Asana Aktie

Welcome, everybody, to day 2 of the Citi TMT Conference. I'm Steve Enders part of the software research team here with us for the next session. We have the team from Asana, Dan Rogers, Aziz Megji. So I want to thank you both for joining us today.

Thanks for having us.

Thanks for having us.

Yes. Maybe just to start, Dan, I think it's been about a year since you took over would have been maybe the biggest changes that you made since you've come in? And Aziz maybe some other question to you since you took over as CFO earlier this year. What have you kind of evolved maybe in the strategy since then but Dan start with you.

Yes. So just winding back the clock, Asana was founded about 17 years ago, we were founded on the idea that as soon as you get more than 2 humans in a room, you have a collaboration challenge that you need to figure out who's doing what by when. And fast forward to today, we became one of the most ubiquitous collaborative work management companies, 85% in Fortune 500, about 300,000 companies around the world are using Asana, but the situation I arrived in is that the modern team is no longer just humans that need to collaborate with each other, but humans and agents that need to collaborate with each other.

So First mission really was to reimagine Asana as the human agent operating system to account for the fact that the collaboration that needs to happen now is going to be between agents and humans and agents and agents and the agents, in turn, need that collaboration strata to figure out what's the agent doing next? In fact, does the agent understand the company's goals? And has the agents work now handed over to the right human afterwards and to the next agent to pick up. And so this kind of task centricity that we found with human collaboration is also the same thing, literally, it's the language of agents. They talk in the language of tasks. Certainly one that's used chart, you'll see the kind of task hierarchy as it goes through how it's processing or we literally run on the task hierarchy.

The work graph that underpins Asana is really a relationship between tasks, projects, goals and humans and now agents. So reimagining a sane for the new era. And so that means 100% of our engineers are building against the human agent operating system. So instead of collaborative work management now, we call it Agentic work management, our core category, we're repioneering. And along with that, launching new products. And so actually, in the next couple of weeks, it's a big couple of weeks for us because a lot of the things we've been innovating on come to market. You'll see not just one product, our core product, but 5 new products. and that we'll have new products for each of our buying centers, whether that's IT, whether that's software development teams, whether that's professional services and client delivery teams, whether that's process architecture and process builders.

We really have a solution and end market operations team, which is our home base. We leverage solution for every team. That's on the product side. And then of course, go to market. We've been upmozing as well. We brought in the new Chief Revenue Officer, and we've been very focused on sales base. Verition our pipeline discipline. You see it in our numbers, you see a nice uptick really every quarter since I've started actually both an uptick in our top line growth and opinion operating margin and an uptick in our NRR.

So it's been pretty consistent now on the maybe it's 3, 4, 4 quarters. Every single one has followed that same trend line. And so obviously, if we continue on that thing will be a great story.

Yes, let's keep trend going, Aziz.

Yes. I mean when I started as CFO 6 months ago, it was correspond at the start of our fiscal year, and the world has kind of dramatically changed since then. And for me, it's really around how do we allocate our resources to the highest leverage areas to help drive this operating system that we're building and accelerate our growth. And we've made a tremendous amount of investments that maybe we didn't anticipate in the plan cycle months ago around how do we invest in our R&D capabilities to build these new products how do we bring on additional innovation. We acquired STACK AI and absorbed the dilution, and that's been a really exciting journey early days, but we're seeing great proof points how do we see our customers with our AI capabilities. We've seen really strong momentum with our AI products.

Now we want to get them out to our full customer base. We're investing ahead of the benefits. So how do we absorb that. And so we've been able to have this rapid investment that will help drive future growth acceleration and also adhere to the financial commitments we made at the start of the year. And so that's been a real focus of mine is really around resource allocation, ensuring we're placing our bets in the highest leverage or a hearing or financial commitments while we do that.

That's great. That's great to hear. I do want to dig in a little bit into the guidance, and then we'll have much deeper on the side. But -- maybe you could just talk to some of the moving parts here. I think pretty good beat for the quarter, decided not to flow through the entire beat. Can you maybe just walk through what went into the decision-making process for that? And maybe you think there are some of the moving pieces on the outlook.

Yes. I mean, as Dan kind of alluded, we had a strong quarter. We were 10% year-over-year or second straight quarter of growth acceleration -- all KPIs for the quarter were very strong, especially the NRR, every cohort improved. And so as we thought about the beat, we beat our midpoint of our guidance by $2.4 million. We flowed through the full year about $1.5 million. And we -- as we move to genetic Work Management or triggering unpack, there are some revenue recognition timing pushouts that are associated with that. So as part of our base becomes consumption part of that revenue gets pushed out into future quarters.

And it's really only a Q3 phenomenon where we see that push out because in subsequent quarters, you have the pull-in from the previous quarter. So that was about a $1 million impact. If you think about that together, $2.4 million beat, $1.4 million kind of flow through of the beat, a $1.2 million impact. In the absence of that impact, we would have been rolling the full beat and then slightly raising from there. So that's how we think of the puts and takes. And then as we transition to more of a consumption-based model in both the core package with AWM and with teammates as companies expand with us, -- we're going to learn a lot about consumption. We're going to learn about how quickly customers get from adopting these paid consumption.

We learn about consumption patterns and ramp right now with the data we have, we wanted to be a little bit more prudent in how we factor that into the guide. And so that was reflected in how we guided as well.

Okay. That makes sense. Last question for me on Guide and then we're going to get into AWN, but -- but just on the product road growth side of the business, I mean, that's been a, I think, a recurring kind of headwind to it or to the overall Asana growth. But how do you kind of think through the headwind of that moving forward? Kind of what are the things that you like, you can tweak and you can control at least to it agreed to try to mitigate that headwind? And then I guess, lastly, just on the guidance side of it, -- it does seem like the assumptions on that downtick, but you, again, flowed through the guide, which probably means that something to offset that. So help -- what was the positive that you kind of saw here too?

Well, I'll maybe hit the business piece and then you can do some of the financials around it. So from a business perspective, I'll say, again, one of the beautiful things about Asana is a lot of our customers want to interact with us fully digitally or partially digitally. So it is a real advantage to have a PLG motion. And so many of our existing large enterprises as an example, come in through the door of having a trial experience getting started digitally. So whilst we have that advantage, it is true that the top of the funnel is changing constantly. And most recently, we found that the top of the funnel has a lot of tire kickers who are not going to convert into paying customers, not going to defer richness of the product experience.

And so the challenge really is how do we fill the funnel with more of ICP sometimes give us like some kind of intra effect where all systems tend to complexity. It's probably the same with all funnels. All funnels tend to get clogged up over time. And so you have to put a lot of concerted effort into getting back to the core verticals that we're focused on, the core ones that we're focused on. And so we made a pretty dramatic decision to change 100% of our marketing allocation to target verticals and target personas, instead of some of the generic programs that you might do on paid search, et cetera. So that's a big change.

The top of the funnel mix should change quite dramatically. But then when they arrive, we've also done a lot on the product experience. So instead of arriving now to just collaborative work management, they'll arrive to agenetic work management, which includes teammates, and it will also arrive to Asana client management, which is for those teams that are looking to do client delivery, will now they'll find. And that's about almost 1/3 of our customers actually, they'll find that there's actually a dedicated product experience.

So -- the surface area of, I'd say, getting to the right product to the right folks has just increased fairly significantly. So we hope that, that turn of the change that profile quite significantly.

And then how we've factored in the guidance. If you think about the quarter, there's a couple of things that are really working well. One is the strength in the enterprise to if you look at the metrics that kind of reflect our enterprise business. So our CRPO, which is correlated to the bookings that we see in enterprise. If you back out the large customer that we renewed about a year ago, -- that growth accelerated from 7% last quarter to 11%. If you look at our 100,000-plus customers on a customer count logo basis, those accelerated to 16% growth year-over-year from 12% last quarter. We now see 25% of our 100,000 customers adopting AI, which is our AI products, which has led to strong improvement in NRR in the 100k plus cohort that cohort improved their NRR from 96% to 98%. So enterprise is really strong. We're strong momentum in our AI products, 20%, 5% of our net new ARR was with our AI products this quarter.

So that is what's driving kind of the flow-through of the beats and the revenue growth equation. Now on the flip side to your PLG question, we are seeing the impact that we called out at the start of the year that we were going to see 2 points of ARR headwind from the PLG business. That has increased in Q2. Now it's around 2.5% impact. And the flow-through of that AR impact, we're seeing more pronounced on a revenue basis in Q3 and Q4 -- so the impact to our revenue growth is about 1% in Q3 and [ about 5% ] in Q4. So if you take those 2 things together, 3 things together, strong enterprise strong AI product adoption, which is improving NRR in our larger cohorts and then this continued headwind on self-serve PLG, which you're seeing actually in the NRR or our overall PLG base, which is muting a bit the improvements in the -- in our larger customers. That's kind of the puts and takes. And as Dan walk through the initiatives -- it's a big focus of ours to get that business reaccelerated because as we do it's an accelerant to both our revenue growth and our NRR.

Okay. That's very clear there. All right. Shifting gears now to AWM. I think it really seems pretty interesting what you're doing here. Maybe we can dig a little bit into what is generally new in the product with AWM? How does it maybe evolve what you're doing before with CMA instead of it just being a repackaging or a renaming of the prior solution set?

Yes, great. Maybe I'll talk about what's happening in the real world. In the real world, does this AI productivity gap. Our productivity gap is People are experiencing a lot of personal productivity increase with working with the chat agents with the but companies in general, haven't really translated that into their workflows into their core productivity -- and so company footprint of AI tends to be fairly low or single-player mode of multiple people now producing their documents better or doing their coding better, that make us not a business process. So we said how do we more deeply ingrain agents into what we call the agentic enterprise?

And the answer is through agenetic work management. So what is the agenetic work management? Well, the first idea is we prepacked up some agents that can work alongside humans. But unlike the single-play agents, let's make a multiplayer from the get-go. And let's make them instead of you're having to buy these things or find these things, let's make them raise their hands as you're doing your work. So 30 pre-bol teammates. So teammates across -- of course, we've had 17 years of history of what people are trying to do at work. So 30 teammates that actually cover the large part of what people are trying to do at work.

And we've pre-skilled them, pretrained them, and pre contexted them on your work craft data. So what does that look like? Let's say, in marketing, where we have 5 of these prebuilt agents, we do have a campaign planner in marketing, that is pre-skilled and pretrained on what it takes to build a marketing campaign. It literally knows that every marketing campaign has these 16 steps, and you're probably going to need to have brand approvals, and you're probably going to need link into your core brand assets. And you're probably going to -- so what it will do is if you're in Asana and you wake up in just over a couple of weeks' time, it will open up Asana you might be working on a campaign, you might be running a task. This thing has got to volunteer itself. And so how, I'm your campaign manager agent. I got you. What the heck is this thing.

Let me click on this thing. Yes, I know so much about what you're trying to do already because I've scanned the work graph and figured out who you work with, how you do this. And by the way, I've actually preordained from the people that have trained me what make us a great campaign. Here's what I think going need to do next? Are you game? Sure. So you'll start working with a campaign planner, and it will then in turn so -- and I noticed that these are the 16 people that you work with on campaigns. Do you want me to kind of tag them into? Okay. Great.

And the next thing you know, we're all working with that agent. So this is like a completely different paradigm shift. We have millions of users and in a couple of weeks' time, millions of users are going to each have 2, 3, 4, 5, 6 agents that they're working alongside that have volunteered themselves to help. So literally, we are going to go across the calm in a massive leap to see agents in the modern enterprise, prepackaged, pre-skilled pretrained, operating just like humans. And because they're in the same context as the rest of the humans, you can fully govern them, you can fully audit them, and you can fully scope them to work just as the rest of the human teammates.

So last thing one, and again, to your point, -- this is not a, oh, we've got some new AI feature. We've got some new virtual chat assistant. This is actually germane to how you work. It's deeply embedded in your workflow. So it is a category changing shift. The second thing is we have developed a chief of staff, we called DASH, and DASH will also be rather pleasing to any of our users because DASH will again be fully contacted in the work graph, before the context it in the teammates that can help. And just be able to pull not just on everything that's in the Asana but also everything that's in your e-mail and everything that's in your chat with Slack and everything that's new calendar and then actually infer or in everything that's in your meetings from Meeting transcripts and infer the tasks that need to happen next and what you do -- and actually, any of the tasks that you currently are working on, what new information that's in that peripheral system, you need to be aware of that can be enriched in that task.

So again, is going to be a huge leap forward in what one can imagine a Chief of Staff should do. Again, like really point Aziz's point about would be busy from an R&D perspective, I really can't describe how the velocity of our engineering teams is probably 2.5x in the last 12 months. And so we are shipping stuff that's game changing. And I think the big reveal is just a couple of weeks away, and I think people are going to be very surprised about the new Asana what we've been up to. And then workflows in general, both through our acquisition of STACK and then also through this thing called AI Studio, the ability to visualize processes and actually have those processes connect not just to agents, but also to third-party systems, if this, then this -- so for example, Citi has built their own virtual assitant called Sky is amazing, got a preview of it last night.

But -- in reality, where no customer has a discussion with Sky. It was probably going to end up talking in 1 of 5 paths that's going to need some other workflow that falls out of it or some other team that needs to get involved. And that's really where STACK comes in, visualizing workflow, connecting to other systems. So it will end up being the tapestry for the new enterprise is the idea.

Okay. I mean it's it's really interesting and I think kind of how it's evolving and how you're thinking about what the future of Asana looks like. I guess I maybe want to ask about the diffusion of AI into the enterprise and how you see the spreading. How much are you thinking about this being something that just gets surfaced naturally within the product set. And that is what's going to drive the the end user to start using this versus this being kind of more of a sales-driven push and really trying to just get it in front of all the customers and needing to train the good market team on that.

Yes. I spend a lot of time with CIOs. And I kind of talked to series about this great AI productivity gap? And what's the reason behind it? Yes, there are security concerns and governance concerns. But actually, the biggest one is discoverability is that teams just don't know how to use various agents or retains they should be using. And there's a huge productivity -- initial productivity or cold start issue, which is don't have to get started with set agents. Don't have to find them, don't know how to get started with them. So that's a challenge we wanted to solve and very deliberately. We had 6 months where we had these simple AI teammates that we were selling as an add-on, so not discoverable and not germane to the core experience -- and that's fine, and we got as Aziz was saying, 25% attach rate of our AI products, but would 100% attach rate look like. And that's really where in product notification, in-product nudges really being very contexted as someone is trying to work and something that will literally help them and trying to do that in an unobtrusive way.

I think we may have nailed it. And so I suspect that most people will want to try these things. We've also been very thoughtful about making sure that there's not a billing event when they try those things, right? So how much do we give to get them to a point where they're delighted has been almost like a scientific endeavor, and I think we found the right amount there, which is basically -- and the unit we're using is requests -- so we're going to see requests for every user so that really you should feel like, why not? Why wouldn't I give this agent to go? It's going to pass my company security requirements, it's going to pass my governance is they're waiting to do work at my bidding, and it seems to know a heck of a lot about what I'm trying to do.

Let's give it a world. And because we've seeded 5 requests per user per month, we think that's enough for them to get to a point of joy and kind of saying, okay, this thing is we've got to get more of these teammates. I got to use this more as domain to work.

Yes. Okay. And then when you think about the monetization potential of this down the line, like understanding you're trying to drive usage and seeding it out to customers, I guess, what's the next step to when we start to see the revenue and the monetization path for you all?

Yes. What we've seen with the adoption of studio in AAT its just give us a lot of confidence that getting this to our fuller base as Dan said, reducing the friction and the barriers to adoption and engagement will help drive that consumption path a lot quicker. And so we haven't kind of defined. It's not in our guidance. We've been conservative and prudent how we factored in. But as we think about our model, we've grown with customers primarily through headcount changes, right? As they grow headcount, we grow, right, as now we have multiple ways in addition to headcount changes to grow with customers. We can grow with outcomes and the outcomes we drive greater consumption and utilization of our products, we can drive -- grow by the work being done and the output we're creating.

And I'm sure you'll touch upon with our new agenetic apps and expanding buying centers, we can now move to different departments with outcomes as well. So just enables these additional growth vectors that we've never had. And we're seeing that with expansion. Our NRR improvement, and a lot of that is being driven by expansion driven by our AI products, and we're seeing that with renewal activity. We had a large customer that we called out in the quarter where they have less headcount than they did 3 years ago when they renewed with us. We piloted AI studio and AI teammates with them several months ago. They saw value in 1 production workflow in a marketing application they saved about 30% of time line creating content from cutting campaigns. That ultimately led to a renewal where we were able to offset a downgrade of seats with studio and teammates and create an expansion outcome. .

And this is a multimillion-dollar TCV type deal where products are half of that. So being able to expand with consumption and outcome-driven products, A year ago, that would have been a downgrade for us. Now it's an expansion with an opportunity to drive future expansion as they continue to leverage these products and have more work through them. So these are exciting new levers to our story that I just add additional growth vectors in the long term.

I'll just say 1 other comment is, obviously, we're pioneering from a product innovation perspective, but pioneering from a business model perspective as well as a notion of literary across millions of users, multiple agents were entering cells. -- that doesn't exist. So how should 1 forecast that? And then we've got the conviction and confidence to do this based on kind of I'd say, our run-up of the last 4 to 5 months, but we're taking a huge leap. And so it's important to be prudent and conservative. But yes, I think we're also being very pioneering.

Okay. No, that's interesting. Maybe this is a good point to ask about net retention. I mean you saw a 2-point jump this past quarter on the higher end of it. I guess, what do you need to see happen moving forward to get that number to 100% and potentially above that from here? .

Yes. So if you think about -- our net retention is a rolling 4-quarter metric. So -- each of the quarters in that role in fourth quarter are improving. We've had 5 straight quarters of improving NRR. So if we -- even if we just kept our in-quarter NRR where it is today, you will see sequential improvement. And to drive it to 100% or greater, which is the goal, it's really 3 things. Like we have 2 things that we are doing really well that continue to drive better net retention. One, we're seeing the gross retention part of that equation improved quarter-over-quarter. So our utilization of our underlying seats is improving, which that's highly correlated to net retention. So that's number 1 on the gross retention.

Number two, we are seeing the customers as they engage deeply with our AI products and drive better outcomes we're seeing a dynamic both mentioned and expansion. Our AI customers are actually expanding fast much faster than our overall base expansion is an important lever. So we -- a year ago, it was about pricing and seats as leverage to expansion. Now we have 5 products we can expand with both seeds and consumption and outcomes. So that gives us just a lot more in our arsenal to expand with customers across additional buying centers. So that's the second. And then the third piece is back to the self-serve, what's driving down our net retention. So if you actually back into what the in quarter would have been for the 100,000 and 5,000, they look better than 98%. They're actually approaching 100% and one of them is already above 100%.

It's really that sub-500 cohort that's bringing that down to 97% on aggregate. And all things that Dan outlined are all aimed at improving the lifetime value of those customers, having them land at higher ACVs, expand at greater rates, driving more value for them through having more personalized teammates and products which will improve the retention, so it's continue retention much more to sell, which will help accelerate expansion. And then as we get that PLG and self-service piece, that NRR improvement will be a big tailwind to the NRR.

Okay. That's good to hear. I think we only have a few minutes left here, but I want to make sure that we touch on some of the other new products you have, like client management, service management and command I guess, maybe, first of all, kind of what went into the decision-making to create a specific solution like those? And how do you kind of think about what that means in terms of augmenting the business or kind of expanding the TAM that Asana can go after?

Yes. I mean, first, maybe you have to understand a bit about my own history to understand that question. So my -- I guess my formative years were at ServiceNow and then Rubraca so maybe get a page in the book or a chapter in the book both of those companies on how you go from single product to multiproduct and I was running a lot of strategy teams at ServiceNow when I was a CMO there as well. But really, the -- I guess, my main task was how do you go from being an IT service management company to being a multi-work flow platform. Similar Rubrik, how do you go from bigger data infection vendor to a multiform multiproduct data security platform. So I'd say part of it is this is what I do, and so that's maybe a bit of a history.

And then -- but specifically to Asana, it was obvious to me that we were already serving all of those buying centers. We were just doing so with a horizontal approach. So very nice correlation under the hood of "Oh, wow, x percent of our teams that were serving our IT teams and Y percent R&D teams, Z percent marketing and marketing teams. Fortis operations team -- it was kind of a beautiful picture. And then when you saw what they were trying to do in the platform they were trying to push the platform, what the edges were, where they were trying to go.

There were specific problems they wanted us to solve. And at a certain point, it's hard to do that in a horizontal canvas. And so we said, "Well, why don't we keep the horizontal canvas but be a lot declarative from some of those vertical use cases. So that's what we've done. So we've had about creating these vertical products, but because they still sit on the same operating system for human agent teams, the better together story is actually amazing. It is, yes, you can have a teammate that still works across all of these other departments. And so our angle in is not or let's take out the existing IT products, let's take out the existing client management products, let's take out the existing R&D type products, Atlassian, et cetera. Those might be byproducts, but the reality is, we're going to better serve everyone, this horizontal across the company by having better decisions for -- and the solutions will be amazing because they will be designed for the here and now.

And so we're very lucky because we began R&D on all of these efforts, let's say, post the Codex Cursor revolution. And so we got to build and imagine for the agenetic future. So our approach to IT service management is as modern as it gets to imagined 9 months ago and shipped today. And so with all of the underpinnings of what that could look like, what real-time knowledge basis could look like, what self-learning agents could look like. And so we believe no one has this kind of solution because they're all encumbered by the past way of solving it. But we've literally solved it for the next generation. So every one of those products, I think, will be quite mind-blowing now when people see them.

Maybe this is a good -- I mean, run up on time here, maybe a good time to plug the work innovation some coming up in a few weeks here. I guess, when should we expect coming out of that?

Aziz, do you want to take this? I feel like I've had a lot of that on back.

It's more your domain.

So, yes, again, it's an important -- so we have 2 innovations summit in London and New York. And basically, for us, they become development milestones as well of things they're going to release for each, and you can give us kind of summer release and winter release actually for us. And increasingly, we're going to start describing that. to the outside world. So really, it's kind of our winter release or we want to release preview. But all of the products will be in market by then, and so it'll have a lot of customer stories about real customers that are doing it that we've been very coy on and we've had to be very coy because they've been in this kind of design partner process, but you'll see a lot of big brand names that have been using these products and getting to these agentic outcomes delivering real productivity baked into their workflows. So I think it will be a rather grand unveiling of what it looks like to run a company that is an agentic enterprise.

Yes. And then we will have an investor fireside investor and analyst fireside with Dan, myself and our Chief Product Officer, Arnaud Barnat Boes to elaborate on the innovations and the customer stories and this business model and product transformation that we're undergoing. So we're looking forward to that and it should be some exciting announcements.

Terrific. Well, definitely looking forward to that. I think we're at time here. So we'll leave it there. But Dan, Aziz thank you so much for being here today.

Thank you for the great questions.

Thanks, Steve. Appreciate it.

Thank you for standing by, and welcome to Asana's Second Quarter Fiscal Year 2027 Earnings Conference Call. [Operator Instructions] I would now like to hand the call over to Eva Leung, 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 Second Quarter Fiscal Year 2027. With me on today's call are Dan Rogers, our Chief Executive Officer; and Aziz Megji, our Chief Financial Officer.

Today's call will include forward-looking statements, including statements regarding the expected release and benefits of our product offerings and our expectations for revenue to be generated by those offerings, our retention and expansion opportunities, our expectations for our financial outlook, including our fiscal year '27 full year guidance, strategic plans, our market position and growth opportunities, and our capital allocation strategy, including our stock repurchase program, among other items.

Forward-looking statements, including risks, uncertainties and assumptions 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 Annual Report on Form 10-K and our most recent quarterly report on Form 10-Q for additional information on risks, uncertainties and assumptions that may cause actual results 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. Reconciliations 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 Relations website at investor.asana.com.

With that, I would like to turn the call over to Dan.

We delivered a solid second quarter, exceeding our expectations on both revenue and profitability with continued improvement in the underlying health of the business. There's three things I want to point out this quarter.

First, the business continues to get healthier. Growth is accelerating, retention is improving again, and we saw a broad-based strength across industries and geographies. Second, while still early, our AI products are creating a new growth and expansion vector beyond our traditional seat-based model. Customers adopting AI Studio and AI Teammates are engaging more deeply, retaining better, and expanding faster than the broader customer base. And we believe this gives us an early validation of our opportunity to build meaningful consumption and outcome-oriented revenue stream. Third, we're acting on the learnings by bringing AI Teammates, AI Studio, and Dash together as a core part of the Asana experience through our Agentic Work Management product.

We want our customers to experience these capabilities early and naturally as part of how they work every day rather than a separate AI products that they have to discover and purchase. And we're going to be bringing that same orchestrated execution across humans, agents, and systems with Asana Client Management, Asana Service Management and our Command products.

So let's have a look at this quarter. Improving health of our core business validates our strategy. It gives us confidence in the investments we're making to drive future growth. Revenue was $216.4 million, up 10% year-over-year and above the high end of our guidance. Reported net retention improved in every cohort we report. Overall NRR improved to 97% from 96%. In quarter net retention improved for the fifth consecutive quarter. Core customers NRR improved to 98% and our largest customers, those spending over $100,000 or more improved to 98% from 96%. That improvement is being driven by broader multiproduct adoption within the largest customers creating additional pass-through expansion. The technology sector delivered a second consecutive quarter of year-over-year growth.

Now while growth remains modest, we're encouraged by the continued acceleration in this vertical. That growth included another expansion with a leading AI lab this quarter, adding seats, in addition to the expansion with AI Teammates that we mentioned last quarter as well as a global streaming service to both expanded seats and added AI Studio. Outside of tech, the story has been consistent for more than a year. Non-tech continues to grow faster than the company's overall growth.

In fact, we added new customers across a range of industries this quarter, including one of the largest telecommunications operators in the U.S., a large insurance operator in the U.S., a Big 4 professional services firm, one of the world's leading law firms, and an iconic American luxury jewelry brand. We also saw encouraging acceleration in the U.S., where revenue grew 10% year-over-year in Q2, returning to double-digit growth for the first time in over 2 years. This growth acceleration is attributed to improvement in both bookings and retention in our tech customers, which are concentrated in the U.S., strong adoption of our AI products, and acceleration in new logo acquisition.

Internationally, Darktrace and a leading U.K.-based financial service company were notable new logo wins for our EMEA team, and Delivery Hero expanded its relationship with Asana, including our AI products. Looking now at our AI product momentum. Momentum across our AI products continued to build this quarter. And while still early, we're seeing an encouraging validation of the opportunity to build meaningful consumption and outcome-oriented growth and expansion revenue streams alongside our traditional seat-based model. AI Studio and AI Teammates, in fact, drove about 25% of our net new ARR, up from 17% last quarter. This is above our 15% full year target, which we set in March. We find customers that are adopting our AI products, engage more deeply, retain better, and expand faster than the broader customer base.

This shows up most clearly in our largest accounts. More than 25% of our $100,000-plus customers have now purchased AI Studio or AI Teammates. This has been a key contributor to the NRR expansion we're seeing up market. Also seeing clear evidence that AI products can mitigate seat-based pressure while creating new expansion opportunities tied to usage and outcomes. This quarter, we signed our largest AI expansion deal in Asana's history, a 3-year multimillion-dollar agreement with a Fortune 500 media company, spanning AI Studio and AI Teammates with AI products representing almost half of the total contract value.

What's particularly important is the role our AI product played in the expansion. The customer is operating with a smaller workforce which historically would have resulted in a seat contraction. Instead, the investment in AI Studio and AI Teammates more than offset a smaller footprint, resulting in a modest overall expansion with also the additional upside potential of consumption growth over time. And they're already seeing measurable value.

In fact, in one creative marketing workflow, AI Teammates have already reduced the content operation cycle time by 30%. This is an important example of how our AI products are creating new growth vectors beyond seats, allowing us to expand with customers, based increasingly on the work and outcomes delivered through Asana rather than changes in headcount. We're seeing customers move beyond individual use cases to make Asana a core part of their broader agentic enterprise strategy, coordinating humans and AI across the workflows that run their businesses.

Asana is becoming the operating system for human agent teams for them. Let me share a couple of examples of what that looks like in practice. Indeed is a great example of how enterprises are using our AI products together to remove manual coordination at global scale. The world's #1 job site deployed AI Studio to automate project discovery and the technical scoping for its analytics teams. It also runs the dynamic intake and triage across the 70-person in-house creative agency, which operates in more than 60 countries and 28 languages. Annually, that work reclaims more than 1,400 hours of senior level time. It's cut lead time from raw request to active project by 60%. It's reduced manual ticket management by more than 40% for the creative team and delivers roughly $300,000 in savings and unlocked capacity. Indeed is also piloting AI Teammates as an autonomous brand auditor, matching localized content to global brand guidelines across dozens of languages.

Washmen, a UAE-based textile care business is another example of AI Teammates running an operation end-to-end using AI Teammates to agentify their customer support and returns process. So when a garment comes in, one teammate researches its retail value. The second reviews the care plan for risk. Third, checks it against every past claim, and the fourth handles compensation and drafts the customer message.

A person steps in only when a teammate escalates, the result is 90% faster claim resolution, taking it from 3 days down to 6 hours. These kind of results reinforce our belief that our AI products create the greatest value when they're being embedded in business-critical workflows with a shared context that enables people and agents to coordinate and execute together towards outcomes. This principle is at the heart of what we're bringing to market in mid-September with Agentic Work Management. So let's take a look at Agentic Work Management.

Let me explain what we mean here because this is a real meaningful evolution of our product. Not simply label on traditional work management. Individuals have experienced significant productivity gains from AI, but most organizations haven't yet translated that into the productivity gains at the enterprise level. AI often sits outside the workflows that run the business, requiring people to find the right agent, provide the right context, and bring the output back into the work.

With AWM, we closed that gap by putting people and agents and systems on the same plan. Historically, customers use Asana to coordinate work between people, to provide visibility into those tasks. With AWM, they can orchestrate execution across people and agents in the same context, same goals, and the same governance. AWM brings 3 things into every paid package tier. First, AI Teammates, including more than 30 prebuilt teammates for marketing, operations and IT. These are preapproved and ready to work and pretrained with no prompt engineering required.

Second, AI Studio, so that any team can build no-code workflow automations for intake, routing, approvals, and status. And third, Asana Dash, this is your AI chief of staff that knows a person's goals and priorities, pulls decisions out of meetings, e-mails and chat, and surfaces what needs their attention and keeps them that one step ahead.

So what does this mean for customers when AWM comes to market later this month? Well, beginning mid-September, all our new logos, self-service customers, and sales-led renewals will be moving to AWM. And they'll start with AI Teammates, AI Dash built directly into their package tier. This includes an allotment of Teammates and Dash requests.

Most importantly, rather than trying to find the right agent, the Teammates will surface themselves based on what a customer is trying to accomplish. This is deliberate. We want customers to experience the full value of Asana early. Similarly, the full allotment of request is designed to let customers put our AI products to work in their mission-critical workflows from day 1. By simplifying the purchase decision, we can get more customers to first value faster and create a natural path from demonstrated outcomes to deeper AI adoption to increase consumption and stronger seat retention and expansion over time.

We chose requests as the unit of consumption because we want our AI pricing to be customer-friendly, simple, and predictable. A request gives a customer a clear understanding of what they're buying with a consistent price per request, speed limits, usage visibility, and alerts. And behind the scenes, Asana is going to select and optimize the appropriate model. That complexity should be ours to manage, not the customer's.

So AWM is how we bring the operating system for human agent teams to customers today. People and agents running those cross-functional work that runs the business. Asana Client Management applies the same orchestrated execution to client delivery, service management to service delivery, and Command to product development, same platform, different kinds of work. We're not entering these markets with point solutions. Each is a purpose-built application built on top of the enterprise work graph that our customers are already running on. So each starts with that same shared context, memory and governance, the people, systems and agents need.

And the AI Teammates and automation a customer builds in one application carry into those others under the same permissions and audit trail. Each of these new products represents a large adjacent market and new buying center. So let's take a look at them.

Starting with Client Management, The promise here is simple. The complete client workflow coordinated across clients, account teams, delivery teams, AI, files, approvals, budgets, and projects. Nearly 1/3 of our customers today are already doing some form of client delivery or running a professional services team today. But they often run client delivery in Asana while managing the rest of the client relationship across disconnected systems communication and e-mail, statements of work and approvals elsewhere and resourcing and spreadsheet. That makes it really difficult for them to maintain a single view of client health, project profitability and team capacity.

ACM brings those pieces together. It has a branded client portal for requests, reviews and approvals, AI Teammates that draft statements of work, client-ready assets, and status updates, and time and budget tracking sits alongside actual work. Client Management is in early access right now.

Next, let's have a look at Asana Service Management. Traditional service management was built to route a ticket to a person and track it to resolution. Well, AI has changed that model, enterprises increasingly want service teams to resolve requests automatically, not simply route them faster.

Asana Service Management is one AI-native service platform for IT, HR, facilities and legal with 24/7 agents that can resolve routine requests through Slack, e-mail, or a portal before they even reach a human. Service Management builds on that with one front door for every department, a self-learning knowledge base that gets more accurate with every resolved case, and agentic resolution that moves Asana from a place where service work is tracked to a place where it's actually resolved. ASM is in early access now with strong feedback from IT design partners, particularly around the self-learning knowledge base.

Finally, looking at the Asana Command. As we know, AI has made code generation dramatically faster, but the coordination around that code hasn't kept pace. The spec, the handoffs, the release plans, the traceability. Increasingly, that's where the bottleneck now sits. Coding agents need more than the ability to generate code, they need context, a shared plan, and the decision history they can trust. Command provides that planning and orchestration layer built on the same enterprise work graph that already supports product and engineering planning teams today. That's the promise, ship faster with humans and agents in sync.

We designed Command as an open platform from day 1. So customers can orchestrate the agents and tools, they choose rather than being locked into any one proprietary agent ecosystem.

As SpaceXAI described it: "Command is a novel approach to a difficult problem. Coordinating work across many agents and tools modern engineering teams use. Its open platform design lets developers bring SpaceXAI into a broader orchestration there without being locked into a closed system."

Later this year, Command will also integrate deeply with OpenAI's Codex. This will bring parallelized cloud-hosted coding agents natively into how work gets planned, assigned and shipped. Command, reaches early access later this month.

Turning now to StackAI. StackAI is about turning your business processes into governed agentic workflows in minutes. Reading, writing, and executing across all the systems that the company already runs on. While Asana provides the plan, the shared context, and the people around that execution. Importantly, it gives us a more complete solution to enterprise AI transformation initiatives we're increasingly seeing from our IT and AI transformation buyers. And in that motion, we've already seen early wins including one of Australia's largest retailers. We believe these engagements are early validation of the opportunity to bring Asana and StackAI together for larger, more complex enterprise workflows.

In closing, taken together, we're expanding Asana in 2 dimensions. AWM gives us a path to drive deeper product adoption across our customer base and create meaningful long-term consumption growth alongside seats. While our new applications expand the workflow users and buying centers we can serve, all of it is running on the same architecture and advances our strategy to become the operating system for human agent teams.

With that, I'll turn it over to Aziz, to take you through the quarter and the outlook.

Thanks, Dan. Let me start with the quarter. Q2 revenue was $216.4 million, up 10% year-over-year, an acceleration from Q1 and above the high end of our guidance. StackAI contributed approximately 50 basis points to reported growth which was in line with the expectation we shared last quarter. Currency impact was immaterial this quarter. We have 26,778 Core customers which we define as customers spending $5,000 or more on an annualized basis.

Revenues from Core customers grew 11% year-over-year, and this cohort represented 77% of our revenues in Q2. We now have 890 customers spending $100,000 or more on an annualized basis. This represents a growth rate of 16 percentage points (sic) [ 16% ] year-over-year. As a reminder, these cohorts are measured using annualized GAAP revenue during the quarter and therefore, can be affected by the number of days in the quarter.

Our dollar-based net retention increased on every cohort we report. Our overall dollar-based net retention was 97%. Core customer NRR was 98%, and among customers spending $100,000 or more NRR was 98%. As a reminder, our NRR is a trailing 4-quarter average and therefore, a lagging indicator of more recent trends. This improvement is being driven by the continued strength in gross retention, healthier seat expansion within our largest enterprise customers, and broader multiproduct adoption, AI Studio and AI Teammates increasingly creating an expansion vector at renewal. As Dan discussed, that allows us to expand with customers in ways that are less dependant on seat growth alone.

Turning to self-serve. The PLG headwind we discussed last quarter builds throughout the year. The impact of lower PLG bookings compounds into the revenue base each quarter. So the drag on reported revenue growth increases even if the underlying self-serve trend does not deteriorate further. That pressure comes as several of our underlying growth acceleration levers are improving. NRR continues to strengthen. We're experiencing strong momentum with our AI products. Our U.S. business has accelerated and technology vertical has now returned to year-over-year growth for 2 consecutive quarters. It also explains the gap in our net retention.

Core and our $100,000-plus cohort are both at 98%, while company-wide NRR is 97%. That differential sits in the sub-$5,000 cohort which is concentrated in self-serve and skews towards customers outside our ideal customer profile. Getting company-wide NRR back to above 100% really comes down to 3 levers. First, gross retention improvement in the core and enterprise space; second, seat multiproduct and consumption expansion in those same cohorts; and lastly, improving ICP mix and driving stronger retention and expansion in the sub-$5,000 customer base. The first 2 are already starting to show benefits, and you see that reflected in our Q2 KPIs and financial results.

The third remains a key focus area and we expect the investments we are making there to contribute to improving NRR in FY '28, improving the growth in NRR within our sub-$5,000 customer base is centered on 2 areas. First, we're focusing our acquisition spend on the customer sizes, industries and use cases with the strongest fit and highest lifetime value potential. That includes becoming more targeted and verticalized with industry-specific team templates, AI Teammates and use cases designed to improve conversion and retention.

Second, we are increasing the surface area through which these customers can expand with us. AWM and ACM launched in self-serve in mid-September, bringing AI Teammates directly to our large PLG installed base while extending Asana into new workflows and use cases. We believe this creates a new vector to get deeper into critical workflows and expand these relationships beyond seats, which we feel will improve retention over time.

Now moving to profitability, where I'll be discussing non-GAAP results and year-over-year comparisons. We delivered a 10% non-GAAP operating margin in Q2, expanding approximately 300 basis points year-over-year while continuing to make significant investments in our AI products and agentic applications and the go-to-market capabilities to scale them. Our gross margin was 87%, which was down approximately 120 basis points from last quarter. This decline reflects 3 primary factors: first, higher AI infrastructure and compute costs attributed to onetime scaling and development costs for our new products, which accounted for approximately 80 basis points of the change. Second, the addition of StackAI, which has a lower gross margin profile, given its subscale accounted for approximately 30 basis points of the change. And third, the remainder of the gross margin impact reflects the mix shift from seats to our AI products.

R&D expenses were $50.7 million or 23% of revenue. Sales and marketing expenses were $88.2 million or 41% of revenue. G&A expenses were $28 million or 13% of revenue. Net income was $23.8 million or $0.10 per share on a diluted basis. We have kept our overall expense base relatively flat while adding capacity in lower-cost regions such as Poland and using AI products to increase productivity and expand capacity across our teams. We're seeing that most acutely in R&D, where AI is enabling our teams to deliver the most robust product road map in Asana's history without a commensurate increase in R&D spend. The combination of a more efficient talent footprint and AI-driven productivity gives us the capacity to continue investing behind our highest growth opportunities while driving operating leverage over time.

Moving on to the balance sheet and cash flow. At the end of Q2, cash, cash equivalents, and marketable securities were approximately $340 million. Our remaining performance obligations, or RPO, was $522 million, and current RPO grew 10% year-over-year. This represents 81% of total RPO and will be recognized over the next 12 months. The underlying RPO trends was stronger than the reported growth rates suggest. This is due to the comparison against the large multiyear contract we signed in Q2 of last year. Excluding that contract, current RPO growth accelerated to approximately 11% from 8% last quarter while total RPO growth accelerated to approximately 12% year-over-year growth versus 7% year-over-year growth last quarter. Our total ending Q2 deferred revenue was $350.7 million, up 12% year-over-year.

Adjusted free cash flow was $42.3 million or 20% on a margin basis. Note free cash flow benefited this quarter by approximately $5 million from stronger collections than expected. Before I turn to guidance, I want to connect the product strategy Dan described to the evolution of our financial model. In mid-September, we are including a base level of AI Teammates and Dash requests in the AWM tiers without changing tier pricing. This changes both for new and existing customers. We're seeding that usage deliberately, investing to drive adoption first, with the expectation that stronger retention, seat expansion, increasing consumption follow over time. Underpinning this shift, we have made significant investment in our monetization infrastructure and in-product experience, enabling AI native capabilities such as usage metering, overages, and consumption-based billing at scale.

Let me walk through how we reflected that transition in our guidance. There are 2 dynamics affecting revenue recognition as we transition towards consumption. First, going forward, all new AI Teammates sales will be consumption-based with revenue recognized as customer requests are consumed rather than ratably over the contract term. Because customers have flexibility in the timing of their consumption, this also introduces greater variability in the timing of revenue recognition.

Second, as we transition our core packaging from CWM to AWM and embed our AI products into the core subscription, a portion of subscription value that historically would have been recognized ratably is now allocated to AI consumption and recognized as that capacity is consumed. As customers ramp consumption over time, this shifts a portion of revenue recognition into future periods. The shift of new AI Teammates sales from ratable to consumption-based recognition, along with the AWM packaging changes creates a $1.2 million revenue timing impact in the second half. This is roughly split between Q3 and Q4.

Note this is just a timing impact. It does not change anything in customer economics, has no impact on ARR, bookings, billings, deferred revenue, RPO, or cash flow. In addition, this transition also creates approximately 150 basis points of gross margin pressure across Q3 and Q4, reflecting both costs incurred ahead of associated consumption-based revenue recognition and the growing mix of AI products, which currently carried lower contribution margins than our seat-based business.

Importantly, we're making these investments deliberately to seed AI usage and drive deeper utilization of the platform with expected benefits to retention and expansion occurring over subsequent renewal periods. As a result, we expect gross margin to be in the mid-80s exiting the year. We've already seen meaningful reductions in the cost of delivering our AI products through optimization and routing. And we expect those efficiencies to continue as we scale. Importantly, as you'll see in our operating margin guidance, we've been able to absorb the remaining increased costs through efficiencies and productivity gains elsewhere in the cost base while continuing to deliver margin expansion ahead of our expectations.

Note, this is all while absorbing approximately 1 percentage point of incremental operating expense as a percentage of revenue from the StackAI acquisition as we discussed last quarter. Second, the PLG headwind discussed earlier continues to weigh on the second half revenue growth profile. We estimate approximately 100 basis points of pressure to revenue growth in Q3, which increases to 150 basis points of pressure in Q4. Our outlook assumes that current PLG trends persist through the balance of the year and incorporates no recovery in FY '27 from the initiatives I discussed earlier.

Third, AI Studio and AI Teammates represented about 25% of net new ARR in the quarter or closer to 22%, excluding the large deal. Including StackAI, we now expect AI products to represent approximately 20% of that new ARR for the full year, which is up from approximately 15% of net new ARR, which we discussed in March. We're deliberately prudent with this target because seeding every customer with AI Teammates and Dash starting in mid-December may delay some consumption package purchases by a matter of months. This metric captures only new consumption and capacity package purchases, not the requests and credits included within the AWM tiers. No attribution is being made from the AWM packaging change. Fourth, we continue to assume minimal FY '27 revenue contribution from Client Management, Service Management and Command. Given enterprise sales cycles and deployment time lines, we expect the financial contribution to become more meaningful as a key growth driver in FY '28.

Finally, Q3 includes approximately $3 million of incremental AWM and agentic application launch investment consistent with what we discussed last quarter. That investment is concentrated in global brand and marketing and AI go-to-market activities around our September launches. We expect that spend to normalize following the launch with sequential operating margin expansion returning in Q4.

Now moving to guidance. The guidance I'm giving includes all the assumptions I mentioned above. For Q3 fiscal 2027, we expect revenue of $217 million to $219 million, representing 8% to 9% growth year-over-year. This includes a $700,000 headwind to revenue from our AWM packaging transition. We expect non-GAAP operating income of $18 million to $19 million, representing an operating margin of 8% to 9%.

In addition, we expect non-GAAP net income per share of $8 -- $0.08, assuming diluted weighted average shares outstanding of approximately 236 million shares. For the full fiscal year 2027, we expect revenue to be in the range of $858.5 million to $863.5 million, representing growth of 9% year-over-year at the midpoint of the guidance. The full year revenue reflects the outperformance from our Q2 results and the expected contribution from StackAI of approximately 50 basis points to growth, same as last quarter.

In addition, as mentioned above, it included a $1.2 million headwind to revenue from our transition to AWM and consumption. We expect an approximately 20 basis point tailwind to our full year revenue in constant currency which is consistent with what we shared last quarter. We expect non-GAAP operating income of $84.5 million to $86.5 million, representing an operating margin of approximately 10%. And we expect non-GAAP net income per share of $0.37, assuming diluted weighted average shares outstanding of approximately 239 million shares.

As we look ahead, AWM brings our AI products to our broader customer base, creating new expansion opportunities as adoption and consumption grow. We're investing ahead of those benefits while maintaining our margin commitments, creating the foundation for stronger growth and operating leverage over time.

With that, operator, we are now ready for questions.

[Operator Instructions] Our first question comes from the line of Patrick Walravens of Citizens.

Great. And Dan, congratulations on all the progress on the product side around Agentic Work Management. There was one thing in your prepared remarks that stuck out to me, and I would love to hear more about it. You said, rather than having to find the right agent, the right teammate can surface based on what the customer is trying to accomplish. That sounds like a very good idea to me. How is that going to work and maybe you could share a simple example of a teammate surfacing to help the user?

Yes. Thanks, Pat. And you're right, that is a good idea. And we think it's a bit of a game changer. Just to kind of level set on AWM, so Agentic Work Management. So this is the evolution of collaborative work management. The big idea here is that we think humans and agents are going to be working together and coordinating together to drive orchestrated execution. And we spent really the last, I'd say, 6 months figuring out how we want AI Studio, AI Teammates and our new AI chief of staff that we call Dash to appear to our customers. And what we found is, the more we can bring that directly into their experience, the better. So you'll see in September some, I'd say, innovative ideas on how we create this amazing experience.

So innovation number one is our AI chief of staff, Dash, as you ask it questions and interact with it, it will suggest the right teammates to help you complete your execution of that task. Number two is through input nudges. We'll actually recognize the type of task that you are trying to complete and suggest one of the prebuilt pre-skilled teammates that can help you. And that's because, of course, we've got all of this great work graph history, so we know exactly what kind of work you're trying to do. And it's no coincidence that we've built these 30 prebuilt teammates, those are exactly the kinds of work that our customers are doing today. So that matching will happen.

And then finally, if you want at the administrative level to do what we call a work graph analyzer, you can actually do that across all of your work and the admin can easily see which teammates could be most useful to help. And this is all in response to the idea that -- today, one of the biggest hurdles of agentic enterprise is actually the discovery of the agents being able to find the right ones that will work for you.

Our next question comes from the line of Steve Enders of Citi.

Okay. Great. I guess I want to dig in a little bit more just in terms of the factors being included in the guidance outlook on the revenue side, in particular. And I guess, one, better understand the PLG headwind dynamics and I guess, what exactly maybe change there in the guidance here versus last quarter? And then I guess with the headwinds that we're talking about on the packaging side as well, just how should we think about that continuing, I guess, beyond Q4 and going into next year for the potential impact that these factors could have here?

Yes. Thanks. So just to frame that up, I'd say, looking forward, 2 things we're really excited about, one is work-in-progress. So what are we excited about? The first is, as you see, we are now manifesting our vision as the human-agent operating system. We've got so much good stuff ahead of Agent Work Management. And then you see all of these other buyer-specific products of Asana Client Management, Asana Service Management, Command, and Stack. So really 5 new products that we're excited about.

Number two is you saw the upmarket strength, and you saw that this quarter, manifest as an increase in NRR across our $5,000 cohort across our $100,000-plus cohort getting up to 98% now. and AI adoption across the board, whether that's to every customer, which was -- you saw us say, 25% of our net new ARR is now coming from AI products. And then also for those large customers, in fact, over 25% of our greater than $100,000 customers have AI attached. So real excitement there, and then the work-in-progress is PLG. The dynamics changed a little bit.

The thing that we're now, I'd say, encouraged by is customers do still want to engage digitally, a digital discovery, digital playing, and many customers want to fully use and consume in a digital engagement. That remains true. What is new is the top of the funnel can get very clogged up with, I'd say, heavy tire kickers. And the best thing that we can do is focus all our efforts in making sure that the customers that are coming in and actually paying are the right customers for us that they're our ICP. So you'll see us focus a lot more of our efforts, a lot more of our marketing dollars on our ICP. And as they do so, as we get the right ICP into our funnel, because of that product strength, we now have so much more to delight those customers with. AWM will be in our PLG funnel. ACM will be in our PLG funnel. And so a lot more customers will have a lot richer and deeper experience early as they get used to Asana.

And Steve, just to add on to Dan's point, we're really encouraged what we're seeing about upmarket, just another KPI I'll call out is just the growth in RPO and cRPO. So if you actually back out the large customer renewal, multiyear renewal we had in Q2 '26 of RPO and cRPO. RPO accelerated from 7% year-over-year growth last quarter to 12% this quarter and cRPO from 8% to 11% this quarter. And that's really the best proxy for upmarket and enterprise growth. So we're seeing really strong traction there.

Also with our $100,000-plus customer cohort, that accelerated to 16% year-over-year on a customer count basis from 12% last year. And importantly, we're driving this upmarket strength with efficiency. Our sales and marketing spend has been really flat over 2 quarters. So we're seeing stronger sales efficiency there. So as you think about how that upmarket strength is manifesting in our consolidated growth and our guidance.

As Dan called out, the PLG piece is really masking that. So we called out a 2-point headwind to ARR back in March. That actually gap has widened a bit. And the impact of the Q4 headwind, the Q1 headwind and now again in Q2 on revenue growth compounds each quarter, so that ARR impact gets greater each quarter, where in Q3, it's about 1%. And in Q4, it grows to about 1.5 percentage. So that's underlying our guidance. And then you add the packaging transition to AWM, having about a $1.2 million impact in the second half or 30 basis points. That's just timing, and a lot of that is just created because it's the first quarter we're moving to that. It will normalize and should normalize in Q4 and subsequent in 2028, and we'll get that timing impact back in subsequent quarters.

So I think you asked whether that will grow or have a bigger headwind going forward. It won't. It actually have the biggest headwind in Q3, Q4 and then normalize thereafter. So if you take those 2 things in account and you think about our guide, especially with the $1.2 million, we beat Q2 by about $2.4 million. We raised $1.5 million. We had this $1.2 million impact we didn't foresee in the last couple of quarters. So in absence of the $1.2 million impact from the transition from CWM to AWM, we would have rolled the full beat and then some. So just putting into context how we're thinking about the guide. And just to reinforce these new products that were coming out of super excited, but we have not factored any contribution from them in our FY '27 guidance.

Our next question comes from the line of Billy Fitzsimmons of Piper Sandler.

I think great segue here. In terms of, Dan, a lot of new products rolling out in the second half, Command by Asana, Service Management, Asana Client Management. These products obviously expands your TAM. But in some cases, you're competing against new vendors. So Dan, I love that you could kind of talk about what is Asana's right to win in these spaces. And you touched on this a little bit, but what has to be done from a go-to-market standpoint as these products go GA to kind of get them out to customers.

And then as these -- I appreciate that last point there. So to be crystal clear, it sounds like potentially of adoption for these new products is better than expected. It could be a source of upside in the back half. Is that fair to say?

Yes, I'll start off. Dan goes, that's fair to say.

Yes. So -- thanks for the question. Returning to your first piece about new products, new TAMs and what's our right to win in those areas. I guess the first piece to think about is, I wouldn't think of them as just single products. This is a platform. The platform is an orchestrated execution across every team. And the platform itself has many of these differentiators built-in, really orientating around the work graph. So the platform itself promises instant productivity for any of the agents that run on it.

Why? Because we can quickly recognize all the relevant work, we can recognize who work needs to get routed to. It also promises increased velocity because there are a lot less handoffs if you know exactly who's supposed to get it next. There's no back and forth of e-mail and Slack. And then it promises the ability to control and manage the enterprise risk of those agents because every agent is auditable. So if you think about that, now apply that to those new products, so we already know a lot about these workflows. It turns out we've served IT teams. We've served R&D teams. We've served HR teams. We've served client delivery teams. We know exactly what tasks and work is and what the workflow looks like. So we get to bring an agentified solution to those workflows now based on all of the deep, rich data we have on how those workflows actually travel. So I'll give you kind of one example.

Let me do this for Asana Service Management. So Asana Service Management on Asana looks like a request might come in through a single portal or it might come in through Slack. Well, we'll understand the context of that request because we have this rich data. So instantly, we're now able to do one of two things, either a, resolve it instantly using AI, or b, route it to exactly the right person that we know is capable of dealing with that, with all of the full project context and history. Then when we actually make a resolution the resolution isn't just trapped in e-mail as an example, but part of the work graph itself. And now when the next request comes in, we know exactly how that in turn was solved in the last time.

So this is a kind of dynamic learning system that's all baked off this orchestrated execution platform. So that's our right to win. And so what does that lead us to? Yes, sometimes we'll be working alongside some of those point solutions. And sometimes, our customers may want to consolidate their spend on Asana.

Our next question comes from the line of Elizabeth Porter of Morgan Stanley.

I wanted to follow up on your comment about Asana being able to select and optimize the appropriate AI models for customers and you guys taking on that complexity as opposed to pushing it down. So what is the impact to your efficiency to be able to deliver AI and more cost effectively. Is this something where you could start to see greater savings that benefit the margin or more likely pass through in order to drive more share and usage within AI?

Yes. Thanks. I'd say, look, this is a growing competency and we're getting rather good at it. And I would say the piece that we've gotten rather good at over the last, say, 6 months to a year is figuring out which types of tasks should go to which types of model. And so something that may come in as a, I'd say, a generic request or a net new task type, we're doing pretty good categorization now of passing that out into the right model, to both solve for quality and cost optimization.

And so this will in turn lead to a much better gross margin profile as we're able to deal with that request, and we'll talk about request in a second is the unit that we're charging customers on so that we can deal with that request most efficiently, both in terms of efficacy of the outcome for them but also the cost delivered. And so yes, in the beginning, I'd say the gross margin burden, we've taken that a lot on our shoulders. But over time, you'll be able to see, I'd say, getting a much better gross margin profile from that.

Yes. And just to add, as we were determining the scope of the AWM launch, whether this would be new customers only or taking it to specific segments or bringing it to the full entire base like we are. The progress we have made reducing the cost of delivering our AI products particularly through the model matching and routing that Dan just mentioned, gave us confidence that we could go to the broader base while keeping the cost of that rollout manageable and mitigatable.

And you've seen that while it's having a 150 basis point impact into COGS in the second half because we're investing ahead of the benefits, we've been able to rationalize other places in the cost base to still deliver the margin expansion above our expectations. And so that was an important determinant of how broad we were going to go, and how broad we're going to go allows us to spark that adoption and that flywheel of adoption leading to better seat dynamics leading to consumption much sooner and much broader.

Our next question comes from the line of Jackson Ader of KeyBanc.

Great. The question I had was about the seeding the market in AWM and kind of trying to reduce the friction for AI adoption across your 3 AI products. I'm just curious, like what friction are you hoping to alleviate by going to this kind of embedded packaging, was like price a hurdle? Is there so much noise from every software vendor or AI vendor that like people didn't necessarily know what they could access via Asana? Like what is it that you're hoping to alleviate by embedding this in everybody's package?

My short answer would be yes, and then I'll expand on that a little bit. So there's a great productivity gap in AI, which is, individuals have seen massive improvements in the productivity by interacting with chat agents. They become much more productive in code generation, much more productive in document generation.

But oftentimes, enterprises haven't been able to translate that into real productivity. Why? It's because the AI is not actually part of their core workflow. It's not part of what teams do every day as teams. It's not part of the handoff process between teams. It's not part of the, let's say, coordination that's required to actually get work done in an enterprise. So what are we trying to solve? It's really that. It's how do we embed AI more deeply into the workflows that actually matter to our customers. So yes, there's a discovery part to that. We want to make sure that the agents are imminently discoverable.

But also, anything that the agents do actually operates within the context of a team that they are actors within the same work pattern as your humans. And so that's literally why we call them teammates. They are things that multiple people can interact with and improve upon and to interact with humans in the loop every time. So these are going to be much more deeply embedded in your day-to-day work. And because they're so discoverable, we think the cost of discovery has gone down, but also your ability to try these things out has also gone down.

And that ability to keep the multiplayer basically means everyone gets to take part, everyone gets to make them better over time. And when you add the work graph to it, you get this nice additional benefit, which is all of the work that you do to make your agents better, all the work you do to make your workflows better, make the very next run once again better in turn. And so benefits kind of compound and that's often what's missing in some of the single-player chat interaction today.

Our next question comes from the line of Rob Oliver of Baird.

Great. With 25% of net new ARR now coming from Teammates and Studio and would -- really, I think, underscores the case you guys have laid out for now, now being the right time to kind of transition here to AWM. I'm curious, you talked about and Aziz, you mentioned in detail, I appreciate all the detail, some of the impact on rev rec as the move consumption happens. You guys also mentioned in the prepared remarks, outcome-based pricing. And I would love to get some more color on how outcome plays into your thoughts and expectations about AWM as it ramps and how that potentially influences your ability to forecast the business?

Yes, I'll try and describe some of the philosophy here. So our customers want predictability in pricing, but they also want things to tie as closely as possible to the value that they're achieving. Predictability, definitely comes to a, let's call it, like a subscription-type model. But in order to tie to value, yes, we need to more and more tied to the outcomes that they were delivering together. And so that's really where the hybrid model come in. So how should we tie our pricing to value.

Well, we've decided that the unit that we're going to anchor on is requests. We've seen, of course, other companies with their endeavors around tokens or around credits or putting the burden on the customer themselves to choose the model and do model optimization. We, kind of, say we want to [indiscernible] all of that. We think request is the most customer-friendly possible unit.

Why? Because it's literally how you interact with Asana. You will ask it or your teammate to do something or help with something and then fulfill that request. And so we think it's a very natural idea that is, honestly, as customer-friendly as we could imagine. So the hybrid model is essentially a predictable piece that really does scale up and down with the size of the organization. And then also a knowable piece, which is how many requests do you want this system to deliver to you the outcomes of. So yes, we think that's the right customer-friendly mix.

Yes. And then on the forecasting, I'll be honest, our forecasting position on this in a year from now will be better than it is today. So that we've taken some prudence in how we've built this AI product target, raising it from 15% to 20%. The seeding should accelerate adoption in users, but it can push out the timing of incremental paid consumption. So we factored that in and how we have designed the 20%. And we'll learn a lot more post launching in a couple of weeks about how customers are adopting how fast the seeded credits are leading to expansion.

And then upon renewal, how they're impacting and influencing the seat renewal and seat expansion, which is a -- it's not part of that AI metric, but it's an influence and an attribute of seeding that we look to drive over time.

Our next question comes from the line of Taylor McGinnis of UBS.

So, given that it sounds like up market has been pretty strong and the weakness is in the PLG motion. I'd love to ask you a question on that and what you're seeing in terms of top-of-funnel activity there. Were those demand trends stable? Or have they become more challenging in 2Q and 3Q? And just as we think about the 150 basis points of impact of 4Q revenue, does that mean that in FY '28, you'll see a similar headwind of 150 basis points? Or how should we think about that as we look beyond this year?

Yes. So the impact -- so to answer, kind of, is it getting worse in Q2, Q3? It is, but not materially. So I think we called out the 2 points of ARR headwind back in March when we reported Q4. That's gotten a little bit worse, but more to the tune of about 50 basis points. The impact we called out on revenue is really from Q4, Q1, Q2. We don't expect and have not factored in Q3 and Q4 to further deteriorate from what we saw in Q2.

And all the efforts that Dan outlined in terms of driving the right top of funnel, not just the volume but the ICP mix, whether it be the size the industry of the customer. We see that the right ICP drives the right LTV. And then with new products and additional surface areas to procure ACM, AWM, the expansion opportunities with Teammates and Studio. It just amplifies that. So now you have a higher LTV customer with more to buy. It just creates better ACV and expansion outcomes and retention.

So and as we called out, the real inhibitor right now to getting to 100% plus NRR we're seeing is in that self-serve cohort, which is concentrated in less than $5,000. And if you look at, our Core is at 98%, if you kind of back in what that means on in-quarter based on the improvement, our in-quarter is trending towards 100%. And really what's driving down the consolidated is that sub-$5,000. So we don't expect this headwind to persist in the same level in FY '28.

Our next question comes from the line of Rishi Jaluria of RBC.

This is Josh standing in for Rishi. You guys mentioned looking to improve the sub-$5,000 customer base. And I just wanted to sort of dig into that a little bit. I was curious around how you're balancing developing the product to be -- to appeal to a broader audience and sort of being out of the box for giving a customer size while also balancing the specialization that comes with verticalization. And just a little bit more context around that would be great.

Yes. Well, I'll say all of our 5 new products serve really every segment rather well. And it's about how deeply you adopt it and which kinds of workflows you will use against them. So if you take Agentic Work Management as an idea. Well, it turns out, if you're a small business, you're a large business, you will want to have pre-built agents that are working alongside you.

Which ones you pick from that menu of 30 will depend, of course, how thorough you've built out those departments because these are essentially like packaged up agents that are prebuilt for your department. And so if you have a well-tuned, let's say, campaign department, then you're going to absolutely love the campaign orchestration agent. If you have a well-tuned launch process, you're going to love the launch agent. But similarly, if you're a small business and potentially you want to improve your reporting, then maybe you're going to use the reporting agent.

So I don't think the size of the company or really how they engage with us is going to gate how much they love these products. And then I'd say things like a Asana Service Management, if you have a, let's say, a large service department or you have a lot of manual service requests. Clearly, you're going to get a lot more value from that than if those departments are maybe immature or haven't started yet. So I'd say all of our products really serve all of those segments, and that's really part of the strength of Asana is, we have a great digital discovery, digital trial, digital experience and both small businesses and large businesses come to know us through that digital engagement.

Thank you. I would now like to turn the conference back to management for closing remarks.

Hi. Thank you, everyone, for joining the call today. We are on the road attending the Citi and Piper Sandler conference in the coming weeks, and we'll also have a marquee Work Innovation Summit in New York on October 14. Hope to see you all there. As always, if you have any questions, please reach out to me at [email protected]. Thank you very much.

This concludes today's conference call. Thank you for participating. You may now disconnect.

Welcome, and thank you for joining today's Asana Investor webinar. Here is our forward-looking statements. You can also find it in our published deck after the webinar concludes. Over the next 60 minutes, we have a lot to cover. Let me give you a quick agenda.

You'll hear first from our Chief Executive Officer, Dan Rogers, who will set the context of why this moment matters and what Asana has built to meet it. Then our Chief Product Officer, Arnab Bose, will walk you through a live showcase of 4 new Agentic apps we launched last week at our customer event in London, the Work Innovation Summit. Our Chief Financial Officer, Aziz Megji, will connect the product story to the financial opportunity.

Then we'll open it up for Q&A. Please send in your questions through the Q&A chat box in the webinar. With that, I'll hand it over to Dan.

Thank you, Eva. So exciting times for Asana. Last week, we had our Work Innovation Summit in London. What I thought I'd do for you all today is talk to you a little bit through the strategy that we shared, the differentiation of our platform and also, as Eva mentioned, our brand-new products that we're bringing to market.

So let's discuss that. So the first is our strategy. And so it all begins here with this idea that the future of work is changing. We're going to want to work faster than ever, plan better than ever, ship more than ever, launch bigger and in fact, get even more stuff done. And the reality is our personal productivity has indeed increased with AI. Our personal productivity has gone up manifold. We're producing more documents, more code in our everyday lives.

But as you all know, that hasn't actually translated into productivity in our organizations and for our teams. In fact, some stats show that as little as 5% of organizations can note any particular improvement in their productivity. So this is a great AI gap, and that is what Asana is going after. Because the way to actually create that productivity is through the workflows. It's identifying these workflows. And if you think about any company, any company is just a collection of these workflows. So when I speak to our customers, they have a long list of potential workflows that they want to identify. These are workflows that hitherto have been very manual. These are the things that actually affect their productivity that actually slow them down. And so why aren't more companies identifying those workflows? What's been holding them back?

And so as I spend time in the field around the world, the first thing I hear is it's very hard to get started. It's hard to discover agents. Most companies don't have a menu of agents that every employee can just pull and pick from. Most companies are worried about producing such a thing, how would they even deliver that to their employees. They're also worried that if they do so, that those agents have no framework in which to operate alongside their team members, that those agents won't be necessarily good team players, that humans won't be in the loop in the right way. So they don't know how to coordinate those agents.

They also worry about the programming of those agents, who is going to onboard these things, who's going to ramp them in the right way to make sure that they follow our way of doing business. And then finally, if you're a CIO or you're an IT enterprise leader, you're really worried about AgentPalooza. You're worried about agents running amok that don't have the right data controls, security controls or even cost controls. So these are real impediments, and this is where Asana comes in.

We announced Asana as the operating system for human agent teams. This is the place that your teams can achieve the real productivity and get the real work done that they wanted to do with AI and with agents. And this is the place where you can agentify your enterprise. So what is it that allows us to do that? And I use an example here. I'm a tennis fan personally love just finished watching the French Open, I forget to roll right into Wimbledon.

So I want to show a fictitious example is say the Wimbledon merchandise manager wanted to launch a new jacket. What does that look like in a world where humans and agents are able to work together? So with Asana, the first thing that happens is we have onboarded ready-to-go teammates. If you remember, I said, it's super hard today for people to discover agents and trust that those agents are ready for their enterprise. We have 30 prebuilt agents that we have built based on the patterns of usage that we know from our customers. These are agents that hit all of the middle of the bell curve scenarios where you're marketing operations, IT, product teams across the board.

But we did more than that. When anyone invokes any of these agents, the first thing that they do is they consume the Work Graph. So if you look here, we imagine Houston, our Launch Planner, instantly starting to see as someone is writing in a task that they want to launch a new jacket and they need to do so in the next couple of weeks. Our launch plan is going to kick into action and figure out from all the past tasks, past projects, past interactions between people, how did we launch products in the past? Is there a playbook is either codified specifically in a written document or inferred from how we've done this in the past.

From that inference, the Launch Planner gets going. It's actually able to create from day 1, a real project plan pre-populated with the tasks that it's going to take to launch this jacket. So we talked about blocker #1, hard to discover, hard to get going. Well, our agents are out of the box, productive, ready to go. So the second piece that we talked about is in many organizations, they don't really have this notion of multiplayer mode. What does multiplayer mode look like? Well, this is a place where a given agent, in this case, a Brand Consistency Auditor that Houston, the other agent invoked and recommended. This is to make sure that the design is done exactly on spec. The messages are done exactly on spec. Houston recommended that we bring this agency -- this agent into the fold, brand consistency auditor.

But what's amazing with Asana is because it's multiplayer from the get-go, we automatically know who needs to program this agent, who needs to set the rules for this agent on what it should do, whose work should we look at. And you see here 3 people interacting with one agent to program and onboard this agent to make sure it follows exactly the specifications. This is an architectural choice that Asana has made that all of our agents are going to be multiplayer.

So if you go a little bit further, the other differentiation is a thing called shared memory. So what does shared memory look like? Well, shared memory is the promise that each new run of a project is going to be better than the prior one of the project. And what you see here is one of these agents this agent is called Sentry. Its job is to scan any notifications or any regulations that might affect this particular garment or any garment in general. And it looks like there's some new, in this example, labeling requirements. Sentry picks up this labeling requirement, but does a little bit more than that. It knows that the last time that we had this labeling requirement, we actually had to change the labels out. In fact, we had to do 12 bespoke labels that comply with the EU regulations depending on the region.

So Sentry has now come into this workflow and recommended that we use these new sets of labels in the jacket instead of the old set of labels. This is shared memory. Shared memory is every new run of the project is better than the last one because we learned either from what the human said or even how the agents interacted and where agents recommended efficiencies for the next run.

The final differentiation is this idea of governance. So we said that IT leaders are really worried about AgentPalooza. All of our agents are governed. They're governed in terms of data that they can access, the permissions that they have and the human approvals that they need to go through. In this example, Tally, which is the production ordering agent, wants to order 10,000 units based on forecasting. But when we built Tally, we predescribed that a human will always be in the loop on any orders over 5,000 units, and only Sarah has the permission to do that run.

So now that agent within that gallery is fully scoped and fully permissioned for the organization. And within it actually describes how the human is going to be invoked. So this is where our differentiation comes to bear. Our differentiators hit the 4 key blockers that are inhibiting the agentification of the enterprise today. And as a result, when I presented this with most of the people in the audience said we need to get going. We need to get going tomorrow.

And over time, we're going to get even smarter with these teammates. These teammates are going to recommend themselves as you go about your work. Instead of even having to go to a library to discover them, they will be ready and available and make themselves known to you. And FedEx was one of our beta customers, as I described in earnings, and FedEx have put agents into their AI studio workflows. These agents hit both their sales teams, their marketing teams and some of their ordering teams as well. And as a result, they're able to go to market 9x faster. This is humans and agents working together in a workflow.

Arnab is going to walk you through some of the products that we announced. So not only have we created this framework, this operating system for humans and agents to work alongside each other, we actually lit up that framework by launching 5 net new applications. So if you think about Asana, we really have one historic application with collaborative work management.

Well, starting today, we actually have 5 applications, Agentic Work Management, which is all cross-functional teams, which evolves collaborative work management to now include all of those teammates, AI Teammates working alongside as well as the AI system, which we'll show you in a second.

Asana Service Management for service teams, Asana Client Management for any teams delivering client work, Command by Asana for any developer teams and with our acquisition, StackAI by Asana, now we have the ability to create these mission-critical cross-functional workflows across applications in an organization.

So to go a little deeper, we are going to have Arnab pick up from here.

Awesome. Thanks so much, Dan, and hi, everyone. I'm Arnab Bose. I'm the Head of Product here at Asana. And I want to pick up in one particular part where Dan left off with respect to Asana's differentiation, which is the Work Graph. So we've been investing in this system, which tracks who does what by when and how for well over 17 years. And it's this interconnected graph of tasks to projects, to portfolios to company level goals that has clarity around the individuals involved in those particular Work Graph objects. And now we've introduced AI agents into that Work Graph as well.

What's really interesting is not only the ability for the Work Graph to connect human beings, but to also connect AI agents on that same real-time shared ledger of who does what by when and how. And on top of that, from a platform level, we've been adding in new primitives into the Work Graph as well. So it's not just restricted to projects and tasks. We now have time sheets and budgets. We've got notes and meetings. We've got calendar items. We've got the ability to synchronize chats and a lot more.

And I'm going to pay that off in demos showcasing how these Agentic applications take the power of these differentiators like the Work Graph, like shared memory, like the human AI experience that we've got with an Asana and enterprise-grade governance to create real differentiation and new value for our customers.

So let's dive a bit deeper into Agentic Work Management, which is the easy button for getting AI productivity into every team. And as Dan said, it's for any cross-functional project. Think of this as the evolution, the AI era of collaborative work management. At Work Innovation Summit in London, we talked about several customers who are already on their way in terms of adopting Agentic Work Management. You heard from Dan about FedEx. We have the Chief Digital and Technology Officer of COS, a global retailer on stage, talking about how they have invested in Asana as their standard AI productivity tool to get to 90% faster campaign setup times.

We also talked about interesting customers like Washmen in the United Arab Emirates as well as a service in Italy, which is a manufacturing company, who've all started using AI Teammates live in production. But I would love to kind of bring this to you -- to life to you in terms of what are actually -- what is actually available within this Agentic Work Management products. Agentic Work Management is a combination of not just collaborative work management, the Work Graph and Teammates, but 4 different technology innovations that we've built over the last year.

The first is Dash. Asana Dash is your AI Chief of Staff. Asana Dash is a way in which you can interact with Asana's Work Graph tasks, projects and other elements in a chat-based way. It also has your back no matter what's happened in terms of giving you next best actions. I'll show you how this works in a demo and it's fully plugged into many different sources of data, not just Asana tasks and projects, but also your Slack, also your e-mail, also your meetings and your calendar to glean what is the next best action that you need to work on in order to stay in your zone of Genius and get your work done as an individual. So there's a lot of productivity increases that come from investing in an AI Chief of Staff like Dash.

The second is Asana AI Teammates, your prebuilt ready-to-go AI agents. You've seen examples of how they work in Dan section, how they present themselves and suggest to take on work and how they're prebuilt. And I would love to sort of go a little bit deeper and showcase exactly how Asana Dash and Asana AI Teammates work side by side to help you get work done.

The third block is Asana's built-in automation and AI studio. So this powers AI-powered cross-functional workflows and helps you schedule tasks or trigger actions when events happen within Asana. And finally, we've increased our depth of integration, both inbound into Asana and from Asana into other third-party applications in a massive way. We've got MCP applications available already for Claude and ChatGPT Enterprise. And we've also got plug-ins for Google Gemini and Amazon Quick.

And on the integration side, there's a whole host of different important business-critical applications that we are plugging into as well from Asana AI Teammates and Asana Dash.

All right. Now I would love to show you how all of this works with the demo. So in this setup, I'm playing myself. I've traveled to Warsaw, where we have a very large engineering team, and I didn't have WiFi on the flight. So when I land in Warsaw and I turn on my phone and it connects to the network, my lock screen is blowing up with notifications. I've got Google Workspace notifications. I've got Asana notifications. I've got Slack notifications. And because I've been out of touch for about 10 hours, it's going to be very hard for me to go through all of this and catch up on the Workday.

But now there is a moment of Zen. You'll notice that there's a notification from Asana saying that my morning briefing is ready. This is a morning briefing from Asana Dash, my AI Chief of Staff. Dash has looked through multiple sources of data. It's looked through what I have do within Asana today. It's looked through my e-mail inbox. It's looked through chat, it looked through calendar. And it's noticed that there is an e-mail that's unread in my inbox that's associated with the Dash launch creative production project. And it's a note from a vendor saying that they can no longer support what we ask them to do. They've gone dark because they've been double booked.

Now in this situation, before AI, before all of the tooling of Agentic Work Management, I would have to maybe call up my team, find out what alternative vendors we could use, look through multiple different databases. But with Dash, I can simply ask Dash that question. And again, because the approved vendor list is tracked and available within Asana itself, it can go ahead and glean that information. It has already got access to historical product launches we've done in the past. So it knows what are the vendors we've used in the past and does a match of approved vendors versus vendors I've liked and suggest that I should go with Brighton Company. And I can simply talk to Dash via chat or voice to text and tell Dash to go ahead and post a decision directly on that task to unblock the team.

So I've gone from a complete lack of clarity where my notification screen was blowing up. I might have even missed the fact that the vendor is now no longer going to make it to being alerted about this critical gap for a project that is directly tied to one of my strategic goals for this quarter to making a decision that unlocks a team that helps them move forward.

Now there's one more thing that comes up, which is there's a team, the Asana AI team that's been waiting on an EMEA regional approval for me. And again, this is something that I missed because I was planning my trip. I can simply say approved, and this is going to go ahead and update that Work Graph object, update that task and unblock that team and get them off to the races.

So super interesting way in which for an executive, for a senior leader, how Asana Dash like works on their behalf to keep them in their zone of Genius and help unlock their team across multiple sources, not just Asana data, but e-mails, Slack, Teams, calendar and more.

Now from the perspective of the team, what happens going forward is that they're unblocked, and this triggers an Asana AI Studio workflow that sets up a bunch of different tasks that will kick off AI Teammates. Now what this screen is showing is AI Teammates not only run on the context of the Work Graph and the context of the individual that they provide within the task.

But with every single run, they have this concept called shared memory, which makes them better and better going forward. And if Aziz, Dan and I all have access to the same AI teammate and we are using them in our tasks and projects, the really interesting thing is that 3 of us are coaching the AI teammate as if they're a member of our executive staff and getting them up to speed. And that improvement and its ability is not restricted just to me or Aziz individually, all 3 of us can get advantage of it. So it's literally like having a new person on the team who you're enabling with all this knowledge, all this context and all this feedback.

All right. So what's happening now is now that I've unlocked the team and have asked them to go ahead and draft that campaign brief, Launch Planner is already working on behalf of everybody in San Francisco. They might have been sleeping because it's 10 hours separate from Warsaw. But it's gone ahead and created that campaign brief, looking at historical runs, looking at all of the data in the Work Graph and assigned it out to Stephanie and Christy to review.

Now perhaps Stephanie and Christy are on either the legal team or maybe they're in a different team that's sort of dissociated from marketing. And they don't actively work within Asana, they prefer working out of comments in Google Docs. Now Asana AI Teammates are plugged into Google Docs as well. So when they create that brief and when Stephanie and Christy go ahead and provide feedback as comments on that doc, this multiplayer experience where multiple human beings are interacting with an AI artifact, all of that can be incorporated by AI Teammates.

So AI Teammates work in a multiplayer way, not only inside of Asana, but also on artifacts like Google Docs that are outside of Asana, which is super, super cool. So you'll notice that Kirk who's on the Asana AI team asked for that feedback to get incorporated. It's got incorporated. And now this particular campaign brief task is complete and off to the races. Now that was a good way of showcasing how Dash can trigger some work that can automatically generate results via AI Teammates and then AI Teammates work in this multiplayer way.

Let's take a look at how Dash can help you with unforeseen issues, something that's the risk to your project plan. What happened to -- this actually happened to us within the R&D team. One of our PMs who was leading AI Teammates was expecting a baby. The baby came early. Everything is fine. The baby is happy and healthy, but it means we now have to find coverage that we were not expecting. And so you can simply talk to Dash and say, I need a creative brief, I need competitive research, I need copy because you're getting really, really close to Work Innovation Summit in London. Please help me out. It can analyze the work and start creating subtasks that can be handed off to AI Teammates.

Again, this is going back to what Dan was calling out where we want to take the guesswork for the knowledge worker out of trying to understand how should they bring in AI agents, what AI agents to bring in, what AI agents are approved for use within my company to -- you can simply talk to your AI Chief of Staff. Your AI Chief of Staff has your back. It knows all of the approved AI Teammates that you have access to. These AI Teammates with shared memory and the Work Graph context are constantly being improved by your entire organization of your team, and you can hand a task and going build that first cut for you.

So it's handing off all these tasks. And what's going to happen next is, if you say go, the competitive market researcher will be scanning across both deep web search as well as historical data. The copywriter will be generating copy. The creative spec writer will be drafting specs and it could be in word documents or Google Docs or your campaign hero assets could be created. And so this is showcasing one of our deeper integrations. This is with Figma Make, where social assets are created directly with Figma for the launch.

I click one back too far. So this is a really interesting vignette that's showcasing orchestration of multiple AI agents. And again, the AI agents being recommended directly by your AI Chief of Staff across the set of AI agents that, that individual within your company has access to, all within enterprise-grade governance and auditability, all within the context of the Work Graph and all powered by really interesting concepts like shared memory.

So now I wanted to end this demo vignette for Agentic Work Management by talking a bit about how Asana's data is available across a variety of other AI applications as well. So in this part of the demo, let's say that Kevin, who is our Chief Revenue Officer, is heavily on the road, and he needs to stay up to date on what R&D is up to, and he needs to know if he can pitch one of our upcoming products like Asana Dash to Danone, who's a customer in EMEA. He doesn't know for sure if this will be available in EMEA as yet.

So he can simply pull up Claude on the phone. Claude is connected directly into Asana, and he can ask Claude hey, what's the latest status on Dash. And all of this data that you're seeing on the screen is being pulled directly via Asana's MCP connector. So you can go ahead and pull out status on whether the PRD is complete, what risks are and if you can actually pitch Dash to Danone during his customer meeting.

Now the reason why we would have this is for single-player use cases where you've got an executive or somebody who's not directly in the project and they just need to get status updates or things like that out of Asana, we want Asana to be available in all of those canvases as well and not restricted just to things like Asana Dash or AI Teammates where somebody has to make a conscious decision to dip into the app.

Again, we want the entire enterprise to get the value out of the Work Graph, get the value out of what we are able to accomplish with Asana's AI Teammates and the other AI features.

Okay. So that, in a nutshell, is Asana Agentic Work Management, a completely reimagined way to go ahead and think about collaborative work management. It's now no longer just human beings coordinating projects and tasks. It's human beings and AI agents. It's no longer just projects and tasks, it's chat, it's e-mail, it's documents. And it's built on these 4 fundamental features, Asana Dash, AI Teammates, AI Studio and MCP connectors and apps.

Okay. Now that was just 1 of our 5 Agentic applications that we want to talk about today. So I'm going to cover off 3 more and then hand it back to Dan for StackAI. So let's take a look at Asana Service Management, which is our AI native Enterprise Service Management desk for HR, IT, facilities and legal.

All right. So a question would be like, hey, what is unique and what's interesting about Asana Service Management? Well, first of all, we are leveraging all of the AI infrastructure work we've built and all the integrations into chat tools to provide instant AI resolutions in the flow of work. It's a 24/7 AI agent that automatically deflects about 50% of routine requests and it can be present in Slack or Teams or e-mail or in Asana portal.

The second thing that's even more interesting is for questions that actually become tickets that a human being has to go ahead and resolve, we've built a self-learning knowledge base. So the process of resolving that ticket automatically gets qualified as a knowledge-based article that a human being can read or can be leveraged via instant AI resolutions.

And again, the process is building on the foundational platform work that we've done for things like shared memory that you saw earlier on. One intuitive intake for every team. So there are multiple internal teams that have help desk or service desk. It's not just the IT team for break fix IT issues. It could be a legal team, it could be a finance team. It could be a creative team. This is something we've historically seen a lot of in Asana. There's a lot of Asana customers today, I would say, about 20% of our existing enterprise customers where Asana is sold into the office of the CIO or the IT team, and they're using us already today side-by-side with ITSM products because Asana is really good at providing the single desk for all of the enterprise service needs.

And it's also really good at the last thing, which is when a ticket is no longer a break fix ticket, but actually has to be a project, like you're rolling out an upgraded product or maybe you're moving from one CRM product to another. Anything that's a project is really, really great to track in Asana. We see this use case today where we are already being used side-by-side within these IT deployments when requests turn to projects. And Asana Service Management will have that seamless integration where you can go from request to projects in one click. And of course, project management will be part of the package as well.

So let's take a quick look at what this would look like for a customer who's deployed. The IT desk or maybe people within these various departments like services or workplaces or legal are drowning in a sea of inbound Slack messages. And that's happening because nobody particularly wants to go ahead and raise a request via the IT ticketing portal. The historical legacy IT ticketing portals are places where questions kind of go to get stuck, takes a long time to get a response. The IT teams or the help desk teams themselves are overloaded.

So we have to get to a better way. We have to get away from this legacy enterprise service management where things are just like sitting in these like queues and they're costing a lot of human labor to go and get a resolution. So with Asana Service Management, when that ticket gets raised, and that ticket could be raised in a variety of places via your portal, via Slack, via e-mail, the first thing that happens is our AI infrastructure catches it, automatically routes it to an expert AI agent and tries to go ahead and resolve it without it ever reaching a human being. And this is, again, by all of the AI infrastructure work that we've built for Agentic Work Management.

And we've been deploying Asana Service Management internally already, and we are seeing pretty good AI deflection rates. And we believe by the time August comes around when this is going to be in early access, we can get it to that 50% number that we are pitching.

So the first thing is, okay, all of these input channels, how do you go ahead and automatically deflect them so that they don't become a ticket, they don't even hit a human being. The next thing is for something that actually requires review by a human being. So this legal review for a vendor's NDA, this is probably something you don't want to get autodeflected right off the bat. But when it gets to a person, what happens is that interaction with the person is codified in Asana's Work Graph and we can go ahead and incorporate all of that learning directly back into the finance knowledge base.

So the next time a question like that comes up, the Asana AI teammate can take a first crack at getting to a 90%, 99% good resolution. So the amount of human interaction time even for a ticket that requires human oversight can be driven down massively. So there is a sneak peek, early preview of what we've been doing with Asana Service Management. Again, like this is selling into existing customers that we have as well as growing our base in terms of like new accounts we could target with a specific job to be done. And we've also got a whole host of design partners we've been working with. As I said, we've rolled it out internally, and we're seeing really great AI Agentic AI resolution rates. We've also got NYU, Callen-Lorde, UpGuard, LEAP, Harvey and RICOR as design partners for Asana Service Management.

The second product I want to talk to you about is Asana Client Management. This is all about building lasting client relationships on an AI-native platform that's built for agency work, okay? So what does this mean? Let's dive a bit deeper into what we've got here. Now something that you may not be aware of is we have a large set of existing Asana customers today who are already using us for agency work. They're using us to track resource management and capacity planning. They're using us to track their project work internally across like different teams within their agency work.

But what we haven't provided till date is this branded client portal to complete the journey, okay? So how do you do intake? How do you have a clean branded client portal so the client can log in and see the status of their projects. Again, like how do you connect up these newer Work Graph elements like meetings, how do you connect up these newer features like time sheets and budgets.

So all of that new Work Graph content as well as all of the new AI platform capabilities are being combined together along with this new branded client portal so we can complete the journey for client work. So unifying all communications, ensuring multiple agencies are productive with AI agents, accelerating work across the business with agent capacity planning, statement of work creation, client-ready asset production, status update drafting.

So all of these jobs to be done are now connected under one single umbrella. So it's super, super cool. This is also going to be available in the August, September time frame. And it connects the dots not only for these existing customers who have been using us already for project work within their agency businesses, but also attracts net new customers who might be concerned about, oh, I don't want to bet on multiple products. Asana is great for project management, but I need the client portal. Now we're eliminating all that choice like just go with Asana Client Management and complete your end-to-end job to be done.

The final sorry, this is a slide that talks about all of the existing professional services teams that are managing client work over Asana today and clarifies like why I am excited about it from a product strategy perspective because there already is clear indication of product market fit, and we know who the ideal customer profile is.

All right. Great. So now I want to take a little bit of time to talk about Command by Asana, which from an R&D point of view is super, super interesting because it's a way in which the Asana research and development team has been working probably for the last year, where we have gone all in on Asana to track the entire product development life cycle to trigger coding agents, to trigger code review agents, to do our security and compliance processes. And we've been seeing phenomenal improvements in productivity and cycle time.

But because this was a highly customized way of deploying Asana, it was not something that we were able to bring to bear for our customers in market. And Command by Asana is a productization of that end-to-end experience. So a good question would be like what is the value prop for Command by Asana? And from a customer's perspective, why should they change now? And why should they change to Asana? So a really interesting thing that's happening in market today for engineering teams is the rate at which you can generate code is faster than ever before with these really cool coding agents like Codex and Claude Code that are available in market.

But the problem that most companies are running into, and there's widespread coverage of this where people are running out of AI budget. There's some commentary from Microsoft and ServiceNow and Uber about the amount of spend that they have, but they're not really seeing truly improved product delivery and cycle time. The reason why this is happening is coding agents are currently really good at plugging into your GitHub repo or your source code and then learning from that.

But what's not happening is an agentic way to improve the entire product development life cycle from ideation to PRD creation to ticket creation where the ticket has all of the context required to then run the coding agent effectively to take all of the decisions that happen in those loops where you might decide to change the spec slightly or you might decide to react to a bug once you evaluate the first initial PR, none of that gets recodified back into the PRDs of the tickets. And then ultimately, the final product that gets delivered is not connected to the rest of your planning and development life cycles around product launches or scheduling, downstream activities and so on and so forth.

So we want to create that software development factory where you go from ideas to shipping products that your team can sell in the fastest and safest way possible. So ship faster with humans and agents in sync. So there's 3 different things in here from a feature perspective, cleaner tickets with faster agentic output on repeat, no manual reconciliation of things like sprint planning and capacity planning and always on visibility into risk, drift and dependencies. Because, again, like this is all powered by the Work Graph and shared memory.

So as you do more and more projects within Asana, it can detect when you are running into a risk, when there might be drift between the PRD and the PR. And then what are all of your cross-team dependencies where if you look at the Gantt chart of everything required to go deliver your product, how do you reconcile those issues. So those are 3 key features that are part of Command by Asana.

And so I'll kind of walk you through a flow over here, which is everybody within Asana, we all love to build. We've got product managers who have been building prototypes as well as fixing lots of the customer issues. Of course, our dev team is all in on the latest tools like Claude, Cursor and Codex. And our designers are also like fixing defects and shipping visual updates as well.

So how are we doing this? Like what is this command by Asana way of working? And it's like a totally new way of doing it and building product. So we want to take this like process of requirements, plan, code, coordinate and ship and convert every single step of the process into an Agentic workflow. So requirements and planning are scattered across multiple different artifacts today. You might have a live meeting with your team. You might have a word document that's tracking a PRD. We want to agentify that entire process, again, leveraging the platform components of Asana.

When you're coding, again, once the PR comes out, coordinating across multiple people for code review or evaluating the security reviews is something that again happens in a disparate system. And then finally, when you're shipping, that product marketing team or that actual executive leadership team within product is disconnected from the systems today.

So when they ask a question, let's say, when Dan asked me a question of, hey, when is this thing shipping, that's a very reasonable question. But it often becomes this sort of multipronged access request to like figure out, okay, what does the engineering manager and one team think? And is the product marketing manager on that project like in sync with them and so on and so forth. So we believe there is a better way. The better way is Command. Command helps you go ahead and author PRDs directly from those meeting minutes and notes. It helps you iterate over those PRDs so that you can go ahead and break them down into tickets that are ready for coding agents like Codex and Claude code and closer to pick up with the appropriate amount of context provided by the Work Graph.

We do capacity planning in a way that is highly coordinated and agentic so you can coordinate across both human and AI agent tasks. And then finally, you can plug all of that into Asana's Project Management tooling and things like AI Teammates. So if you ask a simple question, like when does this ship, something like the Houston project planner team made that Dan called out way before in his early part of the talk track can instantly by saying respond by saying it's still on track for June 4.

All right. So that's a preview to a command by Asana. We've got our R&D teams using it actively today, and I'm super excited about bringing this to market again in that September time frame.

With that, over to you, Dan, to talk to us a bit about Stack AI.

Thank you, Arnab. So yes, Stack is really the missing piece to the puzzle. We described this on our earnings, and I'll go a little bit deeper here. So this was our acquisition. And it turned out that most of our customers want to identify these workflows and that many of these workflows, the most complex workflows actually span across multiple systems, databases, CRM systems, order management systems, you kind of name it.

And so what Stack has built is this ability to quickly visualize and automate any workflow with no code. And you kind of see here a little bit on the right, this is literally the UI. And they can drag and drop any of these workflows that hit multiple systems with prebuilt integrations. They have literally built hundreds of integrations, and they can build net new integrations very quickly. And so what this allows you to do is create rules that kind of move from humans to various other systems and in this case, back to Asana teammates and Asana agents.

And so what you end up with is that ability to visualize and imagine a workflow and what you want -- how you want to automate it and the rules that you want to set in place and which bits you want to identify and which bits you want humans to take care of. So Stack actually as a stand-alone product is going to be commercially super viable. It's already a commercially viable product. But it will also feed into all of those other products that Arnab just showcased as a logical extension of how you want to do service management, how you want to do some of your developer workflows.

So StackAI both becomes a product and a capability across many of our other products. And these are all governed. And so they already have met the highest requirements for federal and enterprise customers. So that stack and really, and I sometimes describe it as a missing piece to the puzzle.

Let's go to the next slide. So at this point, we'll talk a little bit about our right to win and our differentiation. Again, we covered a little bit on this in earnings, and we described this in a much more visual way in some of the keynote that we just delivered. But just to set a little context here, here's kind of the journey that we've been on, our multiproduct journey. So back in June, we launched AI Studio. AI Studio has had a very nice commercial ramp. So monetization really started to take hold.

And then as you get towards the December time frame, we start hitting some decent commercial milestones on AI Studio with many customers spending over $100,000 on that capability. Launching of AI Teammates. So we go from the beta of our AI Teammates to GA of our AI Teammates. So at this point, we really have a couple of other products in our portfolio.

We acquired Stack in June and launched Agentic Work Management. And through Agentic Work Management, AI Teammates in AI Studio will be discovered now in the line of your work. They will recommend themselves as you go about your regular daily tasks. And as we look then a little bit forward into the second half, our new product portfolio, which is all Agentic workflows, all built for human agent teams is Agentic Work Management, Command by Asana, Asana Service Management, Asana Client Management and Stack AI, all of which allow us to not go just further into other buying centers, but also deeper into the buying centers that we are already in today.

So touching our differentiation a little bit. The first is these are all underpinned by our platform. Our platform has 4 very unique architectural differences, the Work Graph, which we think of as a neural network of the connections between all of these primitives of people, tasks, projects, this living plan that allows everyone to know who's doing what by when. And by everyone, I mean both humans and agents.

Our multiplayer mode, which is the ability for humans to train, guide, improve, provide feedback to any of those agents. Our shared memory, which essentially self-improves every run of every project. And then finally, our enterprise governance, which means every agent automatically scoped and permission in terms of what data it can access, what cost it consume and which approvals it can make on its own and which ones humans are going to have to make.

So built on top of that platform of 5 AI capabilities and these AI capabilities all serve our products, which is how we go to market. So these are the 5 applications that we will go to market with. So this is the new lineup. This is the new Asana. And I'm now going to hand over to Aziz, who's going to describe what this -- the financial implications of Asana.

Thanks, Dan. So while we're still early in this journey, the initial proof points of our multiproduct strategy give us confidence we're moving in the right direction. So as we shared last week at our Q1 earnings, in-quarter NRR has improved for 4 consecutive quarters and reached 97% in Q1. And a lot of that improvement has to do with the expansion and retention that AI studio is driving within our base.

We also saw our technology customer base return to year-over-year growth in Q1. That was after 8 straight quarters of decline and then stabilization in Q4. Our AI product bookings represented 17% of net new ARR in Q1, which was ahead of our FY '27 target of 15%. So our AI products are contributing faster than we had expected. And at the same time, productivity improvements and operating velocity are translating into meaningful margin expansion, demonstrating that we can invest in innovation while improving profitability at the same time.

So now moving to our pricing model for this AI multiproduct platform. It's really about meeting customers where they are with flexible monetization models ranging from seat-based subscriptions with AI-powered expansion path to request and resolution-based, workflow-based and credit-based offerings. The common thread between this is that customers can start with predictable platform subscriptions and expand as AI usage, workflows, agents and outcomes grow. So this approach provides customers with predictable costs and no surprises while enabling Asana to align monetization with customer value and better matching the outcomes being delivered.

So this creates a scalable growth model with greater visibility in the unit economics and margins as AI adoption grows. So I want to just touch upon this reinforcing growth model that we're creating as we transitioned into a multiproduct company and expanded into new buying centers and TAMs. So historically, Asana was a single product collaborative work management platform with growth driven primarily by seat expansion, package upgrades and then adoption concentrated in a handful of buying centers and departments.

So over the past year, beginning with AI Studio and Teammates and then significantly amplified by the announcements at the Work Innovation Summit last week, which we shared today, Asana has evolved into a multiproduct platform for human agent teams. We have multiple ways to land customers, expand across workflows and departments and monetize value through both seats and consumption. So that evolution expands our addressable market, increases workflow depth and customer value and creates growth vectors beyond traditional seat expansion.

So the result is a reinforcing growth model with more paths to land, more opportunities to expand, deeper customer engagement over time and really setting the foundation for durable growth acceleration and long-term value creation. So with that, we'll open it up for questions. Eva?

I guess what we -- a lot of investors have in their mind is why is Asana launching this new Agentic apps right now, particularly Asana for Service Management and Command by Asana. It feels like a change in your multiproduct and adjacent TAM strategy. Can you kind of talk a little bit about that?

Yes. Why don't I take that one? It turns out that we have been serving many different buying centers with our horizontal platform already, marketing teams, IT teams, product development teams, operations teams. And as they got more deeply embedded with our products, they began to describe workflows that they wanted us to build, agents that they wanted to bring to bear on their work, the new capabilities that made themselves possible.

So we began a design partner program with each of these areas to try and figure out what they wanted from us next. And it became obvious that they wanted bespoke applications, bespoke agentic workflows and teammates that could operate within their teams. And hence was born really an incubation mindset of bearing out these products for these particular buying centers for these particular verticals.

And so yes, through the design process and really how we launch products, we came to learn exactly what the requirements are and could build all of these of the same Work Graph foundation that actually makes everything makes sense for the human agent teams.

Thank you, Dan. Another question we have is, how do you win against ServiceNow, Atlassian Jira and other incumbent with this new Agentic app? Maybe, Arnab, maybe you could take that.

Yes, sounds good. So I'll break it down into maybe 2 different categories. Again, I'll choose Asana Service Management and Command. The framework that we use within the Asana product team is answering the question, why should the customer change? Why should they change now? And why should they change to Asana from whatever they're doing for the Enterprise Service Management or current R&D processes.

So when you take a look at like why should they change within Asana's customer base, as Dan was calling out, we are already seeing about 20% of our existing customers be within the IT organization because they have a pain point around tickets that can't be serviced by those ITSM products when they become real projects. That was like an existing change that made it an existing reason to change that introduced Asana into those companies in the first place.

The second thing is with the advent of AI capabilities, there's a massive push to go ahead and drive down internal operational costs. People want to identify their workflows. They want to change now to something that actually provides that level of 50% ticket deflection, proactive coaching and so on and so forth.

Then when you take a look at Asana's differentiation in that area, well, first of all, not only are we able to deflect the tickets that can be answered by knowledge-based articles with our AI infrastructure and capabilities, but we can build these self-learning knowledge bases, we can connect up human interaction in a way which generates shared memory. We can connect a human interaction in a way that can elevate things that are no longer tickets into true projects and the project can work on Agentic Work Management. So there's like 3 levels of things. We're already in a bunch of accounts today, solving the project management use case, even with our historical products.

The second thing is AI is causing every single customer in the world who has an Enterprise Service Management team to reimagine, reevaluate what would it take to make it Agentic. The third thing is we're providing this connected Agentic way of solving that problem in a way that's not just ticket deflection, that's not just automatic knowledge-based creation, but it's generating these end-to-end workflows even for the most complex tasks.

So we believe strongly that we have a right to play and win a substantial amount of that market. The same thing can be applied to command and the R&D processes. Again, like historical tools are designed around sprint planning, ticket management, bug management for a largely human-driven process. That's human beings getting together, they're planning our capacity. They're doing things like story pointing for those who have been in agile R&D conversations in the past. All of that is gone. Like there's a massive change in the way in which you work because the cost of actually generating the code is going lower and lower every single day.

The problem that's happening is how do you set up the right context so that when that code is generated, that PR, that pull request is something you actually want to ship. If you keep going back and forth with that PR because you're trying to prompt your way to the best possible outcome, you're going to burn through your tokens really fast, which is why you get all of these reports in the media today about people burning through their budgets as they've invested in AI coding.

So again, Command is a totally different way of working where you go from ideas to the entire product developer life cycle in a fully Agentic manner, contributing into Work Graph assets to create that company brain that makes it run faster and better every single time.

Great. Thank you. And maybe one question on go-to-market. You're expanding into IT, engineering and professional service buyers. How would your go-to-market model evolve over time?

There will be, I'd say, 3 themes. One is new buying centers, which means that we'll need to learn some new languages for those buying centers, and we have the ability to do a lot more cross-selling within our accounts. The second is the criticality of the workflows that we'll be going after. So we'll be able to, I'd say, go up in some of these accounts because we really are going to be attaching ourselves to much more business-critical workflows that are the core of these enterprises.

And then finally, because we'll be moving to some more consumption and outcome type of meters, adoption will become even more important, making sure that we hold customers' hands to get those workflows lit up in the first place. So those are the ways in which I can see us evolving.

Great. Thank you, Dan. And maybe just one last question for the group. If AI models continue to improve, why doesn't the value accrue to Anthropic, OpenAI and Microsoft or another platform company instead of Asana?

Yes. Well, as we -- actually Arnab, you want to go ahead, then I will go.

Yes, sounds good. So I mean, again, let's take a look at the advances that have happened in the models even in calendar year 2025. They've gotten exponentially better. But when you look at research reports from Goldman Sachs or McKinsey, actual productivity improvement within a company's outcome or job to be done, there's been no improvement. And the reason for this is the reasoning models are amazing at going through tasks and sort of taking the context that they have and iterating through it. But most of the choke points now lie in all the scaffolding around it, the context, the shared memory, the human interaction, like how does a human being even reason about the rate at which these results are coming out.

And we've already seen that data play out in 2025. And so our thesis is that, okay, even if the reasoning models get better, like the rest of the scaffolding has nothing to do with AI. Like it's actually hard data about context graphs. It's hard data about the human in the -- multiple human in the loop processes to get human beings to rock and understand what's going on and so on and so forth. So Dan, let me know if...

Yes. Thank you. That's good.

All right. That concludes our Q&A session. Thank you, Dan, Arnab and Aziz for your time today, and thank you for everyone who joined us. We've covered a lot today, so we hope you leave with a clear picture of what Asana is building and what we're positioned to lead this category and how the financial model support this durable value creation over time. For any follow-up questions, please reach out to me directly at [email protected]. We look forward to continuing this conversation. Thank you.

Thank you.

One second, guys. those of you who don't know me, my name is Matt Bullock. I'm an application software analyst here at BofA. And today, we're really lucky to have Aziz Megji from Asana, the Chief Financial Officer. So thank you so much for joining us.

Yes. Thanks for having me.

Awesome. So maybe just to get started, I want to start with a high-level question about where Asana sits in the agentic technology stack. So you talk about Asana being the operating system for humans and agents. Where do you envision the company longer term? And how do you differentiate against the foundation models?

Yes, absolutely. It's great to be here. So we are -- Dan Rogers, our CEO, repotting the company and really transitioning from human-to-human collaboration in CWM management to this operating system for human agent teams.

And so what does that mean and where does that sit? So as we think about that intelligence layer being the LLM and as more agents are created and execute more work, it just creates the need for more coordination, execution governance and collaboration.

And we really -- that's the layer we sit, right, on top of that LLM or intelligence layer to drive that coordination, which is going to become so important and critical as the proliferation of agents and agents with humans and first party and third parties all come together.

And so if you think about our approach there, it really stems from the historical architecture that has made us so successful in driving collaboration and productivity for human teams, the Work Graph. So this architectural layer that inherently is multiplayer, which is the context layer for how an organization is not only organized, but the work that is executed within that organization, who's doing it, what, when, where, why, how, the governance layer that provides the right access and controls.

And so that architecture and the persistent memory it drives is exactly what this coordination layer on top of the intelligence layer needs to drive productivity in an agentic world. And we've approached that with three different products, AI Studio, AI Teammates and our recent acquisition of StackAI. I'm sure you'll unpack that. But that's where we sit.

And actually, if you think about that layer or that positioning, Anthropic, one of the world's most successful AI-first companies, uses us as the coordination layer integrating [ Claude ] with Asana back to the Work Graph to drive productivity for their workforce. And as they've grown, we've grown. So I think that's kind of validation of the need for this layer and it's important of its role in the agentic enterprise.

That's fantastic. Thanks, Aziz. Maybe just help us think about as agents become more prevalent, how the fundamental value proposition of Asana changes, given that the kind of the core foundation of the platform has been human-to-human coordination? As agents become more prevalent, how does that shift the value you create over time?

Yes. So as agents become more prevalent, as they go deeper, as they proliferate into different functions and tasks, again, it creates that need for that coordination, that governance, that context, that persistent memory layer that we drive. So we view ourselves really as the rails which agentic work really takes place and the Work Graph being that center architecture that enables it.

And so with our AI Teammates, you can execute work in an agentic fashion. We have 20 out-of-the-box Teammates, whether you're launching a campaign where you're executing a research brief; whether within a different workflow, you want to use an agent to execute a task or move a process step from one step to another, those Teammates really play a really valuable role in that coordination.

We also have AI Studio, which is our workflow automation layer. So within the four walls of Asana being able to drive routing, data intake, quality control and process, operational process improvement, AI Studio plays a really valuable role in that.

And then we recently acquired StackAI, which is kind of the -- puts it all together in allowing us to drive complex cross-system workflow automation and orchestration and then bring all that context back into the Work Graph or the Work Graph back into StackAI.

And so we view that three-pronged approach to the three different jobs to be done in the agentic enterprise as now being that AI platform that we're building that's built on the Work Graph and this architecture that's worked so well for human-to-human teams that we believe is going to be the right architecture for human and agent teams.

Fantastic. And you've mentioned several of the new products. You're now officially a multiproduct company, which is fantastic. You've got AI Studio, AI Teammates now rolling out more meaningfully this year. StackAI, as you mentioned. How does the pricing and packaging model of the company have to evolve, given all these new AI products and the historical seat-based model?

Yes. So I think like many software companies, we're in the learning mode and the data aggregation and experimentation mode. So we have four different pricing models today. We have on our agentic work management platform, which is our heritage work execution platform, a traditional seat-based model.

AI Studio, which we came out with about a year ago, is on a credit model. So you prepay for credits. And as you exhaust those credits, you buy more and top up. AI Teammates is on a request or execution model. It comes with a certain number of executions as you exhaust that, you top up and buy more. And now with StackAI, they're on a platform fee and a per builder per workflow model. So it's very consumption-oriented as you drive more workflows, that's their upsell and expansion path.

So all of those pricing models are today what's within our base and how we sell. But we're learning. So within each of those models, there's variations, there's evolutions. We're experimenting with, okay, what if we take the AWM and give you a trial with this many studio credits or this many teammate requests? How does that change the upsell and expansion path or reduce the friction to adoption of our AI products?

So you can see over time that the lines between platform or seat and consumption will blur. And the predominant mode of growth and expansion will be consumption or consumption like, driving usage with outcomes that are creating ROI. Right now, we're learning what's the best way to package it because some of these things are fairly early. But we're getting good data and good signals. And I think we'll know a lot more as these quarters progress this year.

Fantastic. And I wanted to talk a little bit more about AI Teammates because you've been very consistent about framing this as one of the most exciting opportunities for the company, the largest TAM, I believe, of the AI products. Maybe just help us think about how Asana thinks about the ideal customer profile for adopting AI Teammates. How does that journey -- or how do you envision that journey taking place for a lot of your customers?

Yes, absolutely. So Studio -- let me start with Studio. So Studio came out about a year ago. And where Studio, we saw the most value is in existing customers who've built rules, built automation, they have more complex deployments of Asana. They populated the Work Graph pretty fully where they can drive the benefit of automating and supercharging workflows with Studio. And so that has a TAM. It's grown really nicely. It's a nice land-and-expand path.

Teammates, we've seen a lot of success with penetrating those studio customers. And instead of having kind of human-to-agent handoffs within a stream of a workflow, having human-to-agent, agent-to-agent handoffs, so the agent actually executing within the workflow as they were the human; that's really powerful for those studio customers are within the flow of a workflow.

But we've also seen a lot of value in people using the Teammates to execute, to coordinate, to reason, to provide input to not only individuals, but to teams. And what makes teammates really special is that they're inherently multiplayer.

My teammate interacts with my team. My team provides prompts and questions and directions to the teammate. My teammate accesses the work graph and the content and context that I'm able to transverse within Asana. And so it makes it super powerful.

And developing that multiplayer architecture is really difficult. It's not something that you'll get with LLMs or most other applications, being able to have truly a teammate that is for the team and for the organization. And so that's where we see a lot of value.

So the entry point of Teammates can be within a workflow, it can be outside of a workflow. It can help you populate and set up your work and your environment in Asana in the way that it's intended to be, which is super exciting.

And for our PLG base, it is an exciting opportunity because Studio has applicability in PLG, but Teammates has broad applicability in PLG. And that comes out in the second half, and we're really excited about the growth prospects that, that will drive in PLG.

And maybe just to pivot here, I wanted to talk about growth and some of the key metrics you guys have been putting up recently. Specifically net revenue retention, very consistent progress there over the last several quarters. I believe this most recent quarter was a more meaningful step up, but we're still seeing kind of the reported trailing 12-month net revenue retention number stable.

Can you maybe just help us think about the puts and takes of net revenue retention throughout the rest of this year? And what gives you confidence that you can get back to, let's say, 100%?

Yes. So we are encouraged by the trends on net revenue retention. So we've seen now 4 straight quarters of in-quarter improvement in NRR. And this past quarter, Q1 had the largest step-up or increase in net revenue retention versus those other 4 consecutive improvements. And it's both on expansion and retention.

And what's really encouraging is actually the largest share of the improvement this quarter was on expansion. And over the past 2 years, as NRR has trended down, the biggest catalyst for that degradation has been expansion. So seeing our AI products drive expansion within the base is really encouraging.

And so far, it's mostly Studio because Teammates is new and Stack is extremely new. So layering those on and building those motions, we feel confident that we'll further improve that expansion trend. So that's really been very encouraging and great to see.

And if you look at our AI Studio cohort of customers, we're not only seeing them expand with the AI products, but also with seats. So as they're seeing value from AI Studio, driving AI Studio deeper into their mission-critical workflows, they are expanding their footprint with Asana to drive more value for more teams with AI Studio.

So we've seen great seat reach with those customers. Actually, that cohort, the AI studio cohort has had the strongest NRR of any cohort in our base. And so that has also contributed to the NRR expansion.

Now when can we see it back to 100? I wish I had a crystal ball. But the trends are our friend there. Q2, we will lap our large customer churn we saw a year ago in Q2. So that's another catalyst for expansion. And then as we continue to build the motion with Teammates and Stack, those are important catalysts.

And if you think about Teammates, it's just been GA for a couple of months. It's not in the PLG base until the second half. And the flywheel on Teammates is really get a customer to enter into a trial. That trial is 30 to 60 days. They see the value of Teammates within the trial. They start with a small land. They then exhaust their request within that land. They buy more credit packs, then they add even more credit packs because they want to bring it to more teams.

And you see that flywheel build and build. And eventually, they've gotten those teams a lot more value. They're deeper in their workflows. They're seeing productivity gains, and they want to expand seats. So we're very early in that flywheel because it's only been 2 months since it's been out.

But as that builds and compounds, it should also have a benefit to net ARR expansion. And so getting over to 100 is the goal. I think it's a key unlock and a milestone moment for us. I think the trends are encouraging. We have some good catalysts coming out of Q2 with the large deal lapping off. And then as the flywheel builds and we start seeding stack AI more into our base, there's additional catalysts along the way through the year and into next.

And I wanted to ask one quick follow-up because you did mention the large customer churn last year in the second quarter. So that was -- I assume you mean the $100 million-plus TCV deal that you signed that was accompanied with a slight ACV downgrade that you were comfortable trading for greater long-term visibility.

Is there any risk or opportunity associated with the 1-year anniversary of that deal signing coming up this year in the second quarter, whether that's upsell opportunity or downsell?

Yes, it's contracted for multiple years. So there's no risk on a downsell in that customer. But the seats that we have deployed, they continue to use more and more seats. There are seat expansion opportunities over time to upsell and expand with that customer.

We deliberately designed the deal to not include Studio as we saw that as an expansion path. So over time, we see that as a lever to expand with the customer and Teammates as well. They're a beta customer of Teammates, and we think that's an opportunity. So over time, we think there are opportunities to expand and grow that footprint, but no risks in the near term, it was a multiyear deal.

Got it. And maybe just to zoom out to dig deeper into the multiproduct strategy. As you become not just a traditional CWM vendor, but you're also now layering in Agentic capabilities, more workflow tools; has the buying persona shifted at all? Or do you expect it to shift over the next few years as the makeup of the product offering changes?

Yes. It's a huge opportunity for us to expand the buying persona and deploy this agentic work management platform across -- departmentally because if you can expand from 1 department to 2 or 3 or 4, you're driving so much more power from the Work Graph and the coordination that will drive for human and agentic teams.

And so as we think about what are the catalysts for that, we have been a very largely horizontal company for most of our existence. That large customer that you cited has been so successful with Asana because they have this incredible builder culture, and they've built on top of this powerful horizontal canvas workflows and rules and the connections across departmentally that are extremely diverse and global with the scale of a multi-hundred thousand person organization.

For us, driving that departmental expansion and expanding into new buying centers, I mean really strong in marketing, really strong in PMO, inroads in operations and IT, strengthening our footprint there is really through Teammates, Studio and now StackAI, where we have 20 out-of-the-box teammates.

Those teammates can look like ticketing agents. They can look like development, agile process development teammates. They can look like vendor onboarding, employee onboarding teammates. So they expand the reach of our platform to new buying centers, new personas, new ICPs, and that's super exciting.

And then with StackAI, that gives us a whole new land strategy that doesn't have to be tied to Asana. We can now, for the first time as a multiproduct company, land with a customer without having to sell [ CD OEM ] and then upsell and expand with CWM later and with Teammates, create the right connective tissue from cross-system workflow automation back into the Work Graph and Asana, which is a really powerful thing.

And Stack appeals to many new buying centers, too. They're very strong in IT. Their target buyer is an IT and operational buyer. That is an emerging opportunity for us. There's a lot of synergies.

So as we build out teammates, as we proliferate the out-of-box teammates, as we integrate and drive expansion with Stack AI, these are all catalysts to expand our TAM, expand our buying centers and drive adoption across departmentally, which is a real value unlock for the Work Graph and the platform.

That's really helpful. Maybe just to pivot to -- away from the departmental focus, but more towards the vertical side. So obviously, technology has been a little bit more of a challenged vertical for Asana over the last several years. But we're starting to see some green shoots. You returned to positive growth for the first time in, I believe, 8 quarters during the first quarter.

Can you just help us think about the trajectory for the technology vertical for the rest of the year? And what you would say to investors that are concerned that incremental technology company layoffs are a risk to numbers or growth potential?

Yes. So that's right. first time in 8 quarters where we returned to growth, and that's after last quarter, Q4, where we returned to a kind of neutral like 0% growth. And so that's encouraging to see. And that improvement is really largely driven by adoption of our AI products and then seat expansion.

Tech companies were early adopters of Asana and this vision of driving higher, stronger collaboration through work and better hygiene through work and better process and productivity as a result, they're also early adopters of AI and AI automation tools that have that same vision and outcome that they're intended to drive.

And so if you think about our 100,000-plus AI Studio customers, which we called out, we had 8 in Q4 and that doubled in Q1, about half of those are tech because they were earliest cohort. They're amongst the biggest fans of Asana, they're very well adopted, and AI Studio was a natural evolution for them. So that has driven the improvement.

In terms of how we factor that in going forward, our guidance reflects more Q3 trends than it does Q4 or Q1. Conservative prudence. We understand that tech layoffs are becoming more prevalent. It's something we've been living with, by the way, for a couple of years. So as our NRR has come down, it's mostly because of our tech cohort not expanding and reducing seats because most of our churn and downgrade has become from seat reduction, not logo churn or pricing. And so it's something we've been living with.

Part of the reason we've only factored in modest improvement in NRR into our guide despite these new products and these AI tailwinds is because of that pressure persisting and understanding that.

We feel better about our ability to mitigate it than we did 2 years ago. We were a single product company with packaging really as our only lever in those conversations. Now we have AI Studio, AI Teammates, StackAI, and we're seeing success of within renewal conversations where someone has let go of people, they want to reduce their footprint and saying, "Hey, for that remaining footprint, why don't you adopt these teammates and this is the value that they'll drive for that remaining footprint or Studio and now StackAI?"

So we have more mitigants that are not seat-based, but we've accounted for potential pressure in the way that we've guided and how we factored in tech growth from here on out and our improvement. If they do better, it's upside, but we've been prudent in how we factor that in.

And we're not seeing trends that materially diverge from the trends we've seen over the past couple of years, like the outliers of the blocks and others who have done very large percentage of their total workforce reductions is not what we're seeing.

We're seeing the continuation of like mid-single digits, high single digits, low -- less than teens type actions, which we've been dealing with for a couple of years and now dealing with more mitigation levers to offset that pressure.

Makes a ton of sense. And maybe just to go back to -- you mentioned Anthropic a few times today. That's, to me, a really exciting customer journey and opportunity. They've clearly expanded their contract value, but also expanded the number of products they've used over the last 6 to 9 months.

So maybe just help us think about how that journey has progressed. And what makes a company like Anthropic want to use the Asana Work Graph and the broader platform so meaningfully?

Yes. So Anthropic has grown with Asana as they've grown with the company. We've had multiple expansions with them, especially over the past 18 months. They became a studio customer mid last year and then a teammates customer early this year. And we're excited about that relationship. It's not only a customer relationship, but we have a very strong kind of product collaboration relationship and now increasingly a distribution relationship.

So we were a keynote speaker at their Code with Claude conference. We have a really strong MCP integration that our customers use where within the cloud prompt interface, you can launch a project or task back into Asana pretty seamlessly.

And actually, a large swath of the Anthropic users and employees are using that Claude connector and kind of using the intelligence layer that is Claude and then bringing it back into Asana, which is the coordination or OS layer.

And so how Anthropic uses the platform really for us is kind of another piece of validation of the value this OS layer or coordination layer can drive on top of the LLM or intelligence layer. They see that. They increasingly use those connectors.

And also the third kind of prong of our relationship is more increasingly a distribution relationship, right? We are within their marketplaces through AEO and how we show up in the LLM is very strong. And so we're building that piece as well.

So we believe this is another kind of data point and the validation of the importance of the OS or coordination layer on top of that intelligence layer. As agents drive more work, drive more complexity, drive more tasks, the tasks move quicker through workflows, it just increases the need for the elements that make Asana special that are enabled through our Work Graph.

Really, really helpful. Maybe just to pivot here to the StackAI acquisition, not a super acquisitive company, Asana in the past. So maybe walk us through the rationale for the deal. I know you've talked about it accelerating the road map by about a year. And the technology itself seems pretty exciting. So help us think about that. And how should we, as investors evaluate the return on that investment, whether it's from growth, win rates? I would love to hear speak about that.

Yes, absolutely. So we're super excited about bringing the StackAI platform and team into the Asana family. It just closed I think like 4 days ago. And the genesis of it is we had heard in some of our pursuits on AI Studio that the customers have been using this really interesting thing called StackAI, they loved it, right? And they're like, what is this thing? And why aren't they willing to switch from it?

And then you do a little bit of research. And so Dan, our CEO and our CPO, Arnab, kind of looked into it a bit and said, "Hey, this is really interesting. The drag-and-drop interface is really, really simple and intuitive to use. It's really easy to hook up systems and there's 100-plus integrations, the [ rag ] layer is really strong, like this is really hardened from a back end and compliance and asserts that they have. Their customer list looks awesome. Like let's dig in a little bit more."

So then we got to know them. We did kind of this proof of concept in our marketing department where we identified our SEO process using Teammates to bring things back in the Work Graph, where we kind of coordinated across 5 different marketing systems. And like the power of the intelligence and the input and the productivity that drove was really like exciting.

And went off -- and Dan said like we should bring this to our customers. And then you go through the buy versus build and partner kind of evaluation. And to bring this in the fold, to accelerate our road map by a year in this rapidly changing agentic enterprise landscape, it just made too much sense. Like waiting a year to develop these capabilities versus having them now just made a lot of sense.

And our customers -- the next evolution of AI Studio are these capabilities. We believe we have a lot of demand in the customer base for this and can cross-sell it and drive acceleration. And so as we think about ROI, it's about accelerating growth and improving NRR. We factored that into our guidance. We believe probably next year, it will have more of a material impact on growth than this year.

As we integrate it, as we drive the right cross-selling motion as we enable our field and as we get those customer validation of Asana kind of Work Graph plus teams with Stack AI, it should compound. But we're super excited. The founders, Tony and Bernard, are like two of the smartest people I've met in this AI world after Dustin and are now part of the family and are going to be driving this and driving the integration and driving the scaling of this within Asana.

So we haven't been an acquisitive company. It's our first acquisition in 17 years. We have a high bar, but like it just -- the synergies were there just culturally, customer-wise and product-wise and made sense to move. And I think we were pretty disciplined about how we structured that from a capital allocation standpoint as well.

That's great. We have 3 minutes here left. So I wanted to make sure I gave the audience a chance to ask some questions. If you guys do have a question, feel free to raise your hand, we'll pass you the microphone.

All right. Maybe I'll just keep going here. So I wanted to ask about 100,000 customer additions because I think broadly, we got a ton of positive feedback on the 1Q results. But the one primary point of pushback was the flat 100,000-plus customer additions. So if you could help us think about that, the trajectory going forward, I think that would be very helpful.

Yes. So I think first, we define the 100,000 customer cohort based on revenue. So having 3 less days in the quarter actually, it impacts the definition. All of our KPIs that we disclosed are based on revenue. And so there is some distortion.

If you actually looked at like the ARR of the 100,000 customers at end of the quarter, it grew. So that's something we're talking about internally so we revert back to our ARR metric because the quarter-over-quarter comparisons are difficult when there's less days or more days in the quarter versus we look at the comparable year-over-year, which grew 12% off a tough comp where that comp was growing 20%.

But that being said, within the 100,000 cohort, we are seeing strong expansion. Those 100,000 customers on an average size are growing. And part of that is the success we're seeing in penetrating AI Studio and 100,000-plus deployments of AI Studio. This is 100,000 buys of the AI Studio SKU, not influenced or attributed. And those 100,000 are often being added to 100,000-plus seat ARR customers. So we're seeing that cohort grow in size.

We're also seeing strength in that like mid-market cohort, which is a real strength for AI Studio and teammates of the 25,000 to 99,000. But the real accelerator of that cohort growing is landing with larger deal sizes and expanding through these AI consumption-first products like Studio, teammates and now StackAI and then having that kind of drag along seats over time as more people in an organization want to get access to these capabilities.

And maybe just to wrap up, we've got about a minute left here -- we have a question.

Aziz, thanks for the presentation. When you're looking at StackAI and you said most of that revenue growth will happen a year from now, what could you do as a company to accelerate that or pull that forward? Or any levers you could do to accelerate that?

Yes. It's like you have -- Dan, you talked to Dan, that's what he pushes out every day. So the levers are enabling and getting this to our field as fast as possible, right? And so you start kind of small with small cohorts because you need to learn and you don't want to like distract the field too early before you've got the right enablement and right sales plays and the right reference customers. But it's really getting the enablement of our field and driving the right sales place to lead with StackAI where it makes sense to lead with StackAI.

I think it will open doors that are open right now because right now, you're leading with CWM, that's a defined TAM and a design customer base that opens it up. And also the approaching that with personas, ICPs and verticals, like we've been very successful with our vertical team, financial services, health care, education, now increasingly state and local and Fed. They are extremely successful in regulated industries because the regulated industries are highly complex processes that are being automated.

So getting that into our team getting faster. So -- but it's really around enablement and creating the right sales place and getting that quick and investing resourcing into stackAI.

So part of the dilution commentary that we made on one point in Q2 and one point in the second half is not only the size of the team and the cost base around them that we're inheriting, it's also what we factored into our plan in terms of investments to augment and accelerate that. Now we have to build pipe and there's a sales cycle and all that, which is why it factors in more prominently on revenue in '28.

Well, we're out of time here. So I wanted to thank you again, Aziz, for doing this and participating.

Yes, absolutely. I appreciate the questions. It's always great to be here with you. And just to plug -- on June 8, we'll have a webinar. We have our big customer event called the Work Innovation Summit a week from Thursday in London.

And so we're going to have Dan, our CEO; and Arnab, our Chief Product Officer and myself, kind of play back the highlights for investors and what we shared with our customers at that event. And I think it will be exciting. You'll learn more about our agentic strategy, what we've been up to on the product road map and development side. And I think it will just reinforce some of the themes we're talking about today and at earnings last week.

Yes, absolutely. I appreciate it. Yes, absolutely appreciate. Yes, absolutely. I appreciate the plug. On June 8, we'll have a webinar. We have we have our webinar. We have our big customer event called the Work Innovation myself, kind of play back the highlights for investors what we shared with us, what we shared with us, what we shared with strategy, what we've been up to on the product road map and development side. And I think it will just reinforce some of the themes we're talking about today and at earnings last week.

Fantastic. Thanks so much. Thank you. Looking forward to it.

Good day, and thank you for standing by. Welcome to the Asana First Quarter Fiscal Year 2027 Earnings Conference Call. [Operator Instructions] 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 results for Asana's First Quarter Fiscal Year 2027. With me on today's call are Dan Rogers, our Chief Executive Officer; and Aziz Megji, 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 FY '27 full 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 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 the closest GAAP equivalents are available in our earnings release, which is posted on our Investor Relations web page 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 high end 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 4-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 8 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 CoreWeave and [ Epson ] expanded with additional seats and AI products this quarter.

Growth in non-tech sectors continued 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 AI 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 a personal productivity uplift from working with AI chatbots. But for many organizations, that has not yet translated into real productivity 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 to run the business. We see 4 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, CIOs and IT leaders are very worried about the agent-palooza. This is agents running amok 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 4 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 pretrain 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. A 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 work-up. Some of those tasks might lend 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 looks like, and the next launch runs that much sharper. This is engineering, operations and marketing and agents all working off the same plan and moving together, humans and agents moving work faster.

Looking at our AI products, it's been roughly 1 year since AI Studio became generally available, and the adoption trends continue to strengthen. Customers are embedding automation 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 seat 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 of one of the largest managed healthcare companies in the U.S. 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 AI Teammates are now completed nearly 9x 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 Claude directly into the Work Graph through Asana's MCP integration.

CoreWeave, a leading AI cloud provider, has expanded its use of Asana over the past 2 years, growing from 15 seats to more than 1,000 across teams, and they're now an AI Teammates customer. CoreWeave uses Asana across data center operations, IT, supply chain, technical program management and marketing.

In the next 2 customer examples, FedEx and COS, we'll demonstrate the operating system for human agent teams and what that looks like in practice. In both cases, Asana is 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 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. Our 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 time lines from weeks to days.

Looking at COS. COS 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, COS 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 life cycle, preserving workflow context as work moves between departments.

The quality check AI Teammates 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, freeing teams to focus on strategic and creative execution. As COS described it, Asana hasn't really improved our processes. It has redefined how we work. We have 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 COS show the huge increase in velocity and output that's possible when real workflows are optimized for 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 StackAI. StackAI 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, StackAI 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.

StackAI is the logical evolution of AI Studio and accelerates our road map by over a year. Where AI Studio made it easy to create powerful automations around intake, routing and request processing, StackAI 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 StackAI. Together, this allows us to deliver the operating system for human agent teams, delivering on the real productivity promise of AI.

Now a proof of concept with the StackAI team, our marketing team were able to identify a really complex SEO process. They created bidirectional integrations with 5 marketing data stores, summarized insights, then handed over to an AI Teammate that has 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 Rosinol and Bernard Aceituno, 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 StackAI team to Asana. And I'm even more excited to introduce StackAI 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 an agentic 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 multiproduct AI platform with the launch of AI Studios, AI Teammates and now adding StackAI into our portfolio.

On June 4, 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 our innovations across our AI products and our broader AI platform road map. We believe WIS will mark an important moment in our customers in the market understand Asana's role as the OS for human agent teams.

Following WIS on June 8, 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 a self-driving enterprise. We'll showcase our latest product innovations and road map and demonstrate how customers are already realizing value from AI Studio, AI Teammates and StackAI. 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 GAAP 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 4-quarter average and therefore, a lagging indicator of more recent trends. As Dan mentioned earlier, we saw rolling 4-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 multiproduct adoption across the customer base, growing contribution from AI products and continued seat 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 2-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 6-plus months. This includes organizational trial starts trending up sequentially for the first time in over 5 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 and 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 event and their associated marketing campaigns. Net income was $24.4 million or $0.10 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 Teammates 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 readers finalizing each assessment. The result is 10x to 15x 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 organization structures, creating a strong foundation for sustained efficiency, operating leverage and multiyear 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 cRPO relative to last quarter.

Our total ending Q1 deferred revenue was $323.1 million, up 11% year-over-year. Building on our operating margin 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 StackAI. 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 road map. 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 StackAI's balance sheet.

The 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 towards GAAP profitability, attracting and retaining top talent and executing against what we believe is the strongest product road map in the company's history, we remain focused on improving 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 SBC and dilution over time.

Before I walk through the guidance in detail, I want to reiterate that the core assumptions underlying the FY '27 outlook we shared last quarter remain largely unchanged. First, PLG remains a near-term headwind, and our guidance still assumes approximately a 2-point drag on ARR growth from this motion. 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 2 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 FY '27.

We are encouraged by the momentum we are seeing across our AI products, with Q1 AI product bookings contribution to net new ARR coming in ahead of our expectations and StackAI 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 StackAI.

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 FY '27 to be above our full year operating margin guidance. StackAI is expected to represent approximately a 1 percentage point drag on operating margins in Q2 and the second half of FY '27. This is fully reflected in our guidance.

Now moving to guidance. For Q2 of 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 StackAI 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 of 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 StackAI of approximately 50 basis points to growth. 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 $0.37 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 in mission-critical workflows. The addition of StackAI 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.

[Operator Instructions] The first question of the day will be coming from the line of Robert Oliver of Baird.

Aziz, look forward to working with you. Dan, I had two questions, and I'll start with the first for you. So StackAI, you called out, it accelerates your road map, 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.

Yes. Hi, Rob. So it all starts with our customers. 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 road map, and we kind of had a very nice plan about how we were going to add all these third-party integrations, these orchestrations across multisystems, or we can deliver that today to our customers.

So when we found StackAI 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 looking our lips at, honestly. So we're super excited.

In terms of acceleration, yes, we say this accelerates it by a year. They 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 into kind of restart the business on the growth side in particular, with some of the non-tech customers and more kind of 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 StackAI more integrated, does this motion require FTEs as well?

Yes. So again, I'll take that question, Rob. So if you think about the groundwork that we've been laying over the last 9 months, the first piece has really been about multiproduct. And multiproduct 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 NRR 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 9 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.

[Operator Instructions] And our next question will be coming from the line of Matt Bullock of Bank of America.

I wanted to ask about the technology vertical and some of the AI-native [ intermodal ] providers you mentioned in the prepared remarks. So understanding that the guidance doesn't contemplate a 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.

Yes. 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 3 things. One, they are 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 the 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, 1 of 9 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 more of that to come. I'll hand over to Aziz now.

Yes. So on the tech vertical, we're really encouraged about now kind of 2 quarters in a row last quarter, kind of stabilized to flat growth and then a resumption of growth after 2 years to a positive growth. We haven't factored that into our guidance. Our guidance still assumes trends from 2 quarters ago. We're encouraged, but we need some additional positive inflection to get more constructive and included in the guidance. That's just 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 out Anthropic, CoreWeave. A large portion of those early adopters of Teammates have been in the tech vertical. So expansion with our add-ons has been a key driver of that resumption to growth.

And then secondly, we've seen seat expansion. So as these tech companies have gotten deeper adopted with AI Studio, it's also led to seat expansion. So we're super encouraged about that. And retention is also trending in the positive direction as well. So it's expansion and retention, but a lot of that's driven by adding on AI Studio and Teammates.

Really helpful. And then if I could just sneak in a quick follow-up. Can you unpack some of the drivers of the $100,000-plus customer count this quarter? It looked a little bit softer than I think some were expecting. Was that a function of more -- less customers graduating above that line, some selling down? I'm just trying to better understand that metric.

Yes. Maybe I'll just -- I'll start with a few general comments, and then Aziz will pick up as well. If you think about our multiproduct 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 grass shoots of many of those products, right? So AI Teammates is really just 60 days of GA. AI Studio, about 9 months. And of course, with StackAI, we're on day 1. 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 and prosecuting with our sales teams and particularly our enterprise sales teams, these are all going to be great drivers for $100,000-plus [ lens ], and then we'll talk a little bit more about the expansion. But yes, generally, the theme is grass shoots and a bit early on some of the transformation that we've been driving there.

Yes. And just to add on to that, the cohort grew 12% year-over-year. And as you pointed out, 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 applied to non-tech as well is showing up in actually the growth of our $100,000 customers within the cohort versus adding new ones.

And then secondly, 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. 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, we don't break up the $100,000 customers, but those almost doubled quarter-over-quarter. So we're seeing strong growth in $100,000-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.

[Operator Instructions] Our next question will be coming from the line of Patrick Walravens of Citizens.

Great. 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 the 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 parse 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, 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 really this idea of the Work Graph. So what is the 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 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 an 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 the 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 and 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 agentified, 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. I kind of said when I started maybe 6 or 9 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 us rolling into our Work Innovation Summit on June 4, where we'll share more of our ambition and more of our product road map 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.

And our next question will be coming from the line of Jackson Ader of KeyBanc.

The first one was just a clarifying question on the $100,000 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. Well. And then what is like the typical [ team ] spend for one of those customers on, I'll call it, like core Asana look like relative to?

It ranges, but it can -- 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 the StackAI 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 -- Dan, you mentioned this a little bit, but who is the buyer for StackAI? 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?

Yes. No, great question. So I would say, increasingly, there are people in an organization responsible for AI transformation. Increasingly, there are 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 agentified really matches well with, I'd say, that buying center. That buying center now can appear in operations teams. It could 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 kind of 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.

[Operator Instructions] And our next question will be coming from the line of Steve Enders of Citi.

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 adds 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 I 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 prebuilt AI Teammates that anyone can bring right alongside them in their day-to-day work. Aziz?

Yes. 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 $100,000 cohort, a lot of them have originated as smaller cohorts, smaller buys 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 a 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 StackAI 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 of 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, we're seeing good engagement there. And 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 a follow-up. Just on the tech vertical, I think there's been quite a few layoffs so far this year across the space. I guess, 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?

Yes. So a couple of things there. As we said in the published remarks on our NRR assumptions, like we've only factored in modest improvement to NRR into the guidance. So that would imply -- we've been seeing pressure in the tech vertical for multiple years. A lot of that has been layoff activity in those tech customers or lack of headcount growth. So that would imply that that's kind of implicitly factored in.

But being a multiproduct company, we have mitigants to that now with Studio and Teammates, and we've seen success. No customers downgrading seats because they let go 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, like we've been deliberate about how we factored NRR 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.

[Operator Instructions] And our next question is coming from the line of Josh Baer of Morgan Stanley.

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 rerating. I'm assuming that you believe that those -- 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 yes, 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 multiproduct platform. And you saw us launch AI Studio, AI Teammates, StackAI. And now in a couple of weeks, you'll see even more ambition at our Work Innovation Summit. So multiproduct 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 hope to achieve. And you'll see a deliberateness around that 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 maybe our mindset was something was going to be delivered in 3 weeks or now we're trying to deliver the same thing in 1 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.

[Operator Instructions] And our next question will be coming from the line of Billy Fitzsimmons of Piper Sandler.

Can we double-click on kind of the positive trends in NRR? And maybe it makes sense to kind of break it down into its components because it seems like it's both a combo of multiproduct adoption and importantly, seat growth. And on multiproduct adoption trends, a lot of the AI products you talked about are still new. It seems like the strongest growth is coming from customers that are kind of AI-first already like a CoreWeave or Anthropic, but I kind of imagine there's a material portion of the base who is kind of much earlier in 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 seat expansions and kind of the growth you're seeing, is this just kind of your largest customers continuing 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?

Yes. So we're seeing NRR improvement across both tech and non-tech. We called out FedEx and COS this quarter, who expanded with seats and Teammates. So we're seeing it in both tech and non-tech.

And on the NRR, 4 quarters of improvement in the 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 4 straight quarters. So we're very encouraged by that.

And the larger piece of that expansion of the improvement in NRR 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 seat expansion. As I said before, we're seeing the greatest seat expansion with those that have adopted our AI products. So it'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 that's the NRR. So that's been fairly positive.

And the seat growth has been both on expanding seats and also new logos. We called out a couple of new logos in the prepared remarks, 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 now -- as Dan has said, we're multiproduct. That means that we can land larger ACVs on the outset and then expand from there.

So NRR is taking a nice trend. Next quarter, we have the large customer downgrade kind of laps off. So that's another catalyst for improvement, along with continue 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 Baird conference next week. And of course, please join us for the investor webinar on June 8. Looking forward to seeing all of you. As always, if you have any questions, please reach out to me at [email protected]. Thank you very much.

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

All right. For important disclosures, please see the Morgan Stanley research disclosure website at www.morganstanley.com/researchdisclosures. And if you have any questions, please reach out to your Morgan Stanley sales representative.

My name is Josh Baer, Software Analyst here at Morgan Stanley. We are thrilled to have part of the Asana leadership team with us today, Dan Rogers, CEO; and Aziz Megji, Head of FP&A and also incoming CFO.

Thank you so much for being here. Really appreciate it.

Thanks for having us.

As an introduction, Dan, for those investors who might benefit from a refresher on Asana but also for those who might not know you yet in this role, can you rewind a little bit thinking about 2025? What attracted you to Asana? And you've had an extensive career and senior leadership roles at a bunch of different software companies, what puts you in a great position to lead Asana forward?

Yes. Great. Thank you. Let's turn first to Asana. So looking back before I joined, Asana has 170,000 customers around the world, which means we are a known global company. And I had used the Asana product in 2 of my prior companies. So it was a brand that was much beloved and much known to me. 85% of the Fortune 500 use Asana today. So in some sense, we're fairly ubiquitous. And when I talk to those customers, as I say, they were kind of hooked on Asana. We were delivering real value in the coordination of human-to-human interaction, that coordination of projects.

Our humble beginning 17 years ago as the platform for collaborative work management and really the pioneer of the collaborative work management market. Dustin's vision, bringing in a social graph into the work environment through the work graph. So all those things attracted to me. But what really piqued my interest was our potential around human to AI interaction and human agent interaction. And we'll talk a little bit about that, I'm sure today.

Vis-a-vis myself, my own background. Sometimes I say I come from England but sometimes I say I was born in the cloud. It was raining when I started and I ended up going to many of the titans of cloud computing, including AWS, ServiceNow and Salesforce. And lastly, spent time at a cybersecurity company, Rubrik, helping them on their journey to becoming a public company as the President there and then at LaunchDarkly, where I managed to serve a different audience, which was really developers, developers that were fast moving and interacting with many of these new AI code generation tooling. So very much around application speed and going from idea to kind of code. And that's really seeped into me as a fast-moving innovation kind of mindset that I bring to the party.

Great overview and background. I want to start with strategy, which is to be the pioneer of the Agentic enterprise. And wondering what does this wave of work transformation really entail? What exactly is the strategy to address this opportunity?

Yes. So we're now entering into a new era of work. Work is going to change fundamentally. And in this new era, humans and agents are going to be collaborating together. If you close your eyes and kind of wake up in 1 year's time, it is clear that work is going to be a tapestry of humans and agents working alongside each other and agents and agents working alongside each other.

So what's our role in that? So let's kind of wind back. If you take any company, any organization, as soon as they have 10 people, 100 people, 1,000 people, they need to coordinate with each other. They need to have clarity on who's doing what, when and how. This was the genesis of Asana. Does the problem go away when you have agents, when you have thousands of agents that are running about in the organization? No, it actually grows exponentially. So humans and agents still need coordination. They need a more than ever, a structured system that is the system of record for work. They need a knowledge graph for work, what your priorities are, what your time lines are, how this pertains to the projects, what the task inventory is, the tasks to be done. And so that ledger is Asana. We are the foundational layer for the Agentic enterprise. We are the instruction set for these agents and these humans to work off of. Just as we were with human and human collaboration, we now are with human agent collaboration and agent-to-agent collaboration.

If you break that down one step further, most of us have had the experience of interacting with a kind of chat agent. And you'll see now as you kind of type in your prompts that, that experience breaks down into tasks of how I'm going to solve this from an individual basis. Maybe there's 10 tasks that have been articulated in the response that it's going to go through sequentially. Well, you're going to need a ledger of all of those tasks for all of the agents that are interacting. And wouldn't it be great if that ledger is persistent and it happens across all of the agents that they can all operate against the same set of tasks. And again, that's really where Asana comes to the fore.

Excellent. So with that backdrop in mind, can we dig in a little bit on Asana's AI products, AI Studio, AI Teammates. I mean what are these products? And what -- how do they achieve this strategy goal? What value do they bring to customers?

Let's start with the AI Teammates. AI Teammates is in beta right now. We have over 200 customers in our beta program and will become generally available later in March. That really is the first manifestation, I would say, of fully using the Work Graph for an agent. These are first-party agents. We'll have agents for marketing teams, agents for operations teams and agents for IT teams that have pre-described some of the jobs to be done by those departments. Those agents will work off of a Work Graph. So they are instantly productive. They don't have to infer the tasks and the steps that need to be taken because those things have happened in the past in our Work Graph. They know exactly which people they need to interact with. They know exactly what goals that they pertain to. They know exactly how long those jobs take, who needs to be involved, who needs to approve things, who are the managers.

And so that governance model already exists. So our Teammates literally on day 1, you can put them in the environment, day 1, hour 1, and they're instantly productive. Part of the reason why many companies haven't yet found the productivity gains from AI is they have all of these loose tools that are not operating against the common instruction set. They don't have a system of record to work from. Our AI Teammates are an antidote to that. Our AI Teammates are instantly productive.

If you look at AI Studio, which is a product that we launched just last year, a fast-growing AI product from Asana, we reached over $6 million in ARR, which we announced in our Q4 earnings in well under a year. How did we do so? We embedded work -- intelligence into workflows. Many of our customers use us today in simple or complex workflows. And with AI Studio, you could put AI nodes into those workflows, AI nodes that do quality checks, AI nodes that make sure things are on spec, AI nodes that complete in complete forms, AI nodes that translate, AI nodes that route the work for the correct people.

So if you take, for example, one of the large fashion retailers in Europe, who's a customer of AI Studio, they use AI Studio every day, and it goes from SKU to factory. And so all of the production steps are being coordinated with AI intelligence along the way. And again, AI Studio follows those same guardrails that preexist within the Work Graph. So you don't need to set up some new permissions. You don't need to set up some new data privacy rules. They're automatically going to follow those things that have already been established for your enterprise.

Very helpful. Aziz, I want to bring you into the conversation. Maybe we could talk about the business model, the pricing model for these products. How is your AI monetized? Do these agents and AI Teammates need a seat? Or are we talking about a hybrid and consumption model?

Yes. So thanks, Josh. So we're currently a hybrid model. So both Studio and Teammates, the monetization model is kind of prepackaged credits. So we size that credit package based on the size of the organization, the number of Teammates are deploying, the number of use cases and workflows that they're looking to automate and turbocharge to come up with that right credit allotment. And as they work through those credits, if they go over, we have overages and top-up credit package. So it's -- we found through the betas and the early customer feedback. Customers aren't ready for the full consumption model yet.

So we introduced this hybrid model, and it seems to be working well. We've got 8 customers this past quarter now spending $100,000 or more with AI Studio, and seeing the full benefit and really enjoying how it's priced. And it will evolve and it's dynamic. But today, that hybrid model is working well.

You've laid out the strategy and some products and the vision. A lot of the investor focus in the market this year has been around the potential risks around AI and the potential disruption. And I guess I want to ask you directly, how do you respond to those investors who worry that AI could just fundamentally disrupt the collaborative work management category?

I'd probably put a reflecting mirror back up and kind of say, au contraire, think of this as even more important now than ever to have this coordination layer. So the fact that you have lots of agents that are going to be running about, the fact that you're going to have an increased volume of tasks that are being generated by AI actually increases the need for coordination. It actually increases the need for a Work Graph. The Work Graph is the ledger of the company's strategy. It is the ledger of who's doing what, when and how. That ledger needs to be accessed to be useful.

Individual sessions with interaction with a foundational model are not going to be sufficient. The productivity unlock, the promise of the Agentic enterprise is when agents and humans are working together against a common system of record for work. And in doing so, then we become the system of action, we can move that record on towards collaborative execution. So I'd say we enjoy the advances of the foundational models because it's going to consume our platform more fully. And as I say, we were purpose-built for exactly this moment.

And this is kind of what you mean when you say AI is an amplifier for Asana?

Yes. I mean, right now, it's clear that, that gap between the promise of productivity of AI and actual enterprises enjoying that productivity from AI is large. And we think that gap is a large coordination gap. But actually, those tools need to start to work with each other and they need to start bringing humans in, in a multiplayer mode.

One thing that I learned from earnings on Monday was that both of the leading AI labs are customers of Asana and that they've been expanding their contracts with you. And maybe that shouldn't have been a surprise just given Dustin's early relationship with these companies. But this fact alone, I think, helps to refute that AI bear case narrative out there. Is there anything else that you can share around how those customers are using Asana as far as the use case or their deployments?

Yes. Look at one of those foundation model providers. They have thousands of employees across engineering and product and marketing and operations and IT as well as actually the compliance and risk teams. It turns out that the coordination challenge of work is large. And so they look to us for, I would say, 4 things. The first is the context of work. That is tied to our work graph, that ability to have a common understanding of the tasks and the projects that need to happen. They look to us for a persistent memory that's not just session dependent from a single interaction with a chat but actually persists across the life of a project, the life of a strategy, the life of a goal. They look to us for this multiplayer mode, which is helping the rest of the team stay coordinated and have that visibility into how things are going, moving tasks along seamlessly between teams.

And they look to us for our built-in enterprise credibility and governance and controls, which really mean that they know that their data is protected when they work within the Asana platform. And it already has pre-established who gets access to what, who gets to approve what? So that's all just readily enjoyable.

Yes. And that same AI lab is not only using CWM but they're using AI Studio to actually coordinate their risk and compliance workflows, which are so core to their mission, and that customer expanded again in Q4. So we really enjoy them as a customer, and they see a lot of value from Asana.

Really interesting. Maybe zooming out, thinking about the broader competitive landscape, you're not the only collaborative work management platform. You also have vendors like Microsoft in there that are competing for being the provider of the rails for enterprise agents. And so how do you think about this new competitive landscape and ultimately, why you have the right to win?

I'd probably use a very engineering answer, which is it's all about the architecture. And for us, the architecture is the Work Graph that you could think of as a neural network of the relationships between tasks, which is the fundamental unit of work, people, projects, goals, projects that overlap all of that. And so that Work Graph is very powerful. And the way that we architect it, it is not a simple relationship but it does mean that the agents that operate within our system are instantly productive because they can instantly access that work graph.

So the differentiation is context in the flow of work, the persistent memory across multiple projects, multiple teams, how this thing has been solved in the past. Often that persistent memory might be years rather than the [indiscernible] nature of a session, which is seconds. Then the multiplayer mode, which is that we have already solved the fundamental challenge of making sure that as people update things, everybody is brought along, that humans are collaborating together on our platform and that, that operates together seamlessly. So as agents also update their progress against their work, that seamlessly fits into that same architecture.

And then finally, we were very early on in Asana as a company, we were -- we have some of the largest companies on the planet as our customers, and we still have many of the largest companies on the planet as our customers who have hundreds of thousands of users, which means we have encountered all of the needs and requirements around where the data is, who gets to access it, what permissions happen, who gets to approve things, who gets to reject things, who gets to see things. Those have already been solved problems for us.

So yes, those are kind of readily available for all of our customers. All 4 of those are major sources of differentiation, both against the, I'd say, some of the point solutions from some of the foundational providers themselves as well as the CDM traditional competitors.

Very clear. Maybe shifting gears, Aziz mentioned that on Monday, you reported earnings. Could you walk through some of the key takeaways from Q4 results and FY '27 guidance?

Yes. We had a solid quarter, and it's a meaningful progress in FY '26, we became a multiproduct company. A key highlight was AI studio is now $6 million of ARR, and that's just over 3/4 of full GA, and we're scaling with those customers. We now have 8 customers that are 100,000 plus. That's across geos, across verticals. The results itself, we grew 9.2%, which is above the midpoint of our guide. Our margins we generated were 9%. So it's about 150 basis points above guide. So 5 straight quarters of sequential margin improvement. So we're super proud about that.

If you look at that on a year-over-year basis, 7% for the full year represents like 1,300 basis points of improvement year-over-year, and that's translating into free cash flow. So we had a 13% free cash flow margin for the quarter, which is 700 basis points improvement year-over-year. So strong metrics and the KPIs that we monitor were also improving, not only stabilizing but inflecting. So third straight quarter of NRR improvement. That's on the back of really strong renewals for our largest customers. Our top 10 renewals in Q4 renewed at NRR greater than 100%. Most of those were tech. That's really encouraging.

And that strong renewal activity is translating into our tech cohorts. So we've talked about our tech cohort being a headwind. They're not expanding as fast with in terms of their own headcount pace of hiring. For the first time in 7 quarters, our tech cohort did not decline. It was basically flat growth. And that's on the back of not only strength in renewals but the expansion that AI Studio is driving and strong new business activity.

And then lastly, the balance sheet metrics that we look so closely as leading indicators, mainly for our upmarket business, cRPO and deferred revenue all both accelerated by 200 basis points. Our cRPO grew 17% in the quarter. So those are good leading indicators for the upmarket business. So we feel really good about the historical results. And on the guide, we guided to an 8% midpoint on revenue growth and at least 9.5% on margins, and we can unpack the assumptions in that guide. I'm sure you got that.

Yes, that would be great. You're pointing to some really impressive areas of stabilization, inflection, even acceleration in some of those leading indicators, thinking about cRPO. And the guide -- the revenue growth guidance is for a slight deceleration. So could you unpack some of that? Are there other headwinds that's driving that? Maybe it's -- a lot of it is conservatism. We'll see where we end up, but any thoughts there?

Yes. So on the revenue growth guidance, we kind of count there's kind of 3 different phenomenons going on in the business. So the first is our sales-led business, which is mainly our mid-market and upmarket business, continues to perform well. So we've seen strong productivity increases. We talked about the NRR we're seeing in our large accounts. So there's a lot more we can do that to compound the productivity, but that's growing -- that those segments are growing above that overall rate.

Now where we are seeing headwinds are in the PLG business. So we called out about 2% impact or headwind to our ARR growth is coming from PLG. So that top of funnel pressure that we had called out several quarters ago, while it's improving quarter-over-quarter, it's not improving at the rate that we previously expected in Q3. And so that is a headwind to the growth. And in absence of that headwind, we would be accelerating on the near term.

And then the third thing I want to call out that's factored in the guide is we're seeing a lot of encouraging signs of stabilization and inflection in key leading indicators. NRR, I just talked about. We talked about the tech business, those 2 are not factored in the guide as continued improvement. We want to continue to watch and monitor the progress there before we kind of factor that in the guide. So we're taking a little bit of prudence and conservatism of how we factor in continued NRR improvement. It's been factored in modestly and how we factor in the tech stabilization. It's still factored in as a slight decline versus stabilization and inflection.

And then lastly, on AI Teammates, we're super excited, as Dan walked through on the opportunity of bringing that to our self-serve and our PLG base. It will be fully GA by the end of Q2 across both motions. It's going to take some time to ramp. So you'll see a very different trend in terms of how we exit Q4 because of that ramp versus the first half in Q3. So those are some of the dynamics in play in the guide in terms of guidance philosophy. I share internally philosophy. We've been partners and setting the guide since we both arrived here, close to the pin, reflect what we're seeing, be prudent, the dynamic environment. And so that's how we approached it.

Excellent. Very helpful. Dan, I want to pull you into the conversation on product-led growth, just talking about the headwinds. But at the same time, you're looking to reimagine what product-led growth can be. So what does that mean? What investments are you making to turn this into a growth driver?

Maybe I'll start with philosophy. As a product category, collaborative work management and us as a foundational layer for the Agentic enterprise, that is a product category that will be served digitally that we do think many customers will want to buy digitally, discover digitally and fully engage and consume our platform digitally. So we are -- by all accounts not walking away from PLG, we like it. It really is fundamental for the discovery and consumption of the platform. That is true. And it is also true that we have new dynamics in how that discovery happens, that there is an increasing prevalence of AI search as an example, as a way to discover us, that perhaps many of the experiences will remain within the prompt window of some of those foundational providers is how they want to consume Asana. You see that with our new Claude app as an example, that Claude can fully consume the Work Graph for any Asana customers to actually help them stay within that kind of context.

So lots of dynamics have changed in that business. In Celoxis, we are very exciting to kind of have that set of things that we need to kind of tweak and tune and optimize in a broad philosophy that we actually think is very good for us. But because of the tuning as kind of Aziz intimated there, it gives us uncertainty on PLG. And we see lots of early signs on how that tuning is working, mid-funnel and the experiential pieces. And it actually pushes us a lot on what our UX experience needs to look like. So I'd say fundamentally committed to digital buying and discovery. It keeps us on our toes, some of the changes that are happening in the environment on what the product experience needs to look like and the discovery experience needs to look like. And you'll see us being, I'd say, very lively in our -- both our ambition and how we approach it.

Excellent. I want to ask one on the net retention rates in those large, I think the top 10 enterprise renewals above 100%. I guess a couple of questions there. One, what does the renewal pipeline look like? And in the past, because of your visibility into the underlying engagement of the platform, sometimes you can have -- it doesn't have to be a total surprise if you see downsizing from headcount reduction if you're already seeing that show in engagement. So I guess question is also what signs are you seeing in some of your big customers around headcount growth and engagement?

Yes. So the beauty of growing cRPO and RPO is that we have more of our ARR base under a multiyear contract and therefore, less pressure in terms of the renewal activity that comes up each year. We also, in terms of the renewal base in FY '27, in FY '26 and FY '25, we had some very large customer renewals. So we don't have that same dynamic in FY '27. We have a more uniform size of renewals and no real outliers from a size perspective. So that also derisks.

We've seen some pressure over the last couple of years in the tech vertical NRR. Tech vertical is now 25% of our ARR base. So the concentration of tech has come down a lot. And then we're now a multiproduct company. So having AI Studio and in a month or so time, having AI teammates to introduce in those renewal conversations to drive expansion, mitigate downgrade if the customer is inclined to reduce seats, is something a lever that we haven't had in this fulsome way ever as a company. And AI Studio and Teammates are not dependent on seats. You can derive the value in absence of seats and absence of headcount. So that's a real powerful lever, and we're seeing that play out in renewal conversations.

And then you're right, we have greater visibility into our renewals. We've hired, about 2 years ago, an amazing Chief Customer Officer. He's built a team, increased our CSM coverage. So we're getting visibility 12 months in advance of these renewals into the health of the account. Do we think they're at risk of downgrading? We're starting to put action plans about a year in advance about what we're going to do to increase utilization, drive better adoption, introduce new workflows, how we can leverage our Teammates. So it gives us a lot more visibility into the health of the customer. And overall, we're seeing actually adoption and utilization increase year-over-year, which that's always been a leading indicator for NRR and for our GRR. So that also gives us comfort as well going into FY '27.

Maybe shifting over to margins. I'm wondering where the sources of leverage are from here. You -- in your opening remarks on the quarter, we've noted such a strong margin expansion recently. And maybe one way to ask the question is, I'm sure that Asana is a heavy user of Asana and all the AI technology and innovation coming out. And so do you have any examples of departments or categories of OpEx where Asana is really driving a lot of efficiency?

Yes, we're the #1 user of AI Studio and AI Teammates, and we use it across departmentally. I mean, Dan is like biggest push is AI internally. And our security department uses it extremely heavily to drive workflows there. We use it in finance, in R&D to manage the dev cycle and spread management. We're using it in our IT department with ticket deflection and kind of help desk like applications. So it's definitely driven a level of productivity in our workforce that has allowed us to move faster and drive greater innovation and do more with our current resources. So we have really more to do on the adoption side, but it's been a lever of us being more efficient and more productive for sure.

And to your question, we're just scratching the surface. So we definitely haven't reached the endpoint of that productivity gain. The more we adopt these tools more fully, the more we embed them not just as tools but into our processes more deeply, then yes, we will continue to have productivity internal gains that will translate into continued operating margin improvement.

Talked about sales-led growth performing well. Are there still areas that you're focusing on improving, investing in, specifically with regard to selling all these new AI tools?

Yes. I'll say, of course, it's early days but our innovation pipeline in terms of delivering and manifesting us as the foundational layer for the agentic enterprise is rich and ambitious and too early to really put into any kind of guidance. But in the second half of the year, you'll see even more manifestations of that. Yes, AI Teammates will be on a massive acceleration curve as that product matures, so will AI Studio. The next versions of those, you'll kind of see a lot of innovation and a bunch of new products that really we're very excited about in the second half that is too early to even flag what they are, what they're going to do but really about realizing our potential in the agentic Enterprise.

And should we expect to see headwinds to gross margins as some of these AI tools are ramping early on?

Not material. I mean if we start to see headwinds to gross margin, it means that gross profit dollars are growing in a way that is not factored in our guidance. And so we're willing to absorb that trade-off because if we're accelerating growth with Studio, Teammates, it means we're getting more deeply embedded in workflows. That's the greatest NRR driver we can have. So based on how we've illustrated in our guide and that target we put out of 15% of our net ARR coming from AI products, we don't expect any gross margin degradation based on that.

Maybe just to round out the conversation on capital allocation. Your free cash flow generation has come a long way that we can have this -- ask the question. And so what does it mean like your current cash profile and where it's going in the future? What does that mean for capital allocation, thinking about M&A and buybacks.

Yes. I mean our capital allocation strategy and framework is dynamic. We just announced increasing our buyback authorization by $160 million to about $200 million, where our shares are trading. And based on our view on positioning and growth in the agentic enterprise, we think that's an attractive form of deploying our capital, buying back our shares and not only neutralizing dilution, but if things hang out at this level, reducing share count and returning capital, we'll always be opportunistic about M&A, more probably on the tuck-in variety to complement and augment our technology and talent.

And then obviously, investing in the business. We talked about on the call, allocating more of our capital or OpEx towards R&D to drive that innovation pipeline and fuel that Agentic enterprise strategy. And so that will continue to be part of the mix. But it will be dynamic and evolving. But yes, it's nice to have free cash flow and growing free cash flow at a really nice rate to allocate and drive even greater value for shareholders.

Excellent. Thank you for the conversation. Thanks, Dan. Thanks, Aziz.

Thank you.

Thank you. Appreciate it, Josh.

Thank you for standing by, and welcome to Asana's Fourth Quarter Fiscal Year 2026 Earnings Conference Call. [Operator Instructions]

I would now like to hand the call over to Eva Leung, 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 Fourth Quarter and Fiscal year 2026. With me on today's call are Dan Rogers, our Chief Executive Officer; and Sonalee Parekh, our Chief Financial Officer.

Today's call will include forward-looking statements including statements regarding the expected release and benefits of our product offerings and our expectations for revenue to be generated by those offerings, our retention and expansion opportunities our expectation for our financial outlook, including our FY '27 full year guidance, strategic plans, our market position and growth opportunities and our capital allocation strategy, including a stock repurchase program, among other items.

Forward-looking statements include 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. A 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 web page at investors.asana.com.

And with that, I would like to turn the call over to Dan.

Thank you, Eva. FY '26 was a year of progress for Asana. We exited the year with solid momentum. We evolved into a multiproduct platform with the launch of AI Studio and we advanced our AI capabilities with the introduction of AI teammates, all of which to help us build the foundation layer of a genic enterprise. Importantly, we stabilized NRR, materially expanded our operating margins and free cash flows, and we set the structural foundations for our long-term profitable growth. So let me share a few highlights for the quarter.

Q4 revenues were $205.6 million, growing 9% year-over-year. We generated non-GAAP operating income of $18.2 million or a 9% non-GAAP operating margin. Operating margin reflects disciplined cost management as well as a thoughtful reallocation of spending towards those higher leverage areas, and we still preserve capacity to invest in our AI platform. Our adjusted free cash flows were also strong at $25.7 million in the quarter or 13% on a margin basis.

Customer health improvements continue to take hold. Our reported NRR remains stable. And for the third consecutive quarter, our in-quarter NR improved. Our top 10 renewals in the quarter delivered net revenue retention above 100%. This reflects a long-term commitment of our largest customers sustained value that the platform continues to deliver for the world's leading companies. Key renewals with expansions this quarter included a leading global advertising and marketing organization, a top-tier European markets infrastructure provider and several large tech customers, including a Fortune 10 tech platform.

Looking at our AI momentum, it continued to be strong across both monetization and engagement. AI Studio continue to scale rapidly. In fact, we exited FY '26 with over $6 million in ARR and grew over 50% quarter-on-quarter in Q4. Our customers are embedding AI studio in their business-critical workflows like campaign launches, product intake and service ticketing where human and AI our collaboration accelerates coordination, reduces cycle time and improve quality across teams.

Our U.S. revenue accelerated in Q4. And our technology vertical returned to flat year-over-year performance after nearly 2 years of quarterly declines. This stabilization was driven by strong renewal performance within our largest tech accounts and improved business execution. We secured one of the largest new enterprise wins with a global leader in data integration and analytics, serving enterprises worldwide, where they consolidated critical workflows on multiple tools right on to Asana.

We also delivered a significant seat expansion and AI studio deployment with a global leader in collaborative design. This customer powers digital product teams at thousands of organizations. It is now deepening its commitment to Asana as its execution foundation. International markets remain a strength for our business. Our international revenues grew 11% year-over-year. We continue to increase our presence in non-tech with those sectors once again growing in the teens. Manufacturing, energy and utilities verticals along with retail and consumer goods and health care continue to do well.

Some notable international vertical wins included a top 10 European multinational hospitality company, a major Japanese energy provider and one of the largest energy retailers in Australia. Government represents an important new opportunity for TAM expansion. These early wins include a major public health agency as well as a marquee deployment with a prominent defense innovation accelerator.

Our channel ecosystem delivered consistent progress in FY '26 with the percentage of partner attached deals improving every single quarter. In Q4, 20% of our studio deals include a partner and we believe we're still early in unlocking the potential of this motion. As enterprises scale AI across business-critical workflows partners play an increasingly important role in implementation change management and expansion. This positions the channel as a meaningful driver of incremental ARR in the long term. Notably, through a partner, we secured a large AI studio deployment with one of Japan's leading global technology and infrastructure providers.

We also drove expansion within South Korea's largest global automotive manufacturers and signed the National Institute of cybersecurity in the Asia Pacific region. These wins demonstrate how our partner ecosystem is unlocking scaled enterprise opportunities across the globe. Our forward-looking indicators in Q4 were strong. Billings and current RPO accelerated this quarter, reflecting enterprise demand strength and their commitment to multiyear, multiproduct deployments.

Last quarter, we outlined 3 waves of work transformation. We believe we're now firmly in the third wave, the genic enterprise. This has the potential to fundamentally redefine how organizations collaborate. It's increasingly clear that the future of work is one where humans and AI agents are working together. And agents won't just drive small incremental productivity gains. They'll actually reshape how work is coordinated, how decisions are made and how execution scales across the organization.

From individual productivity to enterprise-wide orchestration is the foundation of the Agenetic enterprise. Asana is the foundational system of action layer that gives that progression, context accountability and structure. For that orchestration to work in practice, agents have to operate against a shared real-time context, not in isolation. So delivering on this vision requires deep visibility into how individuals work and how teams operate across the organization.

At Asana, that context is captured and structured to our work graph which creates a semantic memory of how work connects across people, teams and outcomes. Agents need this rich individual context. What am I working on? What's blocked? What's at risk? They also need workflow and portfolio context. How does your work connect across the systems, across teams and to outcomes. The more context that's captured within the system of action, the more capable that agents become. That foundation of context is what powers AI teammates and AI Studio, enabling our agents to operate with clarity, accountability and precision.

AI teammates is where this context turns into action. Unlike isolated chat threads, these teammates work directly inside Asana workflows with full visibility and full governance. When you look at what's happening in the market, 3 things clearly differentiate us. First, AI teammates are inherently multiplayer. This is important. It means teams can work together with each other and with those AI agents. Second, our agents have operational context from the work graph.

And thirdly, our AI teammates get the benefits from compounding institutional memory. They learn from team feedback and improve over time. while respecting the permission boundaries that are already established for those teams. This is AI embedded in execution, not laid on top of it. We've now onboarded over 200 customers into the beta program for AI teammates. What's encouraging is not just a sign up number is how quickly those customers are able to drive productivity. Let's look at a few examples.

KW Automotive, a large automotive organization. They deployed AI teammates across marketing, IT and support, and they're driving measurable ROI. For example, their analyst teammate saves up to 3 hours per report by proactively correlating cross-project data, while our support teams are achieving high-quality multilingual resolutions. Their vision is to scale the digital workforce to replace traditional forms with conversational AI and to modernize both the employee and customer experience.

Let's look at another example, Living Space as a home furniture retailer. They're leveraging AI teammates to audit their legacy automation for data accuracy and rewrite complex operating procedures. Their team found that the platform works out of the box, quickly able to replace detailed prompt engineering with natural conversational training. Ease of setup allows them to resolve unreliable workflows and standardize operating procedures with minimal configuration.

When AI is embedded across workflows in marketing, sales, operations and it becomes part of how the company runs. This expands our platform footprint. It increases our stickiness, gives us new buying centers to talk to and compounds our value over time. We expect IT teammates will become generally available to sales led customers by the end of Q1 and our self-serve customers in the second half of the year.

Now let's look at AI Studio. AI Studio brings intelligence into the workflow architecture itself. AI Studio places LLM reasoning directly inside workflow nodes, so humans and systems collaborate with each step of the process. Customers are not just automating tasks, they're designing intelligent workflows in natural language that spans across their portfolios, systems, functions and business units.

With our studio, customers can encode operational logic into workflows, connect structured and unstructured context, automate cross-functional processes and reduce manual coordination at scale. This shifts a sane from a coordination system to a programmable operating layer.

Now as I noted earlier, AI Studio delivered strong sequential growth in Q4. That acceleration was driven by deeper expansion within our existing customers and a larger initial enterprise commitment for our new deployments. We now have 8 customers, for example, across North America, EMEA and APJ spending over $100,000 annually on AI studio alone. This is in addition to the Core subscriptions.

Let me share a couple of use cases on Q4 that really bring us to life. A premier U.K.-based fashion and home retailer has already realized a meaningful impact from AI Studio, using it to identify production risks in real time. This quarter, they expanded their investment to power a new skew to factory workflow, streamlining production, prioritizing accelerating approvals across global teams.

E.ON Next, a sustainable European energy provider is using our studio to automate intake and triage processes that historically slowed complex energy projects. By deploying customer our agents, the team now clarifies project briefs and surfaces missing information immediately before work begins. And that increases request capacity by nearly 500% while improving cross-functional visibility. Taken together, AI Studio and AI teammates are becoming foundational to our platform strategy. We're seeing meaningful ARR growth, enterprise expansion deeper workflow penetration and measurable productivity gains and improved business outcomes for our customers.

Let's look at our differentiation. Asana is uniquely architected for the genetic enterprise. We provide the rails upon which enterprise agents run. As foundational models become more powerful, the bottleneck is no longer the intelligence of those engines. It's a lack of persistent memory and structured execution, a model can think, but it can't act without that context, accountability and a system of record.

There are 4 areas of our differentiation. The first is our work graph. This is the memory layer. It's a context fabric of the enterprise. While traditional infrastructure provides the plumbing for data, Asana provides a vectorized, structured and semantic map of an organization's intent. Without this infrastructure, agents have no home. They have no memory, no sense of priority, no sense of understanding of who's doing what and why.

The second area of differentiation is that we have built our system of action around a fundamental unit that we call the task. And the task is the unit of work that agents can consume execute. By capturing the institutional memory of how organizations operate the ownership, the dependencies and the goals, we provide the necessary structure that transforms raw model intelligence in their business results.

Thirdly, as we discussed with AI teammates, our environment is inherently multiplayer. So the AI teammates operate within the context of existing projects alongside human team members. They collaborate natively within the system of record. And fourth and finally, our differentiation is our enterprise grade by design, which means our agents operate with auditability and the governance required for them to operate at scale. So the combination of persistent memory, task-based accountability multiplay collaboration and governance is what enables our agents to move from experimentation to trusted enterprise deployment.

We are the orchestration layer for agents. This is why the world's most sophisticated enterprises and leading AI innovators are deepening their investment in Asana. In FY '26, 2 of the world's 5 most valuable public companies expanded with us. One of the world's leading AI labs continues their seat expansion again this quarter. They now deployed Asana across thousands of employees themselves to coordinate their mission-critical workflows, spanning compliance, finance, product and engineering. In addition, they leverage AI Studio to automate elements of their risk register and compliance operations, embedding AI directly into how mission-critical work is governed and executed.

For that company that builds foundational AI models, Asana is how they get their work coordinated and governed at scale. Together, these customers validate our position as the foundational system of action layer for the modern enterprise.

Looking at our FY '27 priorities. Our leadership ambitions in Agenetic enterprise directly inform our FY '27 operating priorities. While AI momentum was strong in FY '26, accelerating and compounding that progress is critical to accelerating revenue growth in the long term and our continued margin expansion. Converting early adoption into broader enterprise expansion and higher monetization required disciplined execution across 4 priorities.

Priority one, scaling Agenetic enterprise platform. This is the focus of our R&D investments. We're expanding our R&D team to augment our AI platform talent pool and accelerate our road map. This investment is directed towards expanding the depth and breadth of workflows we address increasing the operational surface areas where agents and smart workflows can operate and embedding more persona-based use cases across IT, engineering, operations and professional services. This is about moving from strong early adoption to broader enterprise standardization, increasing contact density and embedding ourselves deeper into mission-critical workflows.

Priority two, our focus on product-led growth. And here, we're aiming to redefine how users discover Asana and how quickly they realize value once they enter. As we discussed last quarter, PLG is currently a headwind to our growth because of shifts in AI-driven search that is reshaping the top of the funnel. Certainly, we'll speak more directly to how that dynamic impact us in the near term. In response, we're aligning our entire PLG motion to this new environment.

First, we're evolving our discovery strategy towards end for engine optimization and high authority use case-driven content to capture intent where it starts today. At the same time, we're redesigning the product experience to deliver immediate value out of the box. This includes prompt to project onboarding an AI-powered activation using preconfigured verticalized use cases to reduce friction and accelerate time to value. By sharpening our ICP towards teams with true collaborative intent and improving early engagement, we aim to improve our conversion efficiency strengthen our retention and rebuild PLG as a durable growth driver over time.

Our third priority is go-to-market excellence. We drove meaningful productivity and sales efficiency gains in Q4. Our focus in FY '27 is to compound our progress. We're redesigning our territories towards the highest propensity opportunities to align our coverage. We're equipping our sellers with AI-powered tools to prioritize high-intent leads and service clear next best actions in real time. We're investing in channel tooling and enablement, and we're going to better align our incentives between our field teams and partners to scale enterprise expansion more efficiently.

At the same time, we're going to be strengthening that connection between our PLG and SLG by better surfacing product qualified leads with demonstrated intent and high conversion propensity. Together these initiatives position go-to-market execution as both a growth lever and the sales efficiency level.

Our final priority is around speed and discipline. Realizing our potential as a foundational system of action layer of Agentic enterprise requires greater velocity and disciplined capital allocation. We're accelerating the build-out of our low-cost R&D hubs which we expect to meaningfully expand our development capacity by the end of FY '27, while also improving our cost structure. At the same time, we're prioritizing the highest leverage initiatives reallocating resources towards areas of strongest return and embedding AI throughout our internal operations to drive productivity and efficiency. We believe these actions increase execution velocity also freeing up capital to reinvest in growth and expand our margins.

For us, accelerating growth and expanding margins and not trade off this year going forward, they're mutually reinforcing outcomes of disciplined execution. Taken together, our structural differentiation, our role as a semantic memory and execution layer for enterprise work and the accelerating enterprise adoption of our AI platform underscore that Asana is becoming the foundational system of action layer of Agenetic enterprise.

Before I pass it Sonalee, I want to share a leadership update. Sonalee has decided to pursue another opportunity in a noncompetitive in adjacent space. While we'll certainly miss her, we're all super grateful for the leadership, partnership and financial discipline she's brought to Asana. But more importantly, I'm excited to announce our new CFO, Aziz Megji. Sonalee brought is Aziz Megji into Asana as her first priority hire. And he currently leads our FP&A and Investor Relations functions. Many of you on this call are already familiar with Aziz. He has been and continues to be a driving force in shaping our financial strategy, operating rigor and investor and analyst engagement.

Aziz brings with him more than 20 years of experience leading technology companies across strategy, capital markets and FP&A. I've been intentionally pulling him into broader strategic work, including spearheading key initiatives within our go-to-market strategy. His impact there, combined with his deep institutional knowledge makes them a natural choice to lead our finance organization going forward. This is a well-deserved promotion. I couldn't be more excited. And I expect a seamless transition that allows us to maintain our momentum without missing a beat.

I want to thank Sonalee for her contribution and leadership. And I'll now turn it over to her.

Thanks, Dan. It has been a privilege to serve as CFO of Asana and to partner with you, Dustin and the leadership team. I'm incredibly proud of the financial foundation and operating strength we've built together and I'm confident in the company's strategy and trajectory as we scale into the identic enterprise opportunity.

I'm also deeply confident in Aziz's ability to step seamlessly into this role. He has been my partner in driving our financial strategy and his impact has extended well beyond the finance function. He brings deep financial expertise, strong operational judgment and a clear understanding of how we drive durable growth and profitability. I'm proud of the team we've built, and I know the company is in excellent hands.

Now turning to our results for the quarter. Q4 revenues came in at $205.6 million, up 9% year-over-year. We have 25,928 core customers, our 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 Q4. We have 817 customers spending $100,000 or more on an annualized basis, and this customer cohort grew at 13% year-over-year. As a reminder, we define these customer cohorts based on annualized GAAP 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%. As a reminder, our NRR is a trailing 4-quarter average and therefore, a lagging indicator of more recent trends. Our in-quarter NRRs improved again this quarter and marked our third consecutive quarter of in-quarter improvement. The improvement was mostly due to improvements in gross retention and expansion, thanks to our multiproduct strategy and seat expansion.

Improving NRR remains a key focus area and we are confident in our strategy for continued improvement over the intermediate and long term. The initiatives we have in place on the retention side, combined with the expansion opportunity presented by our AI platform position us well for ongoing progress.

In the enterprise and corporate segments, execution strengthened this quarter. Sales productivity and attainment both increased and our top 10 renewals were above 100% in RR. In our SMB business, we continue to see the impact of evolving top of funnel dynamics, specifically, LLM driven changes in search and paid media.

We are seeing modest quarter-over-quarter traffic recovery and improvements in web conversion and retention. Our efforts to date have helped but are not yet sufficient to offset the top of funnel dynamics. As a result, we expect these dynamics to remain a headwind throughout fiscal year '27.

Now moving to profitability where I will be discussing our non-GAAP results. Our gross margin was 88%. Our gross margin was modestly impacted by launch-related timing of expenditures for new products including Asana gov and AI teammates. We expect to maintain these levels of gross margin in fiscal year '27 while expanding operating margin as we continue to scale. We continue to make meaningful improvements in our operating expenses as a percentage of revenue over the course of the year.

R&D expenses were $47.7 million or 23% of revenue representing a 6 percentage point improvement from 29% of revenue in the year ago quarter. Sales and marketing expenses were $88.1 million or 43% of revenue, representing a 2 percentage point improvement from 45% of revenue in the year ago quarter. G&A expenses were $27.1 million or 13% of revenue, representing a 4 percentage point improvement from 17% of revenue in the year ago quarter. As a result of driving productivity and efficiency gains, we delivered a 9% operating margin or $18.2 million of operating income in the quarter. which is a 10 percentage point improvement year-over-year.

Net income was $19.9 million or $0.08 per share on a diluted basis. Our profitability improvement continues to be driven by operating leverage, reallocating spend to the highest ROI go-to-market motions, optimizing infrastructure and cloud costs, and exercising discipline across discretionary spend. We are aligning our talent footprint with industry benchmarks and shifting select roles to more cost-effective regions. This creates a structural foundation for robust innovation while driving sustained operational efficiency and multiyear margin expansion.

Looking at highlights from the full fiscal year. Fiscal year revenue grew 9% year-over-year to $790.8 million. We added over 1,800 core customers during the year. Revenue from our core customers grew over 11% year-over-year. This cohort represented 73% of our revenues for the full year. And we also added over 90 customers spending $100,000 or more on an annualized basis during the year and grew 13% year-over-year.

Moving on to the balance sheet and cash flow. Cash, cash equivalents and marketable securities at the end of Q4 were approximately $434 million. Our remaining performance obligation, or RPO, was $524.8 million, up 22% from the year ago quarter. Current RPO grew 17% year-over-year, an acceleration from last quarter. This represents 78% of total RPO and will be recognized over the next 12 months. Our total ending Q4 deferred revenue was $333.9 million, up 10% year-over-year. Building on our operating margin strength, Q4 adjusted free cash flow was $25.7 million or 13% on a margin basis.

This quarter, we bought back $58 million of our Class A common stock or 4.5 million shares at an average price of $12.75 per share. This activity is rooted in our disciplined approach to capital allocation and our primary objective of maximizing long-term shareholder value. Reflecting our conviction in the long-term opportunity ahead our Board recently increased our share repurchase authorization by $160 million. Including the $39 million remaining under our prior authorization as of January 31, we now have almost $200 million available for future repurchases. We believe repurchasing shares at current levels represents an attractive capital allocation decision while maintaining the financial flexibility to continue investing in innovation and growth.

Before I walk through the guidance in detail, I want to highlight a few key assumptions that underpin our outlook for fiscal year '27. These assumptions reflect both the strength we are seeing in parts of our business and the headwinds we continue to navigate. Enterprise performance remains stronger than the company's overall growth rate. At the same time, self-serve, which is primarily SMB, remains a headwind. Headwinds in our PLG business are expected to create roughly a 2-point drag on ARR growth.

Our guidance does not assume a recovery in that motion in fiscal year '27. Importantly, this does not change our conviction in PLG as a long-term growth driver. We also saw encouraging signals in the tech vertical in Q4. However, it is too early to call a bottom. We are not embedding continued stabilization in our fiscal year '27 outlook. In addition, we are assuming only modest improvement in our net retention rates over the course of the year.

Lastly, given the launch timing of AI teammates, we expect minimal contribution in the first half of fiscal year '27, with a more meaningful ramp in Q4. In aggregate, we expect our AI offerings to represent nearly 15% of new ARR in fiscal year '27. We also believe these products will contribute meaningfully to PLD over time. However, given the timing of the self-serve AI teammates launch in the second half of the year, we have not factored incremental PLG upside into our guidance.

Turning to margins. We expect gross margin to remain in the high 80s, consistent with our Q4 exit rate. Our operating model supports margin expansion while continuing to invest in our highest conviction growth areas, particularly AI and go-to-market productivity. In fiscal year '27, we plan to allocate approximately $10 million of incremental investment into AI R&D focused on accelerating innovation across AI studio and AI teammates.

At the same time, structural efficiencies are creating capacity to fund that innovation. We have reallocated resources toward higher leverage growth areas, reduced lower ROI spend, optimize our geographic mix and improved productivity across go-to-market and support functions. These structural improvements provide a clear multiyear path to margin expansion. As a result, we can expand profitability while continuing to invest in high-return growth initiatives.

Now moving to guidance. For Q1 fiscal 2027, we expect revenues of $202.5 million to $204.5 million representing 8.1% to 9.2% growth year-over-year. Based on current rates, we expect an approximately 60 basis point tailwind to our Q1 revenue growth in constant currency. We expect non-GAAP operating income of $15 million to $17 million, representing an operating margin of 7.4% to 8.3%. And we expect non-GAAP net income per share of $0.07 to $0.08, assuming diluted weighted average shares outstanding of approximately $241 million.

For the full fiscal year 2027, we expect revenues to be in the range of $850 million to $858 million, representing a growth rate of 7.5% to 8.5% year-over-year. Based on current rates, we expect an approximately 20 basis point tailwind to our full year revenue growth in constant currency. We expect non-GAAP operating margin of at least 9.5% and non-GAAP net income per share of $0.36 to $0.37 assuming diluted weighted average shares outstanding of approximately $243 million.

We remain focused on positioning Asana for long-term success in the Agentic enterprise. AI studio momentum continues to build and scaling AI teammates will be a key driver of durable profitable growth and expanding margins over time.

And with that, operator, we're ready for questions.

[Operator Instructions] Our first question comes from the line of Taylor McGinnis of UBS.

Sonalee, it's been great working with you and wishing you all the best. And Aziz, congrats on the promotion, very well deserved.

Maybe a 2-parter for me. First, I think there are a lot of questions on how sticky Asana workflows are in an AI world, and what moat Asana has in developing its own AI solutions. I know you spoke a little bit about this in the prepared remarks, but maybe you can just provide a bit more color based on what you're seeing from your customer base.

And then as a second part to that, could you talk about how the Asana app in cloud work? So does this create a risk that cloud is used to automate more Asana workflows? And I guess, how would Asana share in those economics? So maybe you could just provide more color and unpack why it makes sense for Asana to partner here and how that's being structured.

Taylor, thank you for the kind words. Sonalee and Aziz, they're both beaming over here. And yes, just I'll hit your question directly. The reason that we believe AI is a tailwind for Asana is because we're not just a collaboration application. We are the coordination layer for work. If you think about how work is structured, the ownership, the sequencing, the tracking, completion across teams, that really is perfect for our platform. So as the foundational models get more sophisticated, it doesn't eliminate the need for coordination execution. It actually increases it. More AI output means more actions, more dependencies, more cross-functional complexity. So AI doesn't reduce that coordination, it multiplies it.

So you heard in the prepared remarks why our strategy is to become the pioneer of the Agenetic enterprise. This is where Agenetic enterprises where humans and AI agents are coordinating together at scale. And if you think about our history, 17 years ago, we created the work graph, which was around human-to-human coordination which is about the who, the what, the why, the when of work. It's that same architecture that provides the framework for human to agent collaboration.

So specifically to our differentiation, that Agentic enterprise requires 4 things: number one, context in the flow of work, which is about that unique understanding of who's doing what, by when and how across the enterprise. It also requires a durable institutional memory. So this means a persistent, permissioned understanding of those relationships between projects and people. It requires multiplayer orchestration. Think about that as a shared canvas for teams to work upon where agents and humans can work together on the same projects.

Then finally, it requires enterprise-grade confidence. Enterprises need auditability, roll-based access control, cost controls, ROI visibility that Asana was built with those enterprise controls from day 1. So one of our products is a real practical manifestation of that, which is AI teammates. These are teammates that are working against structured enterprise memory, they're permissioned governance. They're coordinated across workflows, acting as collaborators with inside real teams and real projects. That's why we've had such strong feedback from the 200 customers that we have in beta today.

So AI doesn't replace Asana, it actually amplifies the need for structured context, institutional memory, cross-functional orchestration and governed execution, and that's our architectural advantage. That is the foundational layer for AI, a system of action for work.

With regards to your question around core, think of the core application as a way within the core context to access the Asana work graph and UI, if you're an Asana customer. So you would need to be a core customer and an Asana customer. Then within your AI chat, you can turn those into action or work inside Asana.

Our next question comes from the line of Billy Fitzsimmons of Piper Sandler.

Sonalee, best of luck in your future endeavor and Aziz congratulations. I want to double-click on the tech vertical commentary in the prepared remarks. In past quarters, we've seen indications that the tech vertical has stabilized. You had spoken to fewer tech down sales, better tech renewals. And last week, we had a fintech company radically downsized its workforce due to AI. That's an example of one, but it's an example that's on a lot of people's minds. So how is the potential for maybe AI-related workforce reductions, specifically in the tech vertical factored into guidance? And then what's Asana seeing and hearing in real time for customers?

Billy. Yes, first, a couple of notes on tech. As you noticed, this is our third straight quarter of in-quarter improvement in NRR from the tech sector and our tech ARR is flat for the first time in 7 quarters. So we're obviously closely monitoring the fintech company that you discussed, but we feel much more isolated today than we did 12 to 18 months ago. There's a few reasons for that.

Number one, our tech exposure is structurally lower. Tech is now less than 25% of our revenue and continues to decline as a percentage of our mix. So our revenue base is way more diverse across non-tech industries in international. Number two, the nature of our enterprise relationships continues to strengthen. We've discussed our studio and AI teammates. These allow us to go much deeper into core workflows and critical business processes that ties more directly to business outcomes, not just headcount. So this workflow level and betting trends to continue to materially drive our NRR and help with our retention.

Third, we just don't have the same level of concentrations of renewal exposure in FY '27 and than we had over the prior 2 years. So the renewal profile is much more balanced. It doesn't mean we're immune to macro workforce changes, but it does mean that today, stabilization in tech, improving in quarter NRR, stronger expansion activity suggests that trends are going to be much more durable than we experienced previously. And our strategy of the genetic enterprise is directly aligned to making retention less seat volume dependent and more workflow value dependent.

[indiscernible], Sonalee here. Firstly, thank you, everyone, for your really kind comments. I loved working with all of you analysts covering our stock. But just -- with respect to the guide, as Dan called out, and you've heard me call out actually in the last couple of quarters, we have seen improvements in NRR. Third consecutive quarter of in-quarter NRR improvement of our top 10 renewals this quarter, of which many were tech, they renewed above 100%. But the good news is we've only incorporated a modest improvement into our guide. But in terms of what we're actually seeing in front of us right now, we don't see big risk with respect to the tech renewals. This is purely prudent.

And again, just wanted to see several quarters of that stability before calling a trend. I think what you've found with me, and I think you will find with Aziz is we guide based on what we have high confidence in today and what we see in front of us today.

Our next question comes from the line of Rob Oliver of Baird.

I'll also pass on my congrats to Aziz and Sonalee, great working with you. My question is for you, Sonalee, just around your comments around the top of funnel and some of the prolonged nature of the change in adapting to sort of the new environment around the Open Web and how people are accessing information. I was wondering if you could just help us understand, I know you guys said you still feel very good about the PLG motion. What sort of changes have you made today, what changes are working? And how do you expect that will play out here in FY '27, so you can get back to a more normalized top of funnel.

Thank you, Rob. Let me start, and I'll hand over to Sonalee. So first off, yes, there are a lot of headwinds in PLG. Buying behavior in self-serve and SMB has shifted meaningfully for many of the players in SaaS over the last 12 to 18 months, there is a structural shift in how customers are discovering and evaluating and experiencing software. That being said, we have seen improvements. We continue to see sequential improvements in our top of funnel and conversion. And our AEO search initiatives and channel mix adjustments are driving improvement but the recovery is a bit more gradual than we initially expected.

So you'll see us doubling down in PLG in the areas of AI-enhanced search, funnel optimization and product experience channel mix evolution and monetization expansion within self-serve. We've also brought new leaders in place, our CMO and our PLG GM to have clear accountability to these adjustments. So the phased road map for us in H1 looks like deeper product experience improvements in conversion optimization and in the second half, new product introductions into the self-service base, including some AI-driven offerings.

So PLG and SMB remain an important growth segment for us. In fact, Asana is just so well suited to being bought and consumed digitally. So our objective is to rebuild PLG into a growth driver in the long term.

Yes. If I can just add to that. If you look at our PLG contribution to the guidance for fiscal year '27, it's about a 2 percentage point drag on ARR growth. and again, fully embedded in that fiscal year '27 guide. We're not modeling top-of-funnel pressure abatement despite this strong focus on reimagining the motion and hopefully offsetting those headwinds with all the initiatives Dan called out. And I think what's important to note here is that absent that 2-point drag from PLG, this would represent an acceleration in this guide. So I think that's super important to think about just in the context of the overall guide.

The other thing I would just say with respect to the guide is it's not embedding any further improvement from tech stabilization, and it's only factoring in a very modest improvement from the NRR improvements that we've seen to date. So if any of those end up being better than expected, that would represent upside.

Our next question comes from the line of Rishi Jaluria of RBC.

Let me echo my colleagues, Sonalee, it's been fantastic working with you over the past 1.5 years and wishing you all the best in your next endeavors. Aziz, congratulations really looking forward to working even more closely with you in this function.

Look, I want to maybe think about thinking about the growth trajectory of Asana, Sonalee, you talked about RPO, if I'm not mistaken, is accelerating. You're talking about AI SKUs is representing 15% of new ARR this year and maybe greater ramp in the back half of the year. As we think about all of these moving pieces, I know it's not in the guide for FY '27 because we think maybe beyond that. What are kind of the building blocks to drive acceleration in Asana as a whole, including from Asana AI.

Rishi. So let's start with our strategy. Our strategy is to be the pioneer of the genetic enterprise. That is a strategy that fundamentally orientates us towards long-term growth acceleration. So positioning Asana not just as a CRM provider, but as a system of action, the layer for the genetic enterprise, which is a larger and faster growing TAM.

In the near term, it's a tale of 3 cities. Firstly, we are going to benefit from the AI tailwind. You saw that with AI studio where we achieved $6 million of ARR in Q4. And our AI products are going to be 15% of our new AR in FY '27. Teammates will be GA-ing in late Q1, which allows us to have new reasons to talk to our installed base and approach net new buying centers.

On the PLG side, that continues to be a near-term headwind. Our objective is to turn that into a long-term tailwind. And in the absence of that headwind would be reaccelerating in the near term. And the third point is around our SLG or a sales-led business. And here you're seeing positive proof points already, tech stabilization. And NRR is encouraging, but we need some more quarters of proof points. So if we bring that all together, the acceleration for us is a combination of AI-driven monetization, PLG stabilization and rebuild compounding SLG productivity, improved retention dynamics and expansion into the broader Agendic enterprise TAM. We believe the structural advantages of our platform position us well to capture that opportunity over the long term.

Rishi, just to add to Dan's comments. So you're right, both billings and CRPO accelerated in Q4, and I think that reflects the strong demand environment we're seeing from enterprise customers and their commitment to building long-term partnerships with us. The other data point is of those top 10 renewals in Q4 that were over 100% NRR. That was a fairly large proportion were tech customers. And then on AI products, the good news there is that AI studio, we exited Q4 with over $6 million in ARR. But importantly, the velocity in the back half was much stronger than the front half. and we expect our AI platform to contribute about 15% of net new ARR in fiscal year '27. Add or layer on top of that, the launch of AI teammates in the second half and again, you see those potential drivers of growth as we look forward.

Our next question comes from the line of Steve Enders of Citi.

Congrats Sonalee and Aziz. And maybe this question is for disease is in the room, but just in terms of how we think about the guide and how you think about running the finance strategy moving forward? Just any changes in terms of what that means moving forward or how this guide was built versus maybe how things were done before.

Yes, Steve, it's good to be with you, and thanks for the question. So I've been -- I was fully involved in setting this guide as I have been since I arrived at Asana. So fully stand by it, fully supported, helped Sonalee and Dan build it and get conviction over it. And there's no philosophical shift in the guidance strategy or the financial strategy. It will continue to be disciplined, continue to be close to the pin and reflect what we're seeing at the time of guide. It's a dynamic environment. There's upsides and potential risk. We factor that in the guide. So I'm fully supportive and I'm aligned with it. So I appreciate the question.

Our next question comes from the line of Josh Baer of Morgan Stanley.

Congrats Sonalee and Aziz. Dan, you were talking about growth not needing to come at the expense of margins. If we look like very broadly or high level at the past, there's a period of very rapid growth and negative margins more recently decelerating growth, but really nice margin expansion. So what is it about today that allows for both growth and margins? Is it as simple as AI driving both product cycle, driving top line and AI efficiencies internally driving margin expansion, combo or other factors, what gives you confidence in growth and margins?

Yes. Thanks for the question, Josh. And I know we're going to see you in a couple of days time in person. As you mentioned, firstly, the advancement of the AI models, the foundational models actually helps us manifest our vision of the Agenetic enterprise. As a foundational layer of the Agenetic enterprise, we do see that this is an accelerant for us. It allows us to deliver on a very ambitious product road map over the next 12 to 18 months. So yes, this is a new growth driver for us. And in doing so, it also allows us to scale efficiently as we grow within our own operations as we seek to continually push the frontier of driving to that level of efficiency. So yes, the answer is both.

Josh, I can't resist, but I have to add to that. You've seen strong margin expansion over the last couple of years. That's not something that is going to really change or abate. We think we can continue making investments in AI in a disciplined way, and we're confident we can continue expanding margins sequentially and in many years to come. And there are still meaningful levers to expand those margins. shifting our head count to lower-cost regions, which we've already started, but there's more to come. third-party spend, increasing leverage in sales and marketing where actually Aziz has been going deep in the last couple of months and then driving that AI-powered productivity gains, which you would all expect of us. So again, there's more goodness to come.

Our next question comes from the line of Jackson Ader of KeyBanc Capital Markets.

The one that I had was with AI expected to be 15% of net new ARR in the coming year. How should we be thinking about AI as truly additive and incremental versus maybe a replacement of what would have been broader platform spend within existing customers?

Yes. Let me jump in on that one. If you look at our AG customers today, as an example, and AI teammates, A lot of it is incremental that we are finding net new use cases and new buying centers. And some of it is replacement. Some of it is being able to do the work that they were currently imagining that much more efficiently with an AI-enhanced solution. So a bit of a combination of both, I would say.

And just if I could add there. These new products, AI studio and then increasingly with AI teammates in the second half, they've been great in terms of expansion at -- in these renewal conversations. So again, in terms of mitigating potential downgrades, I think it's something that we we're looking forward to having that incremental thing to go out to our customers with. So it's downgrade mitigation and also significant expansion opportunity.

I would now like to turn the conference back to Eva Leung for closing remarks. Madam?

Thank you, everyone, for joining the call. We'll be on the road attending the KeyBanc, Citizens and Morgan Stanley conference this week. Looking forward to seeing all of you. As always, if you have any questions, please reach out to me at [email protected]. Thank you very much.

This concludes today's conference call. Thank you for participating. You may now disconnect.

Hi, everyone. Welcome to the 2025 Barclays TMT Conference. I'm Eamon Coughlin, Software Research Analyst here at Barclays. Very happy to have Sonalee Parekh with us today, CFO at Asana. Sonalee is a former Barclays employee, so I have to mention welcome back.

I just saw some former colleagues in the row there.

Welcome back. Welcome back. It's great to have you here.

I guess, for anyone in the room that maybe missed your 3Q earnings, can you help us understand some of the key takeaways from the call?

Yes, absolutely. So firstly, thank you. I'm delighted to be here and nice to reconnect with you again.

So key takeaways from our Q3 earnings: It was a really solid quarter. We were really proud of what we accomplished. So we delivered revenue growth above the top end of consensus and our guide. We grew 9% year-over-year. Also, very importantly, we delivered record operating margins, so 8% operating margin and also raised our guide on revenues, which I forgot to add to that. Not only did we beat, we beat and we actually raised, rolled and raised.

And then thirdly, net retention stabilized and that's very, very significant for us. And in my prepared remarks, I talked about net retention being at or near the bottom, which is something a new comment I had made this quarter.

And then finally, free cash flow, we delivered another strong quarter of $13 million of free cash flow. So really across the board, it was a very, very solid set of numbers. And then just on new products, our AI Studio product again showed sequential growth in bookings, which we're really excited about. And hopefully, you'll ask me a little bit more about AI Studio and our AI products.

I'd be remiss not to. I guess just staying on some of that, we can unpack a lot of that there. But like what gives you the confidence that NRR is near or at the bottom? And maybe what's some of the key drivers to improve that? And then maybe what is some of the risks that could actually degradation? Just any sort of comments on how you think of the trajectory there?

Sure. No, it's a great question and one that I think about a lot. And what I said in a couple of the one-on-ones I had earlier is when we make comments in the earnings script, like they're very scripted, and we think a lot about the language we use. So to say we are at or near the bottom was a change versus what I said going into Q3.

So as we now look ahead to Q4, I am more confident today than I was when we were going into Q3, despite the fact that Q4 is typically a larger renewals quarter in terms of volume, dollar volume, but the actual number of large renewals is less for Q4.

So the real drivers was a couple of areas. So one, GRR improved across the board in all cohorts. Secondly, net retention improved across all cohorts, and it was the second quarter in a row. The last quarter, we saw net retention tick up in the quarter. And whilst we were encouraged, we said too soon to call a trend. Now we've seen 2 quarters of in-quarter net retention improve. So that was the reason that I gave the change in language.

Thirdly, we saw better expansion and new products played a role there. So as we enter these renewal conversations, we now have a new quiver in our arrow in terms of offering customers foundational service plans, AI Studio. And then as we look ahead -- this wasn't the case in Q3, but as we look ahead, AI Teammates as well. So I think those new products are helping with the renewal conversations.

And then finally, in our self-serve business, which is still a very large portion of our overall base, and does tend to be the churniest part of our business, we actually saw the best retention that we've seen in a year in 12 months. So I think taking all of that together, it just made me feel more confident as we looked ahead, and excited to keep delivering and executing.

Yes, absolutely. I think just like when we think about some of that renewal base in the fourth quarter, maybe what drives some of the confidence in that NRR being stable? And then maybe as we think about the last 2 years, like that trajectory, like what is driving that stability? Are we seeing the end of that rightsizing from that customer base? And then maybe how to think about next year?

Yes, it's a really very intuitive question or insightful question because one of the things that we've talked about in this earnings but also in the last several quarters is just our exposure to tech, which actually has been declining. So today, tech represents about 25% of our ARR base. But if you look 1 or 2 years ago, it was closer to 1/3 of our base.

So we have that working its way through the base. And some of the large renewals that I called out, as we look into Q3, were in the technology vertical. And I called those out actually for the entire second half, but many of those were in Q3, which we've now gone through. And then we have several in Q4, although they're lower in dollar amount. But what I would say and what we're finding with the tech exposure is, one, it's smaller today than it was; but two, the customers, the tech customers that we have who are renewing as they renew for the second time, they're not coming back for a second downgrade or a second bite at that downgrade apple.

So basically, we're lapping these larger renewals and we're lapping the downgrades from those renewals. So as they work their way through the base, they become a lesser and lesser proportion of the overall. So that's helping.

And then the other thing is, in Q3, we saw better expansion. And I think part of becoming a multiproduct story is really as we enter those renewal conversations, making sure that our sellers don't just have incremental seats or higher SKUs to sell, but actually have new products. And one of the things that's most exciting about our foundational service plans is that customers that buy those what we find is within 6 months, their utilization goes up by about 20%.

So actually, you end up with healthier customers. And hopefully, as those customers renew down the road, they'll be less likely to churn, so healthier and stickier customers. And the other thing I would say is that you end up with customers or customers who buy more than 1 product from us are much less likely to churn. And that's sort of the thesis. And again, that's what gives us confidence that we are either at or near the bottom of net retention.

Super interesting because a company somewhere in the SaaS space, Braze last night printed and they had the first -- second quarter in a row of in-quarter net retention improving from -- they're getting the value of the beast from like [indiscernible] renewals beginning to improve. So it's interesting to...

So it's very similar...

Very similar dynamic.

Yes. Okay. I'll have to read that.

Yes, definitely. I guess just understanding some of the different challenges that are going to the market. I think SEO has been a difficult change for not just Asana, for a variety of different SMB SaaS companies. I guess just understanding some of the remedies that you're pushing through the market, is there any sort of context you could provide on what your net new business is being driven by SEO? If there's any sort of context you can provide and then some of the remedies that maybe were -- that Asana is working through to improve that motion?

Yes, absolutely. So this is not a new phenomenon for us. It's something we've called out now for a couple of quarters, and we did call it out again in Q3, and we expect it to continue to be a tailwind for Q4; however, fully reflected in the way I guided for Q4 and the full year. So we -- I guess it was several quarters ago, we started to see an impact in terms of like top of funnel, which for us, translation is kind of visits to our website and trial starts of Asana.

And what we found was that although the number of visitors to our website was declining, the traffic that was coming to the website was higher intent traffic, so more likely to convert. So whilst we saw a decline in the visits and the trial starts, we saw better conversion rates. But when you take the lower numbers visiting the site multiplied by the higher conversion rate, it's still a downdraft. It's still a negative.

And what we've seen in the last several months and what I called out at earnings and what we're continuing to see is a month-over-month improvement in those visits to our website because of some of the initiatives we put in place. And at a certain point -- and I haven't been specific in terms of like when this will occur, but at a certain point, we will hit the crossover point where the decline in visits is more than offset by the better conversion.

And ultimately, like our belief is that we emerge stronger from this because you actually end up with healthier customers that actually always should have been Asana customers as opposed to, I think, in the past, perhaps with SEO and with some of our SEO investments and marketing spend, of which SEO was a large portion of our overall marketing spend.

Like programmatic as a percentage of overall marketing was about 75% and SEO was the largest portion of that programmatic spend. But when we hit that crossover point, ultimately, that will end up being, we believe, a tailwind because you end up with stickier customers and customers that are likely to stay with us and have a higher propensity to expand with us and have a higher propensity to buy more products from us.

So that is kind of the Holy Grail. And what we're doing is we've used the opportunity to, one, reallocate some of our marketing spend to channels where we believe LLM search is more prolific and prominent. Some of the channels that are net beneficiaries are things like Reddit, YouTube, Quora. And the other thing we're doing is in product we're trying to make -- Dan, our CEO, calls it like the time to that aha moment within the product, we're trying to make that time to get there much quicker.

So we have this new prompt to project that's on our website today, and we think that, that is already driving the kind of behavior that we're hoping to see from customers.

And then finally, the content within our website and the content in our marketing has changed. So the things that resonate with LLM search are more things like short-form video and demos and webinars and FAQs and ROI calculators and those, again, have proven to be really efficient in terms of getting the right type of customer in those trial starts that then ultimately convert.

And I think in the past, we were perhaps -- and I remember when I joined Asana, and I think you are going to ask me about margins a little bit later. But I remember one of the things that really hit me when I joined Asana when I was doing extensive benchmarking of our OpEx, our marketing spend looked fairly off benchmark, like too high. And I do believe like this is an opportunity for us to rightsize some of that marketing spend.

And again, like it doesn't mean that it's going to go straight to the bottom line. We could reinvest in other marketing channels, which is one of the things we're doing today, but there should be some benefit to the margins as well from like this reallocation of marketing spend into more efficient channels.

Definitely. So I mean, I think it's an evolving story for, again, not just Asana like this is a clear market dynamic that I think a lot of people are trying to work through. It doesn't seem like there's a perfect answer, but as you just mentioned, there's a variety of different channels, I think, you can work through.

Yes. And I think like the point about us emerging stronger, I do firmly believe that because the customers and particularly in that base, those tend to be our churniest customers. So it's actually great that we're really inspecting that today and finding remedies.

Definitely. I guess, I mean, one of the more exciting parts of the Asana story is some of the AI adoption, some of the great growth that you're seeing there. I guess just some of the -- can you just describe some of the early feedback you've seen from some of the particularly the enterprise customers regarding Teammates? And then maybe just trying to understand some of the -- maybe the ARPU uplift that we could see from that adoption?

Yes. I love the analysts always ask about like how much are the numbers going up? So we haven't broken it out yet. But you asked about AI Studio and its adoption and then Teammates. And to be clear, it is still early days, but a couple of the numbers that we've put out around AI Studio was: In our first quarter of going GA and it went GA mid-quarter, we did $1 million of ARR. The following quarter, we said we more than doubled that. And then this last quarter, Q3, we've said that we saw strong or healthy sequential growth or strong and healthy sequential growth quarter-over-quarter.

So AI Studio is really doing very well and resonating with customers. What we found with AI Studio in its initial launch was that it was really being adopted by customers that were fairly sophisticated Asana users. Customers that were using Asana already, we call them our builders, but like they were building workflows and already used Asana using like rule-based actions.

And what we've now done is rolled out AI Studio to a much larger proportion of the base. And I think this is what's really exciting because now AI Studio is available to our self-serve base. So I think it really proliferates among the base. And some of the use cases -- like some of the most powerful use cases, think like very repeatable tasks, things like anything involving customer intake, anything involving like marketing campaigns, anything involving like multistep processes with lots of handoffs, lots of procurement use cases.

One of our best examples is like a CEO that is actually using it for RFPs to go through RFPs and his procurement process. But with Teammates, I think what's so exciting is to me, Teammates, it democratizes an AI Studio because the AI Studio, I think, is for people -- and the initial launch again for those more sophisticated users who are building workflows.

Teammates -- actually, you can use the Teammate to build a workflow for you. So I think it has even broader and wider adoption, even broader like TAM in terms of use cases and the kind of customers and departments that are likely to use Teammates. So we actually think that this is an even bigger opportunity than AI Studio.

In terms of where we are on Teammates, we haven't gone GA yet. We will next quarter. But we are in beta, and we have 30 reference customers, and the feedback has been overwhelmingly positive. So we're really excited about that. And we, internally, like, of course, we have to dog food, we're using Teammates a lot within the organization. In some of the use cases there are SDRs and BDRs using Teammates.

We have Teammates doing enterprise technology, code reviews, like you name it, ticketing. We're actually using it for all ticketing within Asana today. And we moved off of another point solution in order to offer our internal teams ticketing just using AI Teammates.

It sounds like there's clear ROI from these products already and early traction with Teammates. I guess just trying to understand like some of the go-to-market with AI Studio and then Teammates, is that a token-based or credit base for the customers? How has that early reception been? Is that the right monetization opportunity? Are you thinking about it differently? Anything to describe there?

Yes. So we are still thinking about it. Like we've gone to market today as -- so AI Studio and actually Teammates, it's a platform fee, quarterly platform fee, and it's use it or lose it. We've been very deliberately generous with the credits. I know tokens or credits, sometimes people use those interchangeably because what we really wanted to do was drive as much adoption as possible.

Because we actually do think there will be high willingness to pay and there is a high willingness to pay, so long as you're driving ROI and the outcomes that customers are hoping to gain. What we found is that customers really, at this stage, prefer knowing what their bill is going to be. So they want that visibility and spend.

Whereas if you move to full consumption or straight consumption right away, they don't necessarily know the value they're going to get and they also don't know what their bill is going to be. So we felt like this was definitely the right way to hit the market. I think as we look ahead, and I think part of Dustin's original vision was that the world was likely to evolve from seat-based to more consumption-based models.

And AI Studio and Teammates is really a way of future-proofing Asana and our role in the CWM market so that in the future, we can grow with our customers as their engagement with us grows. We no longer have to grow based on seats. We can grow based on the amount, like even a small group of power users are using Asana to drive outcomes. And I think like we feel very, very good that as we look ahead, if the seat-based model does, and again, our thesis is that there will be some movement in the seat-based model, that we have this solution, where we can grow and grow incrementally over and above what our ARR base is today.

Definitely. I think the conversation with AI and the ROI that is driving is super interesting when it ties back to like a power user. If you and I are both leveraging Asana and I use it 24 hours a day and you 2 hours a day, for a seat-based model, we're the same price. But then for -- with AI and the introduction of seat-based model, it's a whole new lever...

Exactly. And that's exactly what Dustin had in mind when we first -- or when he conceived at this. And the other point I would make is that AI Studio and Teammates have been many, many years in the making. So our R&D spend isn't going to suddenly like skyrocket or there won't be any step change in our R&D spend because, again, these models and -- or these products have been on our road map for many years. And the beauty of AI Studio and Teammates is that it sits on top of our work graph, which is our core architecture, and therefore, Studio and Teammates are context aware.

And I think that's another key source of differentiation. And again, when you talk about pricing power and willingness to pay, it's about the value you're delivering for customers. And we believe we can deliver outsized value because we are the system of work that these Teammates, agents and workflows pull the data from.

Yes. No, definitely. I guess shifting a little bit to some of the competitive dynamics like throughout the space. Smartsheet was recently taken out to go private and monday.com has this new multiproduct story that it's pushing to the market. I guess where does Asana stand out? What drives the differentiation and what drives those wins in the RFPs?

Yes. So I think a couple of things. Like one, I would say, is the flexibility and scalability of our platform. And again, like when I talk about our R&D spend and the work graph, like these are things that Dustin was thinking about many years ago that like actually were really benefiting from today.

So you may have heard me talk about our very large -- we won a $100 million 3-year TCV deal with one of the major hyperscalers 2 quarters ago. It's a 3-year deal, and we are considered a foundation software with them. And we haven't been specific about the number of seats, but like it's 250,000-plus. We are the only CWM platform that could scale to that level.

Not to mention, you can imagine the scrutiny over the controls and certifications and governance and security, everything that a sophisticated buyer like that would need. We were able to pass that test. I think like that scalability and flexibility and governance and security is -- puts us into a category of our own in terms of being able to serve large enterprise. And I don't think other CWM platforms are anywhere close to that.

Secondly, when we talk about Teammates and agents, I believe our horizontal platform makes us truly differentiated versus some of these other solutions are very narrow in terms of the types of markets and work that they can serve either specific to CRM, specific to ITSM, specific to DevSecOps, whereas we can go across organizations and like within organizations.

And I think we believe and I see it, and I think everyone in this room would see, that work is cross-functional. So it's very hard to be a CWM platform that's siloed. And I think some of the other competitors, you mentioned, are much more siloed than we are. And we think that, that horizontal platform that we designed and the work graph being so horizontal is a key differentiator for us.

Yes. No, that makes sense. I guess just understanding some of the guidance for 4Q, how to think about 2027? And then I think reflecting on your time at Asana, packaging a lot of questions into one, but I guess just like I would love to hear your perspective on your last 1.5 years since you came to Asana. What are some of the things that you think Asana has done well? What do you think some of the things that maybe you could have improved on? And then maybe how to think about 2027 growth and profitability? Obviously, not looking for a preannouncement, but anything...

No, I'm going to guide. So the fiscal year '27 guide is. So yes, no, great questions. And of course, like without being specific, like you've heard myself and the rest of the team say that like our ambition, absolutely, as we look ahead, without putting any time frame on it, is to reaccelerate growth and to continue driving margin improvement. These are 2 things I believe we can do.

In terms of the drivers of that reacceleration, I think net retention, it was your second question, I think it was the right question. We need to get net retention on a path to 100 and above. I think stabilization to slight improvement is a really good start. Stabilization of that trend was key to being able to believe in improving it.

I think our PLG business, so our product-led growth business, what we're learning in terms of the SEO and top-of-funnel dynamics will allow us to emerge stronger. And I think actually what is today a headwind ultimately becomes a tailwind. I think there is more we can do with channel. Like today channel is a tiny part of our overall ARR, single digit.

If you look at some of those competitors you talked about, it's like 40%, 50%, 60%. So I think that's a huge untapped distribution channel. And I think with our new products, like they're tiny today, but -- and if you look at a couple of million of ARR as a percentage of an $800 million-plus ARR space, it doesn't sound like a lot. But if you think about how much those products will contribute to future bookings, it becomes meaningful. So that gets me excited.

When I reflect -- I see we have 10 seconds left, but when I reflect what have we done really well, the new product introduction, keeping our edge and lead in AI and I think the other thing is like driving 12 percentage points of margin improvement, which has allowed us to also free up -- like become more efficient and free up dollars to be able to invest in our AI platform.

Yes. Two companies in a row, you're just driving incredible operational efficiencies. So thank you, Sonalee, for having us and great to be here. Thank you.

Thanks so much.

Okay. Hello, everyone. Thank you so much for joining the session. My name is Taylor McGinnis, and I head up the mid-cap application SaaS coverage at UBS. And today here with me, I have Asana's CFO, Sonalee. Sonalee, thanks so much for joining.

Great to be here. Thanks for having us, Taylor.

Of course. And then I have Aziz, who is Head of Strategy and FP&A. So Aziz, thanks to you, too.

Yes. Thank you.

Maybe a good place to start since you guys just reported last night, and we're very kind to come here right after reporting. Maybe you could just give a little brief half of the 3Q earnings call, you guys had a nice beat in the quarter, raised the 4Q numbers? And maybe you could just talk about what you think are the key takeaways for the group.

Yes, sure. Thank you. And you're absolutely right. We reported, we did the call back, and then we jumped on a flight. So here we are in beautiful Scottsdale. So a couple of things we're really proud about in the quarter. One is, as you say, it was a beat and raise quarter, which as the CFO, you always love. And that was on the revenue side. So we beat the high end of our revenue guidance. We grew 9% year-over-year, 9.3% actually year-over-year. And we also had record operating margin, 8% operating margin. And I think what's the most exciting about that is it was a 12 percentage increase year-over-year.

We also had great cash flow. We had NRR that stabilized. And what's important to me there is that in the quarter NRR, which is something that I pay a lot of attention to because I think it's more of a leading indicator as opposed to reported NRR, which is a lagging indicator. We had in quarter NRR improved for the second consecutive quarter. And that led me to comment on the -- in my prepared remarks that we are at or near a bottom on NRR. And that's the first time I've said that. So I think that's a really key takeaway.

And then finally, hopefully, you're going to ask us a lot about AI and our new products, but AI Studio, we saw another quarter of sequential growth there, solid sequential growth. So we're super excited about the impact that, that will have as we look ahead.

Perfect. And I'd love to touch on the improvement in period NRR because I think that was the highlight of the print, and I know investors have been waiting for that trough. So could you just talk about what's giving you comfort that you're at or nearing that bottom? And how do you think about the drivers of that metric as you look ahead?

Yes, great question. And by the way, that was the #1 question in our one-on-ones today. So I think everyone is focused in the right area. So a couple of things that drove that. Firstly, we saw an improvement in GRR across every cohort. Secondly, we saw an improvement in NRR and the largest improvement in NRR in our 100,000-plus customer cohort. Thirdly, we saw a really big improvement in terms of renewals and in particular, tech renewals, which was something I had called out in Q2 as being a potential risk. And let's just say those renewal conversations went better than feared. And in fact, certain renewals in the tech sector, in particular, which has and continues to be a headwind for us, were not just flat renewals, but turned out to be expansion deals because of the new products. So expansion on seats and also AI Studio and what we call FSP or foundational service plan, which are a new product in motion for us and that's basically paid services. So taking all of that combined to help to drive that higher.

And then the last point I would make is in our monthly business, our small business, which is the tuniest part of our base. we saw 12-month highs in terms of retention. So it was like strength across the board and 2 consecutive quarters that really gave me the confidence to make that comment. And we choose our words really deliberately in prepared remarks. I'm sure you all know that. But I think people really picked up on that. And I think that absolutely is the takeaway. And as we think about it going forward, I said at or near the bottom. I do feel like the trends, and I looked at where we are now as of kind of our earnings print, we expect those trends to continue. And there are some really great initiatives we put in place. Over the last year, we hired a new Chief Customer Officer. And those plays that he's initiated around customer satisfaction around the coverage model, like the number of customers within our base that actually get customer success managers, that is all really playing out as we had hoped. So as we look ahead, we're feeling good about that and more confident than we were a quarter ago.

Yes. I want to talk about the tech vertical because the tech vertical, to your point earlier, had been the main source of some of that pressure as it was for a number of other software companies given all the rightsizing and optimization activity that's occurred over the last couple of years. So in terms of giving you comfort as we look ahead, that were maybe past the worst of it, why is that? Is it that now these companies have gone through a number of renewals, you're now beyond that? Is it that there's more cross-sell opportunity with these AI solutions, maybe it's your own execution, maybe it's a mix of all those things? But could you just unpack what gives you the comfort that you're beyond that and the drivers behind that?

I love what you laid out because it shows me you really pay attention to what we say because it's all those things. So I think the tech vertical today is about 25% of our base. That's down from a year ago, down quite significantly. It was about 1/3 a year ago. Today, it's 25% of our base. So we still have high exposure to detect, but it becomes a lower proportion of our overall base.

The second thing about tech that I think is really interesting is they tend to be super early adopters of new technology. So actually, when we look at our products like AI Studio, and I'm sure Aziz will tell us more about AI teammates, which I'm actually even more excited about than AI studio those tech customers are, in many cases, the initial buyers of those products. And so I think the tech vertical, although it remains a headwind today, it's smaller overall as a proportion of the base. And I think what is a headwind today can actually ultimately become a tailwind for us as we look ahead.

So I think it's certainly not a story of doom and gloom. And 2 of the really large renewals that I talked about in Q2 that renewed in Q3 were very large tech companies and one was a large tech as large a CRM company that you could think of. And the other one was HCM software, extremely large company. And not only did they renew flat, they were expansions. So great for NRR, too.

Yes. That's really helpful color because there's been a number of high-profile tech risks of the late. So I'd love to hear what you guys are hearing from your customers in terms of seat expansion activity and some of the trends that you're seeing there, perhaps is that now these companies have been through a number of rightsizing activities such that companies are just leaner in terms of their software spend today overall than before. But why despite some of these headlines like is that not a concern potentially?

Yes. So one of the things in the tech vertical and nontech vertical as well as we haven't seen customers come back for a second downgrade. So we're not seeing them come back for a second button to Apple. I think the second thing is we've seen utilization across the board go up. So we're a lot healthier in our customer base as well, more well utilized. And then the third thing is we've become a multiproduct company. So we have a lot more mitigants and the levers to offset downgrade pressure if they do have layoffs and need to reduce seats to introduce AI Studio to automate the workflows in the existing seats to introduce a paid services plan, which we call foundational services plans into the account to increase utilization and drive better adoption. So we've actually seen with our FSP plans 20% higher utilization for those customers who are taking up those offerings. And so that's really encouraging for future retention.

So a lot more mitigants and levers in place to offset that. Now that we're a multiproduct company, we're not as dependent on seats. We're also driving a lot more deeper adoption of workflows, whether that be just rules-based within Asana or turbocharge with AI Studio. And when you're adopting those workflows, we're opening up to new use cases, new budgets. So that also diversifies us from seats and a reliance on seats, and it's going to open up over time a new revenue stream with consumption. So a lot more there over the past year as we've introduced new products and been really maniacal about driving better adoption and utilization of the platform.

Yes. That's really helpful, and I appreciate all of that color. Another highlight of the print, which you talked about for those smaller customers that you saw a high in terms of gross retention. Now I know that area has been impacted by some of the SEO disruption and top of funnel disruption that we've seen from some of the changes with the rise of AI search. I think you also made comments on the call that you've seen quarter-over-quarter improvements in that.

And month-over-month.

And month-over-month. Yes. So can you maybe talk about what initiatives Asana put in place to mitigate some of that impact? It sounds like it's still a headwind today. But is there a period of time as you look ahead that you think you'll start to see that really lessening?

Yes. So it's been a real focus of how do we mitigate that impact and take what's been a headwind and greater tailwind over time. So first, it starts with kind of our paid media and our marketing channel strategy. So we've diversified to be in more places where LLM is an AI search are sourcing their content and making their recommendations for us. So moving paid media spend to channels like YouTube and Reddit and Quora to be more visible. How do we structure our content with metadata and formats that are more visible and adaptable in an AI world, so things like webinars, ROI calculators, case studies, the metadata underlying that content. So how do we get picked up in a much more leveraged way.

And then the other big area is just like -- so now we're driving higher intent traffic, we see higher conversion from that. Like how do we compound that with other things we can do in product to improve conversion. So PLG, and this is Dan has brought this to the table and a real emphasis on how do we reimagine the PLG customer experience. So we've actually broadened the new head of PLG, our CPO is now kind of accountable for the PLG business. So that's really led to a lot of great changes on the in-product experience, how do we get our customers so that first like Dan calls it aha moment early in their journey where they're seeing value and they're finding that feature or that ability to set up Asana in that really effective way. And that's really helping kind of when they come to the website, when they get into a trial and then post trial to keep them retained because as suddenly said, that monthly base can be pretty churny, especially early on, if they're not, finding a way to leverage and harness Asana and how it's intended to be.

So a lot of good news on the channels we're in, how we structure the content and then when they're getting the site, getting the trial, getting the product creating that world-class experience for them so that they stick can stay and expand.

Can I just come over the top for a second? Yes, it continues to be a headwind, a headwind that we have reflected in our guidance. So we fully -- like we started talking about it, I guess, 2 quarters ago, but the Q4 guide very much reflects the fact that it will continue to be a headwind for the rest of the year.

Okay, perfect. That was helpful color. On -- you talked a bit earlier that part of the offset, even if you are still seeing some headwind to seed expansion is adding in these newer products, right? So you talked about AI studio. I know in the past, you talked about foundational service plans and more in implementing that into deals. So can you just give us an update in terms of adoption so far? I know there was some color on the call that you gave, so maybe you could recap that for the audience. And when you include those services into these deals, what kind of uplift do you see on that?

Yes. So I think the comment we made on the call around AI Studios continued strong momentum. So our sequential -- our bookings in the quarter were sequentially greater than the bookings in the last quarter. So continue to build that ARR base in a nice way, still small relative to our overall base, but scaling aligned to our internal expectations. We've also turned on self-serve for now a full quarter and seeing good adoption with our self-serve base.

As we think about how that plays into the overall deal structure, it does accrete deal sizes. That depends on the size of the renewal or size of the land. But can be anywhere from -- sometimes they both eclipse the deal size to a small fraction. So it is an important contributor, but I think the thing that we really are excited about is when they're adopted and used and people are building workflows or increasing their utilization of the service plans, it makes them stickier and increases the likeliness of them expanding seats over time. So we're getting that benefit on larger lands benefit of downgrade mitigation, benefit of expansion, but we expect to see longer term that contributing to our NRR expansion. So it's really exciting, and we're really excited about adding Teammates to that mix.

Yes. So let's talk about Teammates because I know that, that's like an exciting offering that's coming up and we're approaching the DA dates for that. So Teammates is the AI agent offering. You've had AI Studio, which is no code workflow automation. Can you talk a little bit about like how you're positioning both of those products? Do they complement each other? What are the big use cases, which customer segments are they geared towards? How should we just think about that opportunity overall?

Yes, absolutely. So we went beta with Teammates. We announced the beta launch at our marquee customer event, Work Innovation Summit in London, New York, just about a month ago in New York. So already 30 customers are in the beta. So this is like real production customers with real use cases. Morningstar, which is a really important customer of ours is using Teammates for their marketing content creation around campaigns and have already seen processes that took 2 to 3 weeks to execute, be willow down to like handful or 2 of ours. So really, really powerful stuff.

And so AI Studio and Teammates are highly complementary. So if you think about AI Studio, it's really about automating and supercharging workflows, so like reliable, structured, repeatable workflows, multistep processes. Where in that -- those multistep, you have agents built in, we call them nodes who are executing a part of that multistep handing off to a human in the loop, they're checking, iterating and it's going back to the node. So where Teammates secure complementary is now the AI Studio agents can hand off to a teammate within that workflow and that team can hand off to another teammate or back to a human. So they fit into that workflow structure really well where AI Studio is that backbone and the Teammates are coming in and helping automate within that platform. Just right alongside a human in that process.

And then the other cool thing is they don't have to operate in the workflows. They can operate autonomous from workflows. They can help you set up your Asana instance in a way that maximizes impact and value for you. They can start automating tasks. So we have -- that are persona-based or function specific. So we have different Teammates that we've rolled out, including a marketing campaign analyst, a ticket deflection analysts, a data intake analyst, a project management analyst who can sit alongside a human and execute those tasks as a true kind of physical worker. And they're all built on kind of what we call the 3 Cs, which really differentiate the Teammates and AI Studio, which is context. They're pulling from the context of the work graph, who, when, what, why, how, which is really that data store model that's a differentiator for Asana.

So they have the context to be effective, to be accurate, to be cost optimized and then the controls and checkpoints. So being able to give the right access controls, the right governance that humans in the loop. That's a real differentiator because you don't want the agent is off doing anything. And going to different projects that they may not really be privy to.

So really powerful, great feedback from just 30 customers thus far, really encouraging. It will be a bigger driver next year, certainly, the second half after it goes GA, and we build pipe and awareness.

Yes. And any -- I know it's still early, right? You mentioned 30 customers that are in beta testing for it. But any early signals that you guys can draw on how that might compare to what you saw with AI Studio? So is the opportunity for Teammates as big as AI Studio? Could it ramp similar? Or how should we compare those two?

Yes. So that's a great question. I mean, as I said, they're highly complementary, which I do believe, but I actually see Teammates, we see Teammates as being even a larger opportunity. Because I think in many ways, Teammates kind of democratizes building these workflows. Like what we found with AI Studio is that the early adopters certainly were those customers that were already using Asana for fairly sophisticated use cases and building workflows, using rules, building multiple workflows like truly like our power users, whereas I think Teammates just democratizes it. And it's -- Dustin won't like me for saying this, but it's like AI Studio for dummies, like the Teammates can actually help you build the AI Studio workflow.

And I think Teammates is much more general applicability. And the other thing about teammates is they are more consumptive in terms of credit. So I think in terms of like ARR ultimately driving kind of net bookings, I think it will actually be -- it will be incremental, but also like a larger opportunity. And going after, I think, in some ways, like different budgets, different use cases, use cases that perhaps like were not classic Asana use cases. And that I love and because it's taken us into like new TAMs.

And on that piece about the new TAMs, right, and it's taking into you to areas that you historically haven't competed in, I guess, how is the competitive landscape evolving off the back of that? So when you have customers that -- I know Teammates is still early, but when they are looking at Teammates when they've evaluated AI Studio, who typically are they comparing those solutions to? Is it DIY? Is it other SaaS solutions, maybe AI native? What does the competitive landscape look like there?

Yes. So I wouldn't say that we've seen a big change in competitive landscape. In general, it tends to be the other CWM provider. So the ones that you call like the Mondays, the Smartsheet, the Air Table, Click-up Rike. Monday is who we see more than others. I think what we have, we do feel it's truly differentiated. We do feel like we have a sizable lead. We think we're unique in that. AI Studio and Teammates sit on top of the Work Graph and that context awareness is unbelievably powerful. And kind of the fact that we have that -- we have this horizontal application, whereas I think some of the competitors are more siloed in vertical. So we do feel like we have like differentiation edge lead.

And the other thing I would say is AI Studio and Teammates, although were -- they're being introduced this year, they have been many years in the making, like this was part of Dustin's original vision. And I think these products truly bring our category into its own and into like going from a really nice to have productivity tool to almost mission-critical because we're all going to have agents running around our organizations. People need to know like who's doing what by when, including those agents. And Asana can help with that. So we feel like this will actually extend our lead in terms of product leadership and competitive differentiation.

Yes. And then in terms of how the pricing model is evolving off the back of this. I know this is a question that you guys get commonly where historically, the model has been tied to seats and seat expansion. And now with the introduction of AI that's changing. So could you comment like where -- obviously, we're in the early innings, right? But how are you guys thinking about monetizing AI and where that might go?

Yes. So I think currently, AI Studio is a platform fee where you get an allotment of credits. And then when you work through those credits, you kind of buy more credits. So it has a very consumptive angle to, but it's not pure consumption. And we found that customers right now and how they're rocking AI and leveraging AI, that's some model that they can really get their arms around. It has a little bit more visibility and transparency into costs. and it's easier for them to adopt and create budget around. And so we've had success with that.

Now there's a lot of learning in terms of like what's the right price per credit and how do we think about that. And so we're learning a lot but how our customers are using the product and what value they're driving and that will evolve. And I think we're thinking about teammates in a similar way for right now. But over time, you could see that evolve into a pure consumption. It's just how our customers evolve and when they're ready for that. I think right now, it's kind of early to go that far.

Yes. That makes sense. And then in terms of how AI is contributing to revenue today and where that could go, I think the original ARR number that you disclosed, I think it was $20 million, right, about a quarter or 2 quarters ago?

I don't think we ever disclosed that. What we said on ARR for...

No, I think we said -- so it came out in Q1. We doubled sequentially in Q2 and then now we've grown incremental bookings and in Q3. So not that big yet, but growing, but off a small base. So more meaningful as we exit Q4 and into next year.

Yes. And the way I described it today in meetings because that's a really natural question. And yes, we were just actually during the meeting saying like maybe we should disclose it separately. Right now, what we've committed to do is to give you updates at key milestones. But the way I think about it is although like when you're close were $800 million ARR company, like for a new product to actually make a difference as a percentage of your ARR take time. But to make a big difference or to become a meaningful contributor to the net bookings you're driving, like that, I can already say, like it will be a significant and meaningful contributor to our bookings, our net new bookings for fiscal '27.

And Aziz made the point earlier, like -- and I think you also talked about how it ramps because, of course, like the first quarter, you're going to get just the early adopters. But by Q4, like it's a much larger proportion of the base. And I think we feel the same way about AI Teammates. What we saw with AI Studio, which was this consistent accelerating ramp. I think with AI Teammates made we get that in fiscal '27. So the larger impact is in the second half and Q4 as we exit.

Yes, because I think some of the math that we ran was that on an ARR basis exiting this year, could maybe start to add a point to growth and knowing that that's going to be revenue growth in the future. I guess the source of the question is, is that if the core business is stabilizing, and AI now is going to start to become this incremental tailwind, is this potentially setting us on up for a growth reacceleration? So maybe just talk even at a high level, does Asana have ambitions to see growth elevated even further than where it is today? And if so, would be the building blocks potentially to get there?

Yes. So that's a great question. And I see now how you mean -- I did talk about like it being 1 percentage point additive to growth. So I see where your math was potentially coming from. But -- so one, yes, we do have ambitions to and we believe that we can without any time. I'm not putting a time frame on it, and I'm certainly not guiding, but we do believe that we have the potential with the products that we have and the large opportunity in front of us. to be able to reaccelerate growth and continue to drive margin expansion.

What I would say is like you've heard us talk about how excited we are about these new products and the incrementality, we do have headwinds that we're combating that we called out in the earnings call. And like I'd like to be super transparent about those. And we are continuing to experience those headwinds in the small business, PLD business with top of funnel, which we are navigating and the pressure is abating, but it is still there and remains a headwind. And we also still have exposure to tech. And although that has stabilized, the pressure in that segment, it is still declining. So that continues to be a headwind.

So I think when you take it all together, the picture is one that is we're feeling encouraged by, but we're certainly not willing to commit to a time frame in terms of when that reacceleration could happen. But I think the building blocks are there. I think we have a great team in place. I think our products are truly differentiated. And like it's the first time our sellers will be able to go into renewal conversations and actually have another thing to pull out of their cats to put in front of customers, and it's something that is so powerful in terms of the value and outcomes that can drive for customers, we feel really excited and I guess what we're investing behind it, too.

So you haven't asked about margins, but we drove significant margin improvement. And part of what we're doing is taking those dollars and those efficiencies and reinvesting them in our AI platform because we do think that there's runway to grow.

Yes, that was going to be my last question to ramp it up is how we think about the margin trajectory from here? Because I know the comment that you gave on the call last night was obviously, there's been tremendous expansion this year. So and expect the same level of expansion, especially as you try to reinvest to ignite growth. So could you talk to, because there was such a great expansion this year, where still are the incremental opportunities? And I guess even just as you look out, how do you think about balancing growth and margin and what the appropriate levels could look like going forward?

Yes. So you're absolutely right. I kind of tried to carve back expectations for another 12% year-over-year margin improvement. And I don't think that's what anybody would want. It's not what's right for the business of our stakeholders. So there is more to do. I think 2 areas. One is just the footprint of our headcount. When I first arrived at an extremely large proportion of our head count was San Francisco, New York. And for a company of our scale and financial profile, that did not make sense. So that's something we started to tackle. And that has a couple of benefits. One is for every engineer that attrits in San Francisco, you can probably hire 2.5 in Warsaw is our center of excellence for R&D. But the other thing -- the other great thing is those engineers that you hire in Warsaw, they don't necessarily have the same expectations around stock-based compensation. So you didn't ask about that, but that's something that is like top of mind and top of agenda for us as we look ahead.

So I think there's more to do in terms of that like footprint of our headcount. And we should be align ourselves to industry benchmarks there. And although we've made improvements and progress, there's more to do. And secondly, on the sales and marketing side. And I think marketing, in particular, something that stood out to me. I think it's one of the reasons that Dan was the right CEO for us because he brings a lot of expertise in marketing, but just reallocating those marketing dollars into more efficient channels will be a big unlock as well.

So look, there is more margin improvement to come. But when you talk about balancing growth and margin, like I would -- any day, if you ask me, would you rather a point of growth or a point of margin. Like at this point, we have such great operating leverage inherent in the business. because we have these 90% gross margins that like I would take a point of growth. And that, in many instances, means we'll be reinvesting some of those efficiencies. But I think that is the right model and the right strategy to be driving.

Totally makes sense. Well, Sonalee and Aziz, thank you so much for the time, and everyone let's give them a round of applause for taking a flight after earnings and making it to the conference. So appreciate it.

Thank you.

Thank you, guys, and thank you all for joining.

Thank you for standing by, and welcome to Asana's Third Quarter Fiscal Year 2026 Earnings Conference Call. [Operator Instructions]

I would now like to hand the call over to Eva Leung, 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 Third Quarter Fiscal Year 2026. With me on today's call are Dan Rogers, our CEO; Anne Raimondi, our Chief Operating Officer and Head of Business; and Sonalee Parekh, our Chief Financial Officer.

Today's call will include forward-looking statements including statements regarding the expected release and benefits 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 revised full year guidance, strategic plans, our market position and growth opportunities and our capital allocation strategy including our stock repurchase program, among other items.

Forward-looking statements include 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. Reconciliations 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 Dan.

Thank you for joining us today. This was a solid quarter. We believe the future of work is one where humans and AI collaborate with the right context, controls and checkpoints. That's the foundation of AI Studio and our newly announced AI Teammates and customers use these capabilities in production and are already delivering real productivity gains. I'm excited to share more about our AI platform in a moment.

But first, let's turn to the financial highlights from the quarter. Q3 revenues were $201 million, growing 9% year-over-year, exceeding the high end of our guidance. We generated non-GAAP operating income of $16.3 million or an 8% operating margin, also exceeding the high end of our guidance. Our margin improvement reflects disciplined cost management and a thoughtful reallocation of spending towards high leverage areas while still preserving capacity to invest in our AI platform. Free cash flow was also strong at $13.4 million in the quarter or 7% on a margin basis. Overall, NRR was 96%, a slight improvement across all cohorts from last quarter even with a heavier volume of large, predominantly tech renewals this quarter.

Retention within our monthly customer base is at a 12-month high, reflecting the work we've done to strengthen customer satisfaction and in product experience which Anne will share more about in a moment. We expanded with some key customers this quarter, including one of the largest multinational entertainment companies in the world, two of the largest Fortune 100 health care service providers and several large tech sector customers, including a Fortune 500 [ PeopleCloud ] platform as well as the leading AI data platform. AI Studio delivered another good quarter with solid growth in sequential bookings, including early traction with self-serve users.

I want to highlight two AI Studio wins that demonstrate how customers across industries are already using our platform to modernize mission-critical workflows. A global premium glassware manufacturer serving hospitality and luxury brands worldwide is using AI Studio to modernize core marketing workflows from campaign management to rapid content generation. One of Europe's largest and most influential trade show operators is now leveraging AI Studio to digitize their planning processes, streamline cross-department collaboration and accelerate decision-making on major strategic programs, including the OKR rollout.

Asana has pioneered three waves of work transformation: Collaborative work management, workflow automation and now AI transformation. These form the basis of our strategy to help companies on their journey to the agentic enterprise, unlocking productivity for teams as they deliver against their goals, smarter and faster.

So let's take a closer look at each of these waves. The first wave was all about solving the most fundamental challenge in modern work, creating clarity and accountability for a company's work. For many of our customers, work was once scattered across e-mails, spreadsheets and disconnected tools. Asana created the structure and visibility teams need to stay aligned and accountable with our collaborative work management platform. Powered by the Work Graph, teams now have a shared understanding who is doing what by when, how and why.

The second wave is centered on workflow automation. Once teams had this clarity, they also wanted to increase their velocity. Asana's no code workflow builder, makes it simple to standardize and automate repeatable processes from marketing intake to engineering sprint planning. And to make it easy, we created a workflow gallery to let you launch any workflow instantly. So teams get to value in a secure, fast, context-aware way.

Now we're entering a new wave with AI transformation. Every customer I speak with sees the immense potential, but the reality is many AI projects today are just not delivering. In fact, a recent MIT report said as many as 95% of AI pilots are failing to deliver on their productivity promise. Why is that? Our point of view is that a lot of the AI solutions and applications today lack three fundamental things.

Number one, they lack context. If you think about the foundational models, they understand very little of the work that's actually getting done within your organization. They don't have the memory of how things have been solved in the past. They aren't properly informed so they can't be accurate or effective.

They also lack checkpoints. AI can't be trusted to just run an end-to-end process without having humans in the loop. But these checkpoints today are nonexistent in many of the tools.

And finally, they lack controls. What we see and what I hear from executives is that AI agents often have more access to data than the employees themselves. Employees are carefully given things like role-based access control, this somehow doesn't translate to the agents that they have in their organization, which, of course, is a risk.

This is exactly what Asana's AI Platform is built to solve. As a platform for human-AI collaboration, Asana delivers the context, checkpoints and controls that enterprises require. The context is really the who, the what, the when, the why and the how. Context is king. If you want AI to be useful, it needs to understand how was this solved in the past, who was involved, who needs to be involved next? What approval process do we need to have? Thanks to the Work Graph data model, Asana can give AI this rich and relevant context. And you also need these checkpoints. It's our strong point of view that humans need to be in the loop on most of these AI processes to approve things and course correct if needed. In Asana, you can check the quality of AI's work and iterate with it so that it will continue to improve. And finally, unique controls. We have a strong belief that AI agent should not have more access to data than your regular teammates. They should follow the same governance process, the security controls, the access to proprietary customer data that you've already established. These are the 3 Cs, as we call them, context, checkpoints and controls are the foundation of our AI platform.

Built on that foundation of context, checkpoints and controls, the first AI add-on product we introduced with AI Studio. Think of AI Studio as supercharging your workflows. I like to think of it as inserting nodes in a given workflow to consult those foundational models, but doing so in the context of that workflow and the context of that work. It allows you to insert AI notes directly into the process to handle specific tasks.

For example, an intake node can check an incoming request, see if it's missing a due date and assign it back to the request automatically. A triage node can analyze that request against your company's goals and flag it as high priority. A quality node can check a deliverable against a predefined knowledge base to ensure it meets specifications. A risk monitoring node can proactively flag when tasks are falling behind schedule well before they cascade and a translation node can automatically convert content for global markets and routed to the right local teams. This is our first step towards enabling agentic enterprise, ensuring smarter, faster delivery of your goals.

Which brings us to the next strategic step in building a genetic enterprise, enabling AI not just to coordinate work, but to do the work alongside your teams as a true collaborative teammate. In our Work Innovation Summit events in London and New York, we announced Asana AI Teammates and we're already receiving strong positive feedback from our initial set of 30 beta customers. We expect AI Teammates will be generally available early next year.

Asana AI Teammates are collaborative agents to help you deliver real business outcomes. They remember, take action and adapt with full context on projects, goals and how your teams operate. They show their work and have built in checkpoints, so you can course correct. And with our AI Teammates, you are always in control. And we've already built out 12 out-of-the-box teammates across engineering, IT, marketing, operations and PMO. These aren't prototypes or demos, they're prebuilt, tested and ready to deploy. Each Teammate operates with full context from the Work Graph, clear checkpoints for human guidance and enterprise-grade controls. Marketing team mix that manage campaigns and create content, PMO teammates that track projects and flag risks, IT teammates that triage tickets and optimize resources. Customers can also build their own AI Teammates in minutes by defining the role, connecting it to the right data sources and refining behavior through checkpoints. This makes agentic AI accessible to every team, not just technical teams.

So what makes our agents different? Well, first, they have context, powered by the Asana Work Graph, they understand from the moment they are assigned how your work gets done, how you solve problems before and exactly who to involve. That context allows them to be truly collaborative because they understand the work, they can actively drive execution alongside people and the team. And crucially, they are multiplayer by design. Our teammates published their plans openly. This creates a shared transparent starting point where everyone can provide feedback, ensuring that AI learns from your team's collective input.

The early response from customers has been positive and reinforces the opportunity ahead. Morningstar, an early adopter of Asana AI is leveraging AI Teammates to tackle complex strategic work that requires deep analysis and human-like reasoning. By creating a specialized AI Teammate, the product management team was able to complete tasks that normally take up to 2 weeks in just 10 to 12 hours. Level Agency has built AI Teammates for marketing to act as a workflow accelerator saving 3 to 5 hours per content project as well as for IT to help triage support tickets and company-wide to intelligently review and operationalize new process ideas.

We're also using AI Teammates internally at Asana, our product design and engineering teams use a Figma and Cursor teammate to convert prototypes into production-ready UI-code in roughly 15 minutes, with more than 90% accuracy. Our brief body teammate supports every marketing kickoff and removes about an hour from the start of a project. And our marketing team's localization teammates achieved roughly 90% language parity by about half the cost, allowing us to reinvest savings into SEO and global growth. These examples reinforce that agentic AI is not theoretical, it's already improving how we run our own business.

Across all these deployments of our AI products, trust is central. Teammates only see the data they explicitly granted access to. Admins control who can create or modify them and customers have full visibility into the usage and cost with the ability to set limits to ensure strong ROI. We built these capabilities into AI Studio and Teammates from day one because enterprise adoption depends on governance as much as capability. This focus on enterprise-grade AI as the foundation of our strategy.

But in addition, operational priorities I laid out last quarter remained consistent and our Q3 results show clear, measurable progress against them. First, as I shared last quarter, when we go deep in a vertical, speak their language of their persona and align to the core workflows of that industry, we win.

I want to highlight this playing out in a meaningful way. For example, in the health care vertical, where we closed several marquee expansions this quarter. One of the largest health care and insurance organizations in the U.S. expanded to more than 3,000 seats and crossed the $1 million ARR threshold. They standardized their clinical service intake across a 20,000-person business unit and are expanding into adjacent teams like analytics, pharmacy and student health, all running mission-critical workflows in Asana.

Another major diversified health care company now well above 1 million ARR with us embedded [ Asana ] deeply in their Medicaid organization to support the creation and expansion of Medicaid managed care plans across local markets.

Asana is also being adopted across many new teams and a global pharmaceutical leader selected Asana as a preferred PMO solution, including for mobile clinical trial workflows, an innovation model designed to expand trial access to patients far beyond traditional sites. These health care wins are a testament to Asana's ability to adapt to industry-specific solutions with ease.

Second, we're improving go-to-market execution and value realization across our sales and self-service motions. We believe our focus on customer health improvement initiatives is contributing directly to the continued improvement of NRR. We delivered our strongest retention in more than a year amongst monthly self-service customers, an encouraging signal that our self-service engine improvements across product experience and support a take and hold.

Third, we're maintaining our focus on disciplined, profitable growth. Our significant improvement in non-GAAP operating margin and strong adjusted free cash flow are direct results of this discipline. Our operating leverage and continued commitment to driving higher productivity from our cost base gives us the capacity to keep investing in high leverage areas, especially our AI platform, all while expanding our margins.

Next quarter, I look forward to sharing additional proof points customer stories and outlining the FY '27 priorities that I believe will support long-term growth acceleration and continued margin expansion.

Before I hand over to Anne, I also want to take a moment to share that Anne will be leaving us Asana after 7 years. I'm so grateful for all that Anne has done and has played a major role in our story. First, as a highly engaged Board member and then as our COO and Head of Business, where she was instrumental in building an enterprise go-to-market motion and serving as one of our most trusted customer voices. I personally want to thank Anne for her leadership, partnership and the foundation she's helped shape across our product customer and field teams.

As we look ahead, given our size, scale and the need to drive tie to alignment across product, product-led growth, sales-led growth and marketing, our go-to-market leaders, including the CRO and CMO will now report directly to me, and we will not be backfilling the COO role. This structure strengthens our ability to move at speed and focus and it best positions us to accelerate growth over the long term and capitalize on the large and growing opportunity we see in leading the market for human AI collaboration. I'm grateful for everything Anne has done to help us get to this point and wish her the very best.

With that, I'll turn it over to Anne.

Thanks so much, Dan. It's been a privilege to spend the past 7 years helping build Asana, first in the boardroom and then alongside the team every day. I've loved this company from the start, and that hasn't changed. I'm proud of the progress we've made building a true enterprise-grade platform and deepening our relationships with the most innovative customers around the world. I want to sincerely thank the entire Asana team for their incredible passion and dedication. I'll continue to be a strong advocate for Asana and a dedicated Asana user. I genuinely believe that the foundations are in place for the company to lead the next wave of work centered around AI human collaboration and to define how teams work for years to come. That progress was evident again in our Q3 results.

In Q3, our enterprise motion continued to scale. The number of customer net adds from the 100,000-plus cohorts grew 15% year-over-year while core customers spending $5,000 or more grew 8% year-over-year. International markets remain a strength for our business, especially EMEA and Japan. Our international revenue grew 12% year-over-year, and the U.S. market grew 7% year-over-year.

Here's an example of that. We landed a new multiyear competitive deal with Guardian, the British-based global news organization to consolidate their tech stack and improve cross-departmental collaboration. Asana was chosen over competitors for its flexibility, enabling teams-like product, advertising and group technology and data to streamline everything from agile road mapping to resource capacity planning on a single platform.

We continue to increase our presence in non-tech with those sectors once again growing in the teens. Dan noted some of the momentum we saw in health care, and I want to call out two other important areas where we saw meaningful wins this quarter: financial services and the public sector, both key growth verticals for Asana.

In the financial service vertical, we expanded with a large North American financial services company. Their goal was to cut marketing campaign execution time by 25% to 50%. Their existing intake process had 29 steps, and they needed a single system that could simplify workflows, automate handoffs and improve reporting. After evaluating Asana against our peers, they chose Asana for its superior user experience, flexibility and ease of adoption, requiring minimal training while still offering the customization needed to modernize their workflows.

We also saw strong momentum in the public sector this quarter. including a meaningful new win with a major German government research agency that manages roughly 6,000 projects each year. This was a competitive win. They selected Asana for its ease of use templates, workflows, Work Graph-driven OKR support and enterprise-grade security. They're implementing Asana as an audit compliance system to manage thousands of research and innovation funding projects across Germany and Europe. Asana gives them real-time visibility into project progress, budgets, team allocations and much more.

We're also seeing sustained momentum in our channel ecosystem with partner attached growth for the third straight quarter and consistently higher NRR in accounts where partners are engaged. The global biopharmaceutical customer win that Dan mentioned was secured in partnership with a global SI partner.

We also landed key new logos with partners at a leading automotive manufacturer in India, a major U.K. food delivery platform and a global enterprise digital experience platform. While the tech sector continued to be a headwind to our growth this quarter, we successfully renewed with several large tech companies, as Dan noted. This is one of the key factors impacting NRR improvement quarter-over-quarter.

Core customer NRR and 100,000-plus customer NRR both improved 100 basis points to 97% and 96%, respectively. In quarter NRR improved across all cohorts. Enhancements in our support infrastructure, improvements in customer satisfaction metrics and AI-driven onboarding for self-serve customers resulted in our lowest churn numbers from monthly customers in the past year.

In our SMB business, we continue to be affected by the evolving top of funnel dynamics we mentioned last quarter, particularly in relation to LLM driven changes in search and paid media investments. Our approach to mitigate these pressures focuses on three areas: First, we're building modern self-serve experiences that get users to value fast. Our new prompt to project flow take someone from a prompt on our website to a working Asana project in seconds and we're optimizing each stage of the buyer journey to turn that engagement into durable growth.

Second, we're evolving our content strategy and technical foundation to maintain authority as AI-led discovery changes, strengthening our presence were LLMs train and ensuring Asana shows up as the leading answer in our category.

Third, we're implementing smarter behavior-based personalization for high-propensity accounts to improve both acquisition and expansion.

As we shared last quarter, we expect these headwinds to persist through Q4. We concluded the quarter with our marquee customer event, the Work Innovation Summit in London and New York where we officially introduced AI Teammates to the world. Across the two events, we had over 1,600 customers, partners and analysts in attendance. Our sponsors included Google, AWS, KPMG and Deloitte. The strategic impact of these events was immediately clear from the response from third-party experts. We held over 30 industry analyst briefings with one analyst noting, "No one is doing agentic like Asana, that's what makes you best in class." This is echoed by another industry analyst who called our multiplayer human plus AI collaboration approach "unique" in the market. These global events are a critical component of our go-to-market motion. They are driving new business, strengthening executive relationships and validating our strategy as a leader in agentic AI. According from one of our financial services customers, "The event was one of the most stimulating engaging conferences I've been to in a while. Asana's application of AI is like no other company today." Another Fortune 100 multinational mass media and entertainment customers said, "I love that this event was focused on helping me get more out of what we're already doing, which inspires me to want to buy more." We are energized by this feedback and the validation of our strategy.

With that, I'll turn it over to Sonalee to walk through the financial highlights for the quarter.

And I want to thank you for your partnership and everything you've brought to Asana. I'm grateful for the support, clarity and customer focus you've helped instill across the business. You've had an enormous impact on the company and so many people here.

Now let's turn to our financial results for the quarter. Q3 revenues came in at $201 million, up 9% year-over-year, which exceeded the high end of our guidance by almost 1 percentage point. We have 25,413 core customers or 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 Q3. We have 785 customers spending $100,000 or more on an annualized basis and this customer cohort grew at 15% year-over-year. As a reminder, we define these customer cohorts based on annualized GAAP 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%. As a reminder, our NRR is a trailing 4-quarter average and therefore, a lagging indicator of more recent trends. Our in-quarter NRRs improved across all cohorts. The $100,000-plus cohort had the largest improvement amongst the cohorts. Q3 in-quarter NRR increased mostly due to improvements in downgrade and expansion, thanks to our multiproduct strategy and seat reach. While we have more work ahead, I am encouraged that Q3 marks our second consecutive quarter of in-quarter NRR improvement. While Q4 includes several large enterprise renewals that are concentrated in our technology vertical, we believe that we are at or near the floor and the initiatives we have in place position us for continued NRR improvement over the intermediate and long term. This continues to be a key area of focus and we believe the initiatives in place on the retention side and the expansion opportunity with our AI platform set us up for continued improvement going forward.

Now moving to profitability where I will be discussing our non-GAAP results. We continue to be extremely focused on driving efficiency and productivity throughout our business, maximizing the operating leverage we enjoy from our strong gross margin at 89%. We expect to maintain these levels of gross margin in fiscal year '26 while expanding operating margin as we continue to scale.

We continue to make meaningful improvements in our operating expenses as a percentage of revenue. R&D expenses were $47.3 million or 24% of revenue, down 14% year-over-year. Sales and marketing expenses were $86.5 million, or 43% of revenue, down 3% year-over-year. G&A expenses were $29.1 million or 14% of revenue. As a result of driving productivity and efficiency gains, we delivered an 8% operating margin or $16.3 million of operating income in the quarter, which is a 12 percentage point improvement year-over-year.

Net income was $17.9 million or $0.07 per share on a diluted basis. Our profitability improvement continues to be driven by operating leverage, reallocating spend to the highest ROI go-to-market motions, optimizing infrastructure and cloud costs and exercising discipline across discretionary spend. We are also aligning our talent footprint with industry benchmarks by shifting certain roles to more cost-effective regions, creating a strong foundation for sustained efficiency and multiyear margin expansion.

Moving on to the balance sheet and cash flow. Cash, cash equivalents and marketable securities at the end of Q3 were approximately $463.6 million. Our remaining performance obligation, or RPO, was $500.9 million, up 23% from the year ago quarter. Current RPO will be recognized over the next 12 months and was 77% of RPO and grew 15% from the year ago quarter. Our total ending Q3 deferred revenue was $305.1 million, up 8% year-over-year. Building on our operating margin strength, Q3 adjusted free cash flow was $13.4 million or 7% on a margin basis.

We continue to take a disciplined approach to capital allocation. Given our strong balance sheet, positive free cash flow and confidence in our long-term strategy, we believe share repurchases are an effective way to return value to shareholders while offsetting dilution. This quarter, we bought back $30.8 million of our Class A common stock or 2.2 million shares at an average price of $14.10 per share. As of October 31, we had $97.5 million remaining for repurchases moving forward.

Now moving to guidance. For Q4 fiscal 2026, we expect revenues of $204 million to $206 million, representing 8% to 9% growth year-over-year. We expect non-GAAP operating income of $14 million to $16 million, representing an operating margin of 7% to 8%. And we expect non-GAAP net income per share of $0.07, assuming diluted weighted average shares outstanding of approximately $244 million. For the full year, we are updating our revenue guidance to $789 million to $791 million, representing 9% year-over-year growth from $780 million to $790 million previously. Currency is about 40 basis points growth benefit to our full year guidance, 10 basis points less of an impact from what we guided last quarter. We are raising our guidance to incorporate our actual Q3 results.

SMB continues to grow at a healthy double-digit pace. Though, as Anne noted earlier, we are seeing top of funnel pressure given the evolving search landscape, which we expect to be a continued headwind to our small business growth in Q4. These dynamics are fully reflected in our updated Q4 and full year fiscal year '26 revenue guidance.

On a non-GAAP basis, we expect full year operating income of $52.5 million to $54.5 million, representing an operating margin of 7%, up from our prior guidance of 6%. We are reinvesting a portion of our Q3 operating profit outperformance back into the business, primarily in our AI platform and product development initiatives. As a result, our Q4 operating margin guidance reflects the impact of this reinvestment as we support the road map and build toward long-term growth acceleration. In addition, we expect non-GAAP net income per share of $0.25 to $0.26 assuming diluted weighted average shares outstanding of approximately $243 million.

Across the leadership team, we're aligned on the priorities that position Asana to lead in the Agentic enterprise and accelerate both growth and margin expansion over the long term. AI Studio momentum continues to strengthen, and we believe scaling our AI platform with Teammates will be a major driver of durable growth.

And with that, operator, we're ready for questions.

[Operator Instructions] Our first question comes from the line of Matt Bullock of Bank of America.

First, I wanted to ask about AI Studio, specifically the self-serve launch. Anything you can share in terms of early learnings from that launch. Any feedback in terms of ARR contribution from the self-serve launch? And then separately, I would love to hear more color on the influence AI Studio is having under renewals this year, given that it's the first renewal cycle you guys have had being a multiproduct company.

Matt, it's Anne. I'm happy to answer that. In terms of AI studio self-serve, we just launched that last quarter, and so we are -- what we're pleased with is just the wide adoption and customers really trying it out, customers of all sizes, including those that you regularly buy self-serve from us. So that's the good news, is it just really democratizes access to AI Studio and people get to try it and actually get value out of it. So we're continuing to watch that and watch consumption on that. It also gives us signal and the sales team signal on where to call into the self-serve signals in corporate and enterprise. So excited about that and continue to watch that.

You asked a good question about renewals. I think AI Studio has been a real help in renewal conversations. One, it's strategic, there's just more for us to sell to customers, and we're really helping to advise them on their AI strategy overall. So we're pleased with how that's been helping renewals. And then four customers that have bought AI Studio and what we're really paying attention to is adoption and consumption. And so getting as many use cases implemented as possible having them see real value. So those are how we're monitoring everything around AI studio.

Our next question comes from the line of Steve Enders of Citi.

Okay. Great. Thanks for taking the questions here. And Anne, great to have worked with you and best of luck on the -- on your next adventure there. I guess just to start, I want to ask on I guess, within the tech vertical specifically, and I think there's been some, I guess, further high-profile layoffs in that space. I guess what is it that you're seeing that's maybe giving you confidence that we're -- I guess, near a trough there, are things are going to improve? And just how are you kind of viewing the impact of that into Q4 and maybe into the next year?

Yes. First, I can answer your question on -- we do see tech vertical stabilizing. It does remain an overall headwind to us. But there is a few important dynamics worth calling out. First is we don't see a follow-on downgrade path with those tech customers. Once they're downgraded once, they tend not to downgrade again. And that's a meaningful shift. So in fact, several of our largest tech customers this quarter actually expanded as they renewed and logo churn continued to improve. We also saw and certainly will touch on this later, I'm sure, a 12-month high in gross retention amongst our monthly customers.

And then we do see this nice and just kind of rounding out the piece here on AI Studio, a nice move for multiproduct, moving us off of seat-based products. AI studio and AI Teammates open up new budgets for us, new use cases, and they do create a strong lever to mitigate those seat downgrades. They also introduced a new consumption-based revenue stream where our foundational service plans and those drive deeper adoption and much higher utilization in our customers and making it even stickier and then as customers stick with us to do cross-functional workflows even more deepened by AI Studios that helps us expand into new budgets and makes us a lot more less dependent on employee count of most tech companies.

Okay. That's helpful. And maybe just to follow up, just to get a little bit more clarity on the 4Q guide, it looks like a pretty healthy rate here. And just kind of wondering maybe what's changed in your assumptions for Q4 versus how you were thinking about it last quarter when you provided the guide there?

Yes, sure. Thanks for the question. So four things I'd really call out that I'm seeing, which are giving me confidence this quarter to raise that full year guide. So the beat in Q3 was driven by consistent execution across most of our core pillars. So first thing to call out is enterprise strength. We saw a 15% year-over-year increase in customer spending $100,000 or more. And we're seeing stable demand trends in this segment and improvement in pipe conversion that is leading to productivity gains.

So the other thing I would just mention there is that whilst we don't typically break out our $50,000 to $100,000 customer cohort, we saw exceptional strength there this quarter. On the international side, that remains a strength for our business. So especially EMEA and Japan. So continued strength there. International revenues grew 12% year-over-year, outpacing our overall corporate growth rate, improving NRR. And I think this is really key. And you'll have noted like my commentary around this changed. So we successfully renewed with several of the large tech companies that I called out last quarter that were looming. This was one of the key factors that impacted our NRR improvement quarter-over-quarter.

Retention within our monthly customer base, as Dan said, is at a 12-month high and that reflects a lot of the work and investments we've made to strengthen customer satisfaction and the in-product experience, which you've heard Anne talk about over the last several quarters.

And then finally, AI momentum. So we saw continued momentum with AI Studio we saw sequential strong quarter-over-quarter growth. That's helping drive conversations with customers at renewal, which Anne just touched upon. So AI studio and FSP are leading to larger initial [indiscernible] expansion and mitigation of downgrade. So just a reminder, what I said in my prepared remarks, is that I'm really encouraged by the Q3 trends in NRR. And that was part of what gave me the confidence on raising the guide overall.

Our next question comes from the line of Josh Baer of Morgan Stanley.

Questions for Dan. Just as AI agents become embedded across probably most productivity tools, how should we think about Asana's competitive position there? I mean are you expecting Asana to be one of many agents that knowledge workers engage with? Or is it important for Asana to really become that orchestration layer that coordinates all agentic workflows across the enterprise. And if so, what really differentiates you, gives you the advantage to win that opportunity?

Thanks, Josh. I appreciate the insightful question. Yes. Look, here's how I would frame it. This is not going to be a winner takes all opportunity for agents. In fact, we will sit alongside many of the other Agentic players. But to turn to your question of differentiation, the way I think about it is, today, broadly speaking, the alternatives fit into three different buckets: bucket number one, single player copilots and personal assistants. Now they're great for personal productivity, they're very easy to pilot, they're great at doing lightweight individual tasks, but they don't scale across an organization. Each person is kind of building their own version, and that is leading to agent sprawl, context often say siloed and knowledge doesn't compound quality and costs vary by individual and no shared governance model.

Second approach we see or bucket 2 for agents which is point solutions and these are from some of the systems like CRM or ITSM solutions. Those are deeply integrated into tools that they're already being used, and so they're really good for structured workflows within their domain. But as you can imagine, they're limited in that narrow ecosystem. They don't address a lot of the cross-functional work or the unstructural work between the spaces and between the departments.

The third bucket is DIY solutions that people are really hacking and building directly on top of LLM providers. They're super flexible for experimentation, attractive for quick prototypes or bespoke workflows. But again, these seem to run into issues with governance, duplication, scaling costs, cross-team coordination and maintaining those prompts and controlling access and ensuring consistency all requires ongoing admin.

So at Asana, we take a completely different approach. Our AI platform has context, controls and checkpoints built in. So if you look at AI Teammates, these address many of those gaps because they operate as true members of the team, not just individual copilots. So if you think about all of the context that Asana has in our work graph, who's doing what by when, how and why, those are the key ingredients that's missing in those other approaches. Intelligence alone isn't enough, AI needs this rich context and rich workflows to be effective. But Asana also provides the checkpoints, review steps, permissions and governance models to prevent that sprawl and maintain quality and cost control at scale. And because AI Studio and AI Teammates work together in one system, customers get reliable automations that are repeatable for work as well as flexible agents for more nuanced judgment-based work. So this is all about that overhead that we talked about on those DIY agent solutions or without the limitations of some of those functional silos of CRM and [ IJSM ] native tools. The result is an AI layer that actually scales across teams and not just within them.

The next question comes from the line of Rob Oliver of Baird.

Great. Anne, I also wanted to extend my best wishes to you, and it's been nice working with you. Dan, my question is for you just around the channel ecosystem and some of the momentum that you guys called out there. Partner attached growth being strong again. Can you give us some sense for where you see kind of the partner ecosystem currently as someone who has a background with a lot of companies that have pretty advanced partner ecosystems. Where is it today? Kind of what inning are we in? Where does it need to be? And where in particular are you guys seeing that traction today? And then I had a quick follow-up as well for Sonalee.

Yes. And Anne mentioned, we're hot on the heels about London and New York with summits, and we had the opportunity to do partner breakouts of both of those, and I couldn't be more excited about our channel ecosystem our product and our category lends itself very well to the channel. And so I see nothing but opportunity for us in building out that channel ecosystem. As I talk to many of our partners today, they just want to do more they want us to be more consistent in how we help them to be successful. And so I do see it as a true ecosystem and partnership where we help ensure their success and not just a transactional channel for us. So very excited about the partner opportunity, and I think we're at the early innings of it.

Great. Very helpful. Appreciate that. And then Sonalee, just for you, obviously, a lot of work has been done by you and the team on the cost optimization side, infrastructure, cloud, and just was curious, I know you've been reallocating kind of stuff around the organization to try to drive higher ROI. But when it comes to those costs, how much more run rate do we have on that? Have they been optimized? Is there more to go? If you can give us a flavor for what might be left, that would be great.

Yes. So the work is definitely not done. Thank you. Appreciate your support, but there is more margin upside to go for. As we think about the remainder of this year, fiscal '27 and beyond. So growing profitably continue to be a key focus of this team with continued emphasis on geo mix benefits, in terms of where our head count sits, vendor rationalization, there's more to do there. productivity improvements in sales and marketing, which Dan has been very focused on, and that will allow us to continue expanding margins sequentially and for multiple years to come.

That being said, we are balancing margin expansion with reinvestments in our AI platform to sustain our product leadership and to accelerate growth. Both our priorities but we are investing alongside expanding margins to support that revenue acceleration goal. So if you think about fiscal '27, we will build off our exit margin in Q4, which you see how I guided today. The only thing I would just caution is don't expect the same rate of margin expansion in fiscal '27 as you saw in '26. But I think that's well captured by consensus today. But by no means is the work done.

And the other thing I would just say is we are reallocating spend and what we're doing is reallocating to areas where we see higher ROI. So that should have an overall benefit to operating margin.

And then the final point I would make is just our gross margins continue to be in the 89% to 90% range. So just the operating leverage that we get as we continue to grow in scale, we'll continue to play through and have a positive impact on margins.

Our next question comes from the line of Jackson Ader of KeyBanc Capital Markets.

The first question, it's really nice to see the retention rates picking up. And it sounds like that was due to lower gross churn. But if I think about revenue growth slowing just a little bit, should we read into this to mean that maybe the expansions or the upsell of existing customers was more muted than it has been in the prior quarters?

Jackson, it's Anne. I'll take that. Yes, I do think what we're pleased with is the improvements we saw in downgrade. And then as Dan mentioned, seeing some good expansions in some of our large tech renewals. And we really are investing in the multi-strategy -- multiproduct strategy approach. So in some cases, what we're seeing is that because we've got FSP and we've got AI Studio, what we're able to do is drive a flat or slightly uptick in renewal but both of those are great for future retention and expansion. And so that's really where we've been making the investments as well as on the monthly side. So a large portion of our base is still monthly customers, and that retention has been at a 12-month high. And so that's a lot of the work that we're doing both in customer support and in product experience. So both of those levers in terms of what we can sell to larger customers as well as continue to make sure the monthly base is healthy, I think will ultimately lead to healthier retention.

Okay. All right. Got it. And then a quick follow-up. Certainly, it was this time a year ago, your first call with the company. And you said the goal -- I can't remember exactly, that Asana could do both, right? You could both reaccelerate revenue and also expand operating cash flow margins. I think on the margin side, like pretty clear what you were just talking about with Rob, absolutely delivered. But if we think about revenue acceleration, coupled with that margin expansion, is that still doable? Is that still the goal, the expectation as we kind of head into 2027 or even or beyond?

Yes. So without guiding to fiscal '27 because I always do that in March. What I will say is that we are early innings on our new product strategy, our multiproduct strategy. And I believe that AI Studio and AI Teammates are going to be the key unlock in terms of driving that growth reacceleration. We, by no means, have given up on that, and it is absolutely this team's strategy to continue to do both. And I am strongly encouraged by what I saw on the NRR side. And if you think about NRR, if we can even drive it a couple of points, you're looking at a very, very different growth profile, a very, very different financial profile. And I didn't -- when I put the comment in the prepared remarks about being at or near a bottom, I didn't put that in lightly. What's giving me confidence is the data that I'm seeing underlying the Q3 trends. So its second consecutive quarter of in-quarter improvement. I don't know if you remember, but when I saw the first quarter improved, I said, one quarter does not make a trend. Well, two quarters certainly gives me a lot more confidence.

Secondly, what a couple of us have called out on improvements in gross retention, that is across the board that we're seeing. And then the multiproduct, it's early days. And I talked about the impact of AI Studio being small for this year. But as we look ahead, and when I think about the contributors to our net bookings for fiscal '27, AI Studio and AI Teammates will play a much stronger role there. So you can count on us to be delivering both for you.

I'm going to hand over to Dan because I think he wouldn't have taken the job if he didn't feel like he could do both.

Thanks, Anne. Yes, maybe I'll just add a little color. And the color really is around, look, number one, collaborative work management, our category is about to have its moment in the sun because of AI. CWM becomes the system of record for work, which means we've got the who, the what, the when, the where and why and how of the work. And that context is just great to make AI effective. And that's exactly why we launched AI Studio and why we followed up this quarter with the beta launch of AI Teammates.

Secondly, the PLG opportunity for us remains massive. Today, it's about 40% of our business and in an AI search and LLM driven world, we can double down on those high-performing channels with AI Search and really target our marketing dollars towards higher propensity customers. So we're optimizing that trial experience, and we continue to help customers to reach value faster.

CWM itself, this is number 3 is a large and growing TAM, and we have a recognized leadership position but our work here isn't done. There's a huge runway for us to innovate and expand the surface where work gets done and deliver even more value to our customers.

And fourth, and as Sona touched on, whilst we've made some progress in our go-to-market motion and efficiency, there's a lot more work to do. So I'll be focusing on everything from persona-based selling, tightening our execution and customer success, improving productivity through high propensity leads and routing across all of our segments to unlock the potential in our go-to-market motions. And finally for me, personally, my style is really about injecting tempo, which is about creating velocity for the organization, which is around faster decision-making, faster learning cycles, getting to beta faster and strengthening the operating rhythm of the company. So all of these will lead to an improvement in innovation and execution velocity.

The next question comes from the line of Patrick Walravens of Citizens Bank.

I'm going to change my question, Dan, because what you just said was super interesting. So I love the idea of increasing the velocity. How do you actually do it? Like how do you get everyone to run faster. We have all the code red stuff going on with Open AI and Google right now and so many people are commenting that just telling everyone to run faster doesn't mean it's going to work and sometimes, in fact, it backfires. So how do you do it? How do you increase the velocity?

Yes. And I'd say my -- fortunately, my prior experiences really were a training ground for velocity, high-tempo organizations executing at scale. And so it's how I drive myself but also the organizations. The first piece is around decision-making and ensuring that you have a tight way to make decisions quickly with the right people involved and the right information that you need.

The second is really a mindset or an operating principle around getting things to beta, and that is about launching new products, launching new capabilities in the knowledge that you're going to quickly iterate on them afterwards. And so it reduces the fear of kind of launching because you know that afterwards, you're going to rapidly iterate. If you think about our AI Studio self-service experience, this gives us a massive set of data points to continue to improve that product get it right to the middle of the bell curve. And then having the right operating rhythm so that everybody understands exactly what needs to be done by when and really kind of pushing the pace and the expectations around that with all of our leaders. Those are some of the things that we can kind of inculcate into the culture.

Great. And Sonalee, if I can just ask a follow-up. I mean, not with the time frame on it, but when you talk about multiyear margin expansion and this company is going to come up on $1 billion pretty quick. Where can the margins be? I mean can they be in the [ 20s ]? Where can they be?

Yes. So when I think about the margin expansion that we've been driving thus far, it all starts with that 90% gross margin or 89% to 90% gross margin and the inherent operating leverage there. So think about it. If we continue growing even if -- like I'm not going to guide, but just even a few year consensus, just if we kept expenses fairly flattish in many areas, you would still get consistent several percentage points of margin improvement every single quarter on a sequential basis. So there is no reason, in my mind, that we can't eventually aspire to be among the best in class in terms of enterprise software companies on margin. I always think we're the envy of many software companies with the gross margins that we have today. And even if AI Studio and AI Teammates mates take off the way we hope they do, and there's a little bit of pressure on the gross margin, there is still a ton of runway. So something with a two in front of it is certainly within the realm of possibilities.

Our next question comes from Arsenije Matovic of Wolfe Research.

So just thank you for the question. How did the large tech renewals in 3Q trend versus your expectations, given that heavier renewal volume in 4Q? Are you more confident in expansion and retention in 4Q than you were heading into 3Q? And is that also now reflected in the updated guidance? And just a follow-up.

Yes, I'll take the Q3 renewals and what we're seeing in Q4. So they did perform better than we expected, and we were very pleased by that. I think that's a combination of operational rigor on that as well as more products to sell. I think we're bringing that same approach into Q4. In Q4, while we have a higher volume of tech renewals, they're more midsized compared to the larger ones that we had in Q3 so continuing to make sure we bring that operational discipline as well as now with the launch of teammates, even more to sell and more conversations to have.

Yes. And I'll just add to that, just on the guidance side of things, when we look into Q4, even though we do have a large renewal base in Q4 as is typical, I would say I am more confident going into Q4 versus where I was when I guided on Q3.

Got it. And just to follow up on that. You did mention the four factors supporting that confidence as well, but still embedding conservatism on new business. So I guess can we just kind of unpack what specifically is supporting confidence in passing through, I think, double the beat in 3Q, even with that slightly lighter FX tailwind than you expected entering last quarter?

Yes. So net retention is a big factor there. So again, it's two consecutive quarters now of in-quarter net retention improvement. And then the gross retention improvement across all cohorts. And importantly, the 100,000-plus cohorts saw the largest improvement among them. So that was even with the headwind from that large customer downgrade that we called out in Q1, but actually impacted from Q2 and will continue to impact for the next couple of quarters. So the fact that in Q3, we managed to improve in spite of that, that added to my confidence levels. And then the multiproduct strategy and specifically AI Studio and the foundational service plans or FSPs, those are actively driving expansion and helping to mitigate downgrades and certainly have been extremely helpful in renewal conversations. And then there are the other items that I called out earlier, but we're seeing strength in other areas of our business, including new business. So the enterprise strength and that mid-market cohort that $50,000 to $100,000, we don't break it out, but what I can tell you is what I saw this quarter was a lot of strength there. International, I continue to expect to -- it's been strong for the last two quarters, expect continued strength. And then even in the enterprise side of the house, we saw 15% year-over-year increase in customer spending $100,000 or more. And if you couple that with stable demand trends, an improvement in conversion, which leads to productivity gains, you end up with -- or I ended up with a more confident picture as I look towards Q4 and the full year.

Thank you. I would now like to turn the conference back to Eva Leung for closing remarks. Madam?

Thank you, everyone, for joining the call. We'll be on the road attending the UBS and Barclays Conference this and next week. Looking forward to seeing all of you. As always, if you have any questions, please reach out to me at [email protected]. Thank you very much.

And this concludes today's conference call. Thank you for participating. You may now disconnect.