Asana, Inc.

Good day and thank you for standing by. Welcome to Asana's first quarter 2025 earnings call. At this time, all participants are in a listen-only mode. After the speaker's presentation, there will be a question and answer session. To ask a question during the session, you'll need to press star 1 1 on your telephone. You will then hear an automated message advising your hand is raised. To withdraw your question, please press star 1 1 again. Please be advised that today's conference is being recorded. I would now like to hand the conference over to Catherine Buon, Head of Investor Relations. Please go ahead.

Good afternoon, and thank you for joining us on today's conference call to discuss the financial results for Asana's first quarter fiscal year 2025. With me on today's call are Dustin Moskowitz, Asana's co-founder and CEO, Anne Raimondi, our Chief Operating Officer and Head of Business, and Tim Wan, our Chief Financial Officer. Today's call will include forward-looking statements, including statements regarding our expectations for free cash flow, our financial outlook, strategic plans, and our market position and growth opportunities. Forward-looking statements involve risks, uncertainties, and assumptions that may cause our actual results 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 may 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 their closest GAAP equivalents are available in our earnings release, which is posted on our investor relations webpage at investors.asana.com. And with that, I'd like to turn the call over to Dustin.

Thank you, Catherine, and thank you all for joining us on the call today. Asana had a good first quarter as we continue to execute on our enterprise go-to-market strategy and make progress on Asana AI. I'll go through a few of the highlights from the quarter and then jump into how I see the AI landscape evolving. Q1 revenues grew 13% year-over-year, with revenue from our largest customers growing even faster than that, and non-GAAP operating margins improved five percentage points year-over-year. Our growth continues to be fueled by some of the largest and the most strategic companies in the world who are partnering with Asana and redefining how they work. It's been a solid start to the year, and we continue to focus on our enterprise playbook, sales productivity, and building our enterprise muscle. Now I want to get to what's top of mind for me. AI is a disruptive force that will dramatically reshape all of software. Rigid software categories like ITSM, CRM, you can go down the list, they're all designed for an earlier paradigm. AI is transforming the way we manage work, the way we execute work, and the way we think about how to work. Everyone's mental model for how work gets done today needs to be rethought. Let me start with how folks currently think about our category, collaborative work management. What used to be about helping humans coordinate work at scale has expanded to enabling humans and AI to collaborate and achieve extraordinary things together. At Asana, we believe the future of work is humans and AI collaborating side by side, with AI teammates taking on and completing increasingly complex tasks and workflows. There's incredible enthusiasm for AI in the enterprise, and rightfully so. But most of what's been released today are co-pilots and assistants, AI that's meant to help personal productivity, summarize and generate text, and look up information. These are useful, but they're asking a lot of users to decide to change their existing behaviors, and in many cases involve a new chat application with its own learning curve. We're just starting to scratch the surface of what's possible when thinking of AI less as an assistant and more as a teammate. Today, AI can take on individual tasks and assist in completing workflow steps, and as we go forward, AI will own more and more complexity. From taking on individual tasks, to assisting with individual projects and workflows, to eventually overseeing entire portfolios of work, helping you balance the workload, avoid missing deadlines, and keep the team aligned around shared clarity. But there's still a trust issue in the enterprise. In fact, our Work Innovation Lab found that 53% of executives are concerned people will make decisions using unreliable information from generative AI. We've all seen confabulating chatbots, and this doesn't breed confidence in the workplace. So there are a few key problems customers are grappling with. How can we trust AI? How do we ensure humans are in the loop and held accountable? And then how do we scale AI at work from just an assistant to a teammate? So it's not just completing discrete tasks. Instead, AI could be taking on bigger bodies of work and taking responsibility for higher level goals. What gives me so much confidence is that the work graph is the ideal structure to overcome these hurdles and scale AI with confidence. Asana understands how work and workflows map the goals. and can break it down in ways both humans and AI can understand in action. We capture the relevant context without the digital exhaust that exists in other collaboration tools that focus more on documents or chat, or the scaling and visibility issues you see with our peers and work management. A helpful analogy is thinking of Asana on the work graph as a form of digital scaffolding. Said another way, we have the necessary structure. We understand the relationships between people, work, and workflows, And that means we direct AI to consider exactly the right context. Not try to decipher what a signal from all the data in your enterprise. With this understanding, AI can begin to provide intelligent assistance, automate tasks, and even act as an agent or teammate driving work forward. Imagine an AI teammate that's the most organized, knowledgeable, effective, and encouraging project manager that you've ever worked with. Helping you figure out the best way to plan and accomplish your work. and even doing a lot of the work themselves rather than assigning it all to others. Our platform is also where the actual collaboration between humans and AI will happen. By deeply integrating AI capabilities into the tools teams already use to manage and execute work, we're creating the ideal environment for humans and machines to work together seamlessly. With Asana, AI teammates appear right in the flow of work, not in a separate tool. As we build this future, Asana's focus on how work is structured will be a key advantage. We know which context to look at, and we don't try to look at all possible data, which is how you easily end up with errors. I like to say that language models confabulate when they try to give you an answer based on what's in the training data, but they're vastly more accurate when asked to give you an answer based on what's in the context window. Our strategic advantage is being able to identify the most important context well, because it's explicitly identified by the relationships between the tasks, projects, portfolios, goals, and people in the work raft. This context and high signal-to-noise ratio will allow the AI we develop to deliver insights and automation with a level of precision and impact that scattered noisy data simply can't match. Let's think about this in the context of common workflows our customers rely on Asana for every day. In resource planning today, You can ask Asana's AI to determine the bottlenecks and key staffing risks by project portfolio or goal. AI can also apply decision-making principles with judgment to route work to the right team. In the future, AI will understand the complexity of each project, predict potential roadblocks, and proactively suggest the best team composition to ensure success. That team would be made up of human and AI teammates working together. For goal management, today's Asana AI can assist in writing goals based on best practices, help identify which teams are the best suited to take on the work, and actually identify which work in the organization would be best to link to that goal. In the future, AI will analyze the work graph to identify which initiatives are driving the most progress toward key results and suggest course corrections for those that are off track. Today, for product launches, PMOs can use AI to recognize where other teammates need to be added, where decisions need to be made, and ask Asana's AI to review work and assign approval tasks. You can have Asana AI complete work now, like having it help edit and draft creative briefs. As work gets done today, AI will create accurate real-time status reporting on goals, portfolios, and projects based on the exact format your team prefers. What's next? AI will take on increasingly complicated portions of the work and handoffs associated with a successful launch, all while keeping human teammates accountable in the loop. That's just thinking about the transformation of common workflows our customers rely on us for today. The opportunity here is so much bigger. We now have the ability to customize and personalize workflows effortlessly and can do this in infinite ways. This level of customization is hard to even grok because it was so out of reach before. There will be a significant amount of value creation as a large swath of enterprise workflows are reinvented with AI and rigid software categories of the past are reshaped. This is where we're focused and I believe we're uniquely positioned to win. And our experience isn't that we simply automate the work. It's that we can do more, move faster, and raise the bar on quality. Like we see in all paradigm shifts in technology, people translate workflows from the previous paradigm into the new paradigm before they realize this is incredibly limiting. The opportunity is to transform. Google and Meta built the best ads businesses in history by creating products only possible in the internet age, adapting ad units to new form factors, and building auction-based pricing with dynamic ad placements. This radically new and profitable model is analogous to the moment we're in. Let me give a concrete example. Right now, people think about automatically translating their marketing content to suit different verticals with AI. But maybe in the near future, your marketing landing page is selected from a thousand possibilities. They could be pre-customized by Asana AI workflows based on what will be the best possible match to the viewer, because customizing to this degree is worth the inference cost, and Asana can make it easy. Or maybe vendor selection is done by AIs running sophisticated RFPs instead of people viewing marketing pages and asking questions. And here's where elevating the quality and automated customization translates into increasing velocity and revenue for customers. I have more conviction than ever that the entire SaaS landscape is ripe for dramatic upheaval, and Asana is well positioned to capture the opportunity it presents. to disrupt old software categories and be the digital scaffolding for humans and AI working together on any workflow that helps achieve their objectives. And we expect our business will expand too. We believe AI will drive revenue growth for us in three key ways. First, it already enhances the value we deliver in our work management functionality, like with our smart summary and smart status features. We don't package the AI parts of our core features as a separate SKU because we understand AI functionality is simply table stakes for participation in SaaS at this point. However, we believe the differentiated value provided by AI plus the Asana work graph makes us more competitive and increases our pricing power. It's motivating customers to migrate to our new packages. And at the same time, AI is enabling us to introduce new, powerful use cases that can be sold independently. So the second way we expect it will drive revenue growth is via license-based add-ons. and we have specific ones we're developing now. On top of that, like we've suggested in the past, there might be more usage-based AI revenue in the future as well. And over the past few months, we've gained conviction on that, specifically in the context of custom workflows. We're working on a private beta with select customers, and we intend to expand more broadly to our enterprise customers as the year continues. I'll reiterate again how incredible this opportunity is in front of us and how well positioned we are to capture the AI opportunity in the enterprise. We believe that with AI and the WorkGraph, we'll further penetrate our existing market opportunity, and with AI-enabled features like custom workflows, we'll increase our TAM and expand into new markets. We moved early on AI. The WorkGraph provides the ideal structure and scaffolding for AI to be effective. We're the number one AI work management platform, and we're just getting started. We look forward to sharing more details at our Work Innovation Summit in San Francisco on June 5th, and later this year in October in New York City. And with that, I'll turn things over to Anne.