding or approximately 237 million shares. For the fiscal year 2027, we expect revenue in the range of $855.5 million to $863.5 million, representing growth of 8.2% to 9.2% year-over-year. The full-year revenue guide reflects the outperformance from Q1 results, and includes an expected contribution from Stack AI of approximately 50 basis points to grow. Based on current FX rates, we expect an immaterial currency impact for the remainder of the year and an approximately 20 basis point tailwind to our full year revenue growth in constant currency, same as last quarter. For the full year, we expect non-GAAP operating margin of at least 9.75%, and we expect non-GAAP net income of 37 cents per share, assuming diluted weighted average shares outstanding of approximately 239 million shares. We are seeing continued improvement across the business, including accelerated momentum across our AI products and deeper adoption of Asana and mission critical workflows. The addition of Stack AI further strengthens our position as the operating system for human agent teams, and we remain very excited about the opportunity ahead. With that, operator, we are now ready for questions.

Thank you. As a reminder, if you would like to ask a question, please press star 11 on your telephone. You will hear that automated message advising that your hand is raised. We also ask that you please limit yourself to one question and one follow-up and wait for your name and company to be announced before proceeding with your question. One moment while we compile the Q&A roster. The first question of the day will be coming from the line of Robert Oliver of Beard. Your line is open.

Great. Thank you. Good afternoon. Aziz, look forward to working with you. Dan, I had two questions, and I'll start with the first for you. So Stack AI, you called out it accelerates your roadmap, I think, by a year. What was really the most compelling reason for you guys to do it now, and how quickly can you integrate that into what you guys have currently? And then I had a quick follow-up.

Yeah, hi, Rob. So it all starts with our customers. You know, we launched AI Studio to our customer base, and it was deeply adopted. And what we found is they wanted to automate more and more and more parts of their workflow and extend those workflows to third-party systems. So they wanted to create automations that bled into their CRM systems or into their databases or into some of their ordering systems. And when you think about that, we kind of said, look, We can continue the AI Studio roadmap, and we kind of had a very nice plan about how we were going to add all these third-party integrations, these orchestrations across multi-systems, or we can deliver that today to our customers. So when we found Stack AI and we interviewed and spoke to many of their customers, this is exactly where they were getting the traction today. They had demonstrated already with their customers these complex operating environments across some of the most I'd say regulated industries and regulated use cases. So our ability to bring that to our customer base today was just something we were licking our lips at, honestly. So we're super excited. In terms of acceleration, yeah, we say this accelerates it by a year. They've built advanced workflow orchestration, configurable knowledge bases, RAG layers, MCP infrastructure, all the things that we would love to have built ourselves and we're planning on doing, but why not deliver it to our customers today? Some of their customers, as an example, have already adopted 1,400 workflows in just a single customer. So if you can imagine taking that to our user base, I think they're going to be very excited.

Great. Really helpful. And then my follow-up is, you guys are clearly making some progress here in the efforts you've put in to restart the business on the growth side, in particular with some of the non-tech customers and more specialized end markets. And I think you called it out in your prepared remarks that, again, you're seeing nice success with those customers. I'd be curious to know if you guys have made any changes to the go-to-market team to verticalize that since you're seeing some success there. And then as we get, you know, Stack AI more integrated, does this motion require FTEs as well? Thank you.

Yes. So, again, I'll take that question, Rob. So, If you think about the groundwork that we've been laying over the last nine months, the first piece has really been about multi-product. And multi-product for us is a way to get to multi-buying center. And so you see AI Studio, AI Teammates, and now Stack. Those are all part of the same ambition, which is to better serve those ICPs. And you'll see this will continue in our Innovation Summit, Work Innovation Summit next week, where you'll see directly how we're going to please and delight more of those buying centers. The second piece of the kind of things we've been focused on is around customer health, which is about making sure that our customers adopt and enjoy our products, which is what you're seeing start to show up in our results and seat expansion. The third has been around sales productivity, and sales productivity is about making sure we hit that sweet spot, that we hit the problems that our customers have today, that we're clearly speaking in their language of jobs to be done by both department and by vertical. And then the final piece of, I'd say, the things we've been doing over the last nine months has really been about going faster, operating at velocity and operating and executing at pace. And so the combination of all of those things is definitely squarely focused on better serving our ICP and expanding the buying centers that we can talk to.

Thank you. One moment for the next question. And our next question will be coming from the line of Matt Bullock of Bank of America. Please go ahead.

Oh, great. Thanks for taking the question. I wanted to ask about the technology vertical and some of the AI-native frontier model providers you mentioned in the prepared remarks. So, understanding that the guidance doesn't contemplate continued positive growth in the tech vertical, Can you just help us understand what drove the return to positive growth this quarter and whether or not customers like Anthropic adopting some of your AI products had any contribution to that? And then I have a follow-up.

Yeah, well, maybe I'll start with the Anthropic piece and then I'll let Aziz talk about broader technology. We love the partnership with Anthropic and I'd characterize it as three things. One, they're a customer of ours. So as they grow, we grow. So we have a number of broad use cases across Anthropic, including their usage of AI Studio and AI Teammates. This kind of reiterates the point that we are the OS for human agent teams, a place where you can get things done across humans and agents. And we are that operating layer that sits on top of the AI layer, as it were. So that's them as a customer. They're also a product partner. And so we were one of the flagship workplace integrations, one of nine that they launched with. And we have launched a great MCP service, which allows our joint customers to access the work graph directly there in kind of the prompt window from Claude. And increasingly, they'll become a distribution partner for us. We presented at Claude Code, one of the keynotes there. We were a part of their connector directory. And, of course, through our AEO efforts, they become an important distribution partner for us. So, yes, we love the partnership with Anthropic and, you know, more of that to come. I'll hand over to Aziz now.

Yeah, so on the tech vertical, we're really encouraged about now kind of two quarters in a row. Last quarter kind of stabilized to flat growth and then resumption of growth after two years to a positive growth. We haven't factored that into our guidance. Our guidance still assumes trends from two quarters ago. We're encouraged, but we need some additional positive inflection to get more constructive and include in the guidance such as our philosophy. What's driving that? It's primarily expansion. So our tech customers have been early adopters of AI Studio, and now we're seeing that again with AI teammates. Dan called that anthropic, core weave. A large portion of those early adopters or teammates have been in the tech vertical. So expansion with our add-ons has been a key driver of that presumption to growth. And then secondly, we've seen seed expansion. So as these tech companies have gotten deeper adopted with AI Studio and It's also led to seed expansion, so we're super encouraged about that. And retention is also trending in a positive direction as well. So it's expansion and retention, but a lot of that's driven by adding on AICB on teammates.

Really helpful. And then if I could just sneak in a quick follow-up, can you unpack some of the drivers of the 100K plus customer count this quarter? It looked a little bit softer than I think some were expecting. Was that a function of less customers graduating above that line, some selling down? I'm just trying to better understand that metric. Thanks.

Yeah, maybe I'll just start with a few general comments and then Zee will pick up as well. If you think about our multi-product strategy, this is really helping us expand those customers and have more reasons to talk to them about more things and more buying centers. And we're at the AI teammates is really just 60 days of GA, AI studio, about nine months. And of course, with Stack AI, we're on day one. And so that's going to be a growing piece of that story. And then our customer health initiatives, which are very much around making sure that our customers are adopting all of our products and using them fully, is along the same lines. And similarly, how we're executing, prosecuting with our sales teams, and particularly our enterprise sales teams, These are all going to be great drivers for our 100K plus lands. And then we'll talk a little bit more about their expansion. But yeah, generally the theme is grass shoots and a bit early on some of the transformation that we've been driving there.

Yeah. And just to add on to that, the cohort grew 12% year over year. And as you pointed out, it was sequentially flat. So a couple of things there. We're seeing strong expansion within the cohort. So those NRR improvement and expansion drivers that I called out for tech, which also apply to non-tech as well, is showing up in actually the growth of our 100K customers within the cohort versus adding new ones. And then secondly, you know, we tend to view that metric on a year-over-year basis. There's some noise looking at it quarter-to-quarter, especially Q4 to Q1. You know, there's less days in Q1 versus Q4, so that just kind of changes the trajectory. So we look at the comparability on year over year. But 12% growth is what we anchor to. And then the second thing I'd add is, if you look at the AI Studio cohort, and we don't break out the 100k customers, but those almost doubled quarter over quarter. So we're seeing strong growth in 100k plus with AI Studio, as they increase their adoption usage, and we add new customers into that cohort. So we're encouraged by those trends, and we expect the cohort to continue to grow as those trends continue.

Thank you. One moment for the next question. Our next question will be coming from the line of Patrick Wall Ravens of Citizens. Please go ahead.

Oh, great. Thank you. And, Dan, it's good to see the progress under your tenure. One question I have for you is... I like the strategy of an operating system for human AI teams. I think it's compelling. But it's just so noisy right now, right? You have Microsoft with Agent 365, ServiceNow with Control Tower, Workday with Agent of Record, and the list goes on and on. How do you break through all the clutter to deliver your message? What do your salespeople do? How do you do it?

So maybe I'll pass the question into two pieces. First is like, How are we unique? So I'll talk a little bit about our positioning. And the second is, how do we get the message out to the world? So for the first part in how are we unique in a crowded market? Look, I think the good news is we all understand that the future of work is humans and agents collaborating together. And that really it's that workflow that's going to be the great productivity unlock from AI. So that's good news that we understand that that is the place to be. It's particularly good news for Asana because over the last 18 years, we have been building an operating system for human-to-human collaboration that lends itself very well. And beginning today, we become the operating system for human-agent collaboration. So what is it about our platform that has allowed us to become ubiquitous as a human-to-human collaboration? Well, the first is is really this idea of the work graph. So what is a work graph? Well, a work graph is the place that brings together every person, every task, every ticket, request, project, goal, and dependency onto a single living plan. Think of it as a neural network. So why is this important for human to agent collaboration? Because it turns out agents are also going to need a ledger of who is doing what by when towards which goal has it been done? Who's up next? That ledger is what we have already built. So think of the work graph, not just as a knowledge graph or as a graph for a single person, but really as the living context, the living plan that any actor can operate within. The second thing that we've mastered is also architecturally very difficult. which is multiplayer mode. Multiplayer mode is the idea that humans and other humans can interact with a single agent or with multiple agents. They can program the agent, coach the agent, give feedback to the agent. Multiplayer mode is a difficult trick to pull off because, remember, you've got contention of whose instructions actually matter most. Who gave it last? How do you build and compound that instruction set? With our AI teammates, you see we have solved that difficult technical challenge, which is keeping everyone congruent in a multiplayer world. The third thing that we have is a thing called shared memory. And this is the idea that every decision that has been made contributes to the next run or the next cycle of that workflow. And then finally, again, I think we have a very clever and unique way of bringing enterprise governance into this agentic tapestry. Because we make sure that every agent has identity, scope permissions, an audit trail, and cost constraints, just as the humans do in the teams that they're operating within. So our AI agents literally drop into the same work graph as our humans have already been operating against. So this is very unique. It unblocks some of the main blockers today about why companies haven't yet gentrified. why they haven't all got teams of agents working alongside them. Those are some key kind of, I'd say, differentiators in our positioning. We were built for this. You know, I kind of said when I started, you know, maybe six or nine months ago, that collaborative work management is about to see its day in the sun. And the day in the sun is, yes, it turns out collaboration challenge actually grows exponentially with humans and agents operating alongside each other. So that's a little bit about positioning. And as you think about how are we going to get our word out, well, it kind of starts today. You'll see that us rolling into our Work Innovation Summit on June the 4th, where we'll share more of our ambition and more of our product roadmap with our customers. And then you'll see us be a lot more purposeful, both of our marketing and sales teams, to make sure they understand how we can help customers get through this AI productivity gap that they've been experiencing and come out on the other side of it.

Oh, great. Well, thank you for all that talk. One moment. Thank you. One moment for the next question.

And our next question will be coming from the line of Jackson Etter of KeyBank. Your line is open.

Great. Thanks for taking our questions, guys. The first one was just a clarifying question on the 100K customers that are AI Studio customers. Are these people spending $100,000 on AI Studio or they are $100,000 customers that also happen to be AI Studio customers?

No, they're $100,000 on the SKU AI Studio. Their spend with their seats would be greater than that. So it's just the AI Studio SKU. Okay, wow.

And then what is like the typical spend for one of those customers on, you know, I'll call it like core Asana look like relative to 100%?

It ranges, but it can, you know, it's double-digit. The spend on AI Studio is a double-digit percentage of what their core Asana spend is.

Okay. All right, got it. I'm counting that as only one question. So my second question is, my second question is, you know, the Stack AI acquisition, it sounds like, okay, part of the play is a little bit more embedded into enterprises, and so you can kind of go to market there in a shared way. But I'm curious, like, you know, Dan, you mentioned this a little bit, but who is the buyer for Stack AI? And is that persona, is that budget, are those dollars coming from the same place in the enterprise where it would come from in order to buy the core Asana platform or these AI studio or teammates SKUs? Thank you.

Yeah, no, great question. So I would say increasingly there are People in an organization responsible for AI transformation, increasingly, they're actually AI centers of excellence. We find this to be a great place to start for AI transformation conversations. And so this idea that you can create cross-enterprise workflows that are automated and gentrified really matches well with, I'd say, that buying center. That buying center now can appear in operations teams. It can also appear in IT teams. And so those were already places that we had conversations, already places that we were bringing the value of collaborative work management. But this does allow us to go, let's say across and up in many cases. So definitely new buying centers, there's a new role that's responsible in many organizations for this left to right workflow orientation. But really anyone that is a strategic operations leader is very much kind of in our sights.

Thank you. One moment for the next question. And our next question will be coming from the line of Steve Enders of Citi. Your line is open.

Okay, great. Thanks for taking the questions here. I guess to start, I guess I want to follow up on some of the AI conversation and just maybe how does the I guess, customer behavior changing with the adoption of Studio? Like, how are you seeing kind of seat ads or other kind of core usage of that change? And I guess any changes there as well with some of the early teammates feedback from the beta program?

Well, maybe I'll take the kind of use case and jobs to be done around AI Studio. So think of AI Studio as the way to bring automations and AI nodes into your automations to life. So think any intake process, routing, approvals, request processing, translation, quality control, operational coordination, all of those kind of, I'd say, automations you can really supercharge with AI Studio. So in doing so, that does more squarely place us into business-critical workflows. And so it definitely allows us to have a richer and deeper relationship with our accounts. With the addition of Stack, that extends, of course, into cross-system orchestration. So even more business criticality when it touches CRM, ERP, databases, support systems, contract management, custom infrastructure, you kind of name it. AI teammates is a more egalitarian idea. And this is about supercharging your teams, whichever team you are in, And it's really about helping people get work done with team members that they can bring in to help them with things like status reporting, launch planning, workflow optimization, research, coordination, execution support. And so we have a set of 20 to 25 pre-built AI teammates that anyone can bring a light alongside them in their day-to-day work. Liz?

Yeah, just to add on to that, we're seeing those customers, it's been a year, and we're seeing those customers who adopted AI Studio actually being the strongest NRR cohort within our base. So the NRR for those customers adopting AI Studio is stronger than those that have not by actually a pretty wide margin on both seat expansion and we're seeing this 100K cohort, a lot of them have originated as smaller buyers and then expanded in that. And from a usage standpoint, we've seen tremendous growth in usage. We're not quantifying that, but we are seeing in those earlier cohorts greater usage by significant margin, and we're encouraged by that. And obviously adding stack, it's a natural expansion path for those studio customers over time from kind of simple automations within Asana to more complex end-to-end executions with Stack AI that are cross-system. So we see a nice upgrade path for the current users and future AI Studio customers as we continue to grow that motion to Stack. So that's another piece. But we're encouraged. And on teammates, it's early. We're seeing good initial progress. It's only been a couple months. But the pipe is growing fairly rapidly there. Those who have adopted it, the usage has been fairly strong. both on the out-of-the-box teammates and even creating their own custom teammates, seeing good engagement there. And, you know, we're really excited about bringing that to our PLG base in the second half and opening up the SAM within our base to teammates.

Okay, that's great to hear. And maybe just to follow up, just on the tech vertical, I think there's been quite a few, you know, layoffs so far this year across the space. I guess, you know, when you kind of have those conversations with customers in that vertical, just how are those headcount changes maybe impacting, or I guess have you seen any impact yet from that vertical in terms of what that means for some of the go-forward employee levels or seat levels within that cohort?

Yeah, so a couple things there. You know, as we said in the published remarks, on our nrr assumptions like we've only factored in modest improvement uh to nr into the guidance so that that would imply you know we've been seeing pressure in the tech vertical for for multiple years a lot of that has been uh layoff activity in those tech customers or lack of headcount growth so that would imply that that's kind of implicitly factored in um but being a multi-product company we have mitigants to that now with studio and teammates and we've seen success customers downgrading seats because they let go of people, we're able to mitigate that with studio and teammates to preserve that ARR, and in some cases actually still accrete that ARR. So that has been really an important motion for us. But as we think about the guide, we've been deliberate about how we factored NR into the guide to absorb some of this if it continues as we continue to scale those consumption-based motions that are very early for us but showing promise.

Thank you. One moment for the next question. And our next question is coming from the line of Josh Baer of Morgan Stanley. Please go ahead.

Great. Thank you for the question. I mean, I know it's hard to talk about growth beyond this year's guidance, but I do think a return to 100% net retention rate, accelerating growth into double digits is really important for the stock, important milestone for re-rating I'm assuming that you believe that path is possible. And so I'm wondering if you could help sort of frame the business case, the perspective around product and go-to-market, like what needs to happen? What do we need to see in the coming years to kind of reach that better growth in the future?

Thanks, Josh. And yeah, I agree. That is a significant milestone if and when we achieve that. So that's definitely in our scopes. Look, if you think about the, I guess, the leadership platform of the things I've been doing, the first is become a multi-product platform. And you saw us launch AI Studio, AI Teammates, Stack AI. And now, in a couple of weeks, you'll see even more ambition at our Work Innovation Summit. So Multi-product platform is definitely a big part of NRR. The second one is customer health, which is really about making sure that we spend a lot of time with our customers, getting them to the value that they hoped to achieve. And you'll see a deliberateness around that, a concerted deliberateness around adoption and utilization. The third has been around our own sales productivity and making sure our sellers are as effective as they can be and delivering more dollars per rep as we kind of grow out into the field. And then finally, operating velocity, which is really about us internally making sure that we're delivering everything on a faster cadence. So if you imagined, you know, maybe our mindset was something was going to be delivered in three weeks, or now we're trying to deliver the same thing in one week. That all adds to more innovation, more innovation internally in our processes, but most importantly, more innovation that our customers are going to be able to experience and enjoy. So those are some of the levers, and I agree that would be a great milestone.

Okay, great. Thank you very much.

Thank you. One moment for the next question. And our next question will be coming from the line of Billy Fitzsimmons of Piper Sandler. Your line is open.

Hey, Dan and Aziz. Hope you're doing well. Thanks for taking the question. Can we double click on kind of the positive trends in NRR and in maybe it makes sense to kind of break it down into its components, because it seems like it's both a combo of multi-product adoption and, importantly, seed growth. And on multi-product adoption trends, a lot of the AI products you've talked about are still new. It seems like the strongest growth is coming from customers that are kind of AI-first already, like at CoreWeaver and Thropic, but got to imagine there's a material portion of the base who is kind of much earlier in development their general AI journey. So help us think about kind of the run rate and motion for those other kind of outside AI companies. And then on seed expansions and kind of the growth you're seeing, is this just kind of your largest customers continue to add headcount leading to more seats or are there other factors there you would point to like sales execution or your AI product portfolio leading to a difference in conversation that's bringing more people onto the platform? Thank you.

Yeah, so we're seeing NR improvement across both tech and non-tech. You know, we called out FedEx and Koss, you know, this quarter, who expanded with seats and teammates. So we're seeing it in both tech and non-tech. And, you know, on the NRR, four quarters of improvement in quarter to 97%. It was actually in that sequence of improvement, it was actually the largest degree of improvement, that improvement from Q4 to Q1. And that's coming both on GRR and expansion. So GRR actually also has improved for four state quarters. So we're very encouraged by that. And the larger piece of that expansion of the improvement in NR has been on expansion. So that's not only with our AI products, that's early, but that's contributing nicely, but it's also seed expansion. As I said before, we're seeing the greatest seed expansion with those that have adopted our AI products. There's a nice flywheel growing there, that as we grow our AI products, we're seeing that associated growth in seats, and that kind of compounds the expansion and thus the NRR. So that's been fairly positive. And the seat growth has been both on expanding seats and also new logos. We call that a couple new logos and a pair of marks, but we still see strong new logo growth and new business tech and non-tech which is super encouraging and higher degrees of attach on those new logos with studio and now increasingly teammates which will be an important driver for us as we you know we now as Dan has said we're multi-product that that means we can land larger ACVs on the outset and then expand from there so you know NR is taking a nice trend you know next quarter we have the large customer downgrade kind of lops off so that's another catalyst for improvement and along with, you know, continuing to improve expansion and customer health, as Dan called out.

Thank you. That does conclude today's Q&A session. And I would like to turn the call back over to Eva for closing remarks. Please go ahead.

Thank you, everyone, for joining the call. We'll be on the road attending the Bank of America and the Bayer Conference next week. And, of course, please join us for the investor webinar on June 8th. Looking forward to seeing all of you. As always, if you have any questions, please reach out to me at ir.asana.com. Thank you very much.

This does conclude today's program. Thank you all for attending. You may now disconnect.