Atlassian Corporation ($TEAM)

Good to go. We're very excited here. First and foremost, I'm Tom Blakey, infrastructure software analyst here at Cantor. We're excited to have the Head of Investor Relations, Martin Lam here with Atlassian, which we think is an exciting buying opportunity. As a segue there, I'd ask Martin to maybe share with the uninitiated, what is it that Atlassian is trying to solve for customers?

Yes. Martin Lam, thanks for having me. So if you think about Atlassian, we're a collaboration company. Our ticker symbol is obviously TEAM. If you look at our products, it's really to plan and manage work. It's to help share knowledge at scale. And especially when you think about that future in an AI world, none of that really changes, right? You still have to plan, manage and track your work, whether it's humans or agents. You start to share knowledge across the organization, whether with AI or cross with humans, all that continues to be very relevant. And that's, I think, why we're really excited about our position in AI era.

One of the genesis of Atlassian was with developers as IT in general took over organizations, you were there in terms of managing those teams. Why don't you just maybe address the bogeyman in the room in terms of AI. Will we need less developers and how this is going to affect the Atlassian model maybe?

Yes. I think it's interesting, right? We have a strong heritage with developers, and that's where we got our start initially. That represents a small part of our business today. We actually look at even Jira, Jira's core user base. 50% of their users are technical. That includes basically developers, engineers and IT. The other 50% are nontechnical or general business users. So we already have a very diversified kind of user base. Everything -- everyone is focused right now on the development and how that continues to evolve. We think of this world where humans and agents are going to work side-by-side. Humans are always going to have to be in the loop. When you think about humans are always going to have to have an agency of directing what do we want these agents to do. What do we want them to build? What do we want them to accomplish? And then humans will have to have checkpoints of, did that agent actually accomplish what we wanted it to do. So there continues to be this role of humans and agents in the loop, especially even in software development. And again, tracking back to the point I made earlier, the role that Jira plays, I don't think that changes anything that level of criticality continues to rise because you need to be able to say, okay, did that agent actually build what we wanted to do? How do I track and manage all these different agents running across my business? Are they doing what we wanted them to do. Jira has always been this orchestration layer of tracking work and who's working on, what is the output. Does that actually ladder up to our company strategy in a world where there are agents in the mix, are those agents doing that? How do I track this increased complexity across my organization. And so again, I think that's a really exciting opportunity for us.

Along those lines, people are worried about seat growth, see growth. You commented on your last quarter, continues to expand. You even invoked the, I guess, the AI 50. Many of them are using your product and customers are expanding their seats even faster in that vertical. Just maybe talk to us about. You said you're expanding outside of developer. Your outside of the developer community. Talk to us about what's driving the seat growth?

Yes. Look, I think we continue to grow with those technical users and nontechnical users. So across both vectors, which is great to see. I think -- two things I would first share. It's like one, we look at those customers that are using these co-gen tools. So again, trying to address some of the fears out there. When we look at those customers that use a cursor that use a cloud code via MCP across thousands of customers, so not an insignificant number. Those customers are driving 5% more tasks through Jira. It's leading to actually 5% greater monthly active usage because to your point, more people have to collaborate to manage this increased complexity or throughput of work. And then ultimately, it's driving those customers to expand their seats 5% faster than those customers that don't use these co-gen tools. So it's really interesting. And again, it kind of backs up what we've always believed in, but we thought it was important to share with the market. And then number two, I think we get questions about, okay, what about these hot new AI start-ups. So we picked the nonsubjective list. The Ford's AI 50. I didn't want to cherry pick some stats. I just drew that over to my data science team and said how many of these -- the hottest startup -- AI start-ups in the world are our customers today? 60% are already our customers today. And they're all growing their seat counts much faster than the overall corporate rate, which is probably not too surprising, but again, it's like -- so we feel good about our kind of position in an AI world, especially even with these hottest companies that investors may have questions about. Hey, do you know those companies work in a different way? It seems like we're well positioned even with these companies.

Going back -- shifting back to the core, the non-AI 50, you guys have been making a concerted effort for a long time now to move upmarket with the enterprise. You saw RPO jump over 40% in the last quarter. Can you just maybe give us an update in terms of the -- I guess, the positive report card in terms of those moves with the 40% growth?

In this moment In time, I think some people would say, okay, our enterprises, maybe taking a beat to evaluate their investment options or evaluate, kind of, the vendors. If anything, we're seeing a lot of these enterprises vote with their wallets in this moment in time. So we saw enterprises grow their seat counts. They sign for larger dollar amounts, and they're signing for longer contract duration which showing the commitment to the Atlassian platform, showing that they want a trusted vendor to run their Agentic workflows on and a reliable platform that has context behind the type of work that they're trying to do. So the enterprise efforts are going great. The actuary report card that you referenced is the result of three things, I think. We've talked to in more recent times about three company priorities. And so it's -- and serving enterprises delivering AI and what we call the Atlassian system of work, which is moving more towards this collection strategy or holistic solutions as opposed to individual point products. So those three strategic initiatives are coming together, and that's kind of the combination culminating in the report card that you just referenced and that's driving great results right now. We want to continue to push ahead on those three strategic priorities. And I think those are going to be important ones as we drive more durable growth into the future.

It's good to see the buy-in view that RPO statistic. The -- sorry to keep addressing the boogie man, I think it's important because we've seen the pressure on software in general as well as Atlassian stock. So that's why this vector is a little bit more leaning this way. So from an AI orchestration and that orchestration layer you talked about with regard to the system of work and even the horizontal movements that you've had across organizations and successfully in recent years. You've heard some providers of maybe some of the apps you connect to talk about the orchestration layers that -- and not just Atlassian, it could be ServiceNow, it could be Microsoft becoming parasites, if you will, in terms of trying to connect to our data. Could you maybe, not to be provocative, but maybe address how does Atlassian get some of its data? How do you -- how would you view, like, Atlassian in that type of market where maybe there's an instance where one of the applications shuts off the connection to some of its data?

I think a couple of things to start on for those less familiar. Atlassian has 350,000 customers. We have tens of millions of users and we power a lot of hundred millions, hundreds of millions of discrete business workflows throughout the platform. And so that platform investment that we've made over the past several years is really important. It provides what we call the teamwork graph or a knowledge graph of understanding how relationships and kind of the context behind those relationships. What third-party tools are your individual teams utilizing. That's actually how we're able to surface, I think, very intriguing and compelling actions or use cases with our AI. We've always had an open ecosystem philosophy. That's no different in an AI era. Like we've always tried to be this coordination layer or a single pane of Atlassian coordinate, all your different workflows even when you use third-party tools because we realize that you're not going to be sitting in our platform. And so we've intentionally tried to stay away from getting too far into specific dev tooling or specific technologies because what's lasting is kind of the human problems of like, okay, human problems are going to be the more lasting problems as opposed to technologies, which come and go. And so we've always believed in integrating with best-of-breed third-party tools. Now those have come in and out of flavor depending on which kind of segment that you look at, but it's very important to tie in to these third-party tools. So whether you're in Microsoft Teams or Slack or Salesforce products, we want to be able to understand how those teams are working because that's the basis of the teamwork graph. In this new era, I think we're -- you're poking at. We still continue...

The market's poking at.

We continue to believe that the open ecosystem approach is an important one. If customers want to tap into Atlassian products, like that's going to be an important one because they should have that freedom to do so. We want to encourage that. What's important, when we look at the MCP data, customers are writing and editing within our products. That's an important aspect rather than just purely reading because that means that we're driving more and more workflows through the platform, and that begets more and more users to collaborate on those workflows and then that also drives upsell opportunity or upgrade potential. So we encourage that type of access into our platform. It is an area that we continue to monitor. I think we look at how the industry continues to evolve about how to maybe monetize this kind of access platform. But again, that open philosophy is a really important one for us. And philosophically, that's something that we believe in.

Certainly, it doesn't sound like you're seeing any issues in the market. So thank you for addressing that. And lastly, Atlassian has a number of drivers to growth. You talked about seat growth, talked about even subsegment growth, whether it be the AI 50. Another growth driver you have is moving folks from your data center segment which on-prem to the cloud. Maybe give us an update there in terms of what we should expect in terms of tailwinds? And we had -- we just had some tailwinds recently and maybe some future headwinds as we kind of move through this moving folks from data center to the cloud.

Yes. So today, we have two deployment models. It's -- we have our SaaS offering or Cloud offering, and then we have what we call the data center offering, which is an enterprise-grade on-prem deployment model. We announced the end of life of that data center deployment. And so those customers will have to move off of that by March of '29, so a little over 3 years from now. And during that time, we'll continue to migrate those data center customers to the cloud. That's an important aspect for us because the cloud is where the innovation is. Earlier, I talked about the platform. That's where the lion's share of the investment has been. That's where you have AI capabilities, that's where you have analytics, that's where you have automation capabilities. None of that's available on data centers. So it's really important that we migrate those customers to give them the best experience that they can get, which is going to be on the cloud platform. These are our largest customers, the data center cohort, right? Like these are the biggest or big enterprises, many of them who have been Atlassian customers for over a decade. Many of them have 50,000 users or more. And so it requires a little more handholding to bring these data center customers over. They have customized kind of footprints on their data center instance. So part of the challenge and an opportunity, of course, is how do we get them to rebuild some of that customization onto the cloud platform. That's why we know it's going to be a multiyear journey for some of these customers because they have to rebuild some of the customization on the cloud instance. How do we hold their hand through it with more kind of white glove service? Like these are all the different avenues that we've looked at. We have a program now called Fast Track, which is giving them a dedicated R&D resource to help them road map out the path to get to the cloud. That has accelerated customers' migration plans quite considerably. And so that's something that we're rolling out with larger scale today.

One of the genesis of Atlassian was with developers as IT in general took over organizations, you were there in terms of managing those teams. Why don't you just maybe address the bogeyman in the room in terms of AI. Will we need less developers and how this is going to affect the Atlassian model maybe?

So I think a couple of things to keep in mind is, again, the data center cohort is a much smaller pool of customers, but with much larger seat counts behind them. So that's the first thing that I would point out. I talked about it being a multiyear journey, I had to move these customers over to the cloud. You get varying levels of price uplift to that you're pointing at, depending on how many users the customer has. So on the low end of town, it could just be a cost neutral or 5% uplift. On the high end of town, there could be upwards of 2x the price. So it really depends on kind of the number of users that a customer has. We've been hesitant to give kind of a direct ratio to apply because of that varying level of complexity. But I think that's something that we're thinking more about how do we help investors understand the level of uplift. I think the commonality between all these though, is that because these are the largest customers, we do have a more traditional enterprise negotiation process with them. We want to ease them over to the cloud. So in those instances where they have more significant uplift. We want to smooth that path out for them. So in year 1, it may be less prohibitive and, therefore, make it more cost neutral for them, so more of a 1:1 kind of ratio in year 1. But in years 2 and 3, you start to peel back that level of discounting. So you slowly ramp them to that full list price over time. So you kind of actualize that price benefit in years 2 and 3.

Very helpful. Talking about some of the benefits of moving folks to the cloud and you get a lot more technology. You've rolled out just 9 months ago, the teamwork collection, maybe a lot of AI capabilities in there as well. So this is a segue for the audience. They just know now that you've moved to the cloud, you can buy things like teamwork collection. Maybe we have a brief definition of that? And what are you kind of seeing there in terms of drivers for this. I think you've reached 1 million -- over 1 million seats in less than 9 months. So there's demand there. And what are folks doing that on that?

Yes. So the teamwork collection, as you talked about, has only been in the market for about 3 quarters now. As we rolled out Rovo, our AI capabilities across our platform, you get a certain number of AI credits with your standard subscription. With teamwork collection, you get 10x the amount of AI credits relative to U.S. stand-alone Jira stand-alone confluence subscription. So it's very appealing for customers as they think about their kind of AI journey because when you talk to our customers, they don't want consumption base pricing, at least today for our products. I think it makes sense for certain other models. But for our products, they don't really want to pay on a consumption basis. So today, if you use AI credits above and beyond your allotment on your standard Jira subscription or Confluent subscription, then you start to pay us on a consumption basis. But again, if you upgrade the Teamwork collection, you get 10x the amount of A credit. So it's a way to kind of forgo that worry or monitoring of AI credits today. That's been the #1 driver of why customers want to upgrade or choose to upgrade the Teamwork Collection. A lot of success early on, it's our expectations. 1,000 customers have upgraded to Teamwork collections. It equates to 1 million seats sold. Those customers that have upgraded Teamwork collection have expanded their seats versus their stand-alone footprint on Jira by double or by more than 10 percentage points of seats expansion, which is great to see that drives additional kind of attach of Confluence in Loom and then ultimately, the 10x amount of AI credits. So there's a lot of compelling kind of package within Teamwork Collection.

Super exciting. Could you want to maybe share with us what you've seen some of your customers using with regard to AI, you talked about the product side. I didn't ask direct about Rovo. And just -- because I think a question that investors have are what are folks -- from a stickiness perspective, from a growth perspective, what are folks doing on the Atlassian platform where they are.

Yes. So we have over 5 million monthly active users of Rovo today, which is great to see. That has grown considerably over the past year. When we look at kind of the agent invocations as we call them or kind of business process automations, like that's been really encouraging because it's basically speeding up people's daily business processes. We talked about tens of millions of business processes flowing through the platform. And so to the extent we can speed those up, that's great to see. I think a really interesting one is of those agent invocations, 40% are within Jira Service Management. So it's clear strength within Jira Service Management of those service management Rovo automations.

Okay. Any questions in the audience by chance?

Just on the -- [indiscernible] the other side of the equation that's easier or not positive [indiscernible]. Can I have [indiscernible] are you using that over time? Or is that something [indiscernible]?

It's a great and very relevant question. So the question was in regards to stock comp, how do we think about that? Yes, I think we've been thinking about this very seriously for over 6 months now where there's a lot of energy around this. We take it very seriously. I think if we look at our stock-based compensation as a percentage of revenue, we are on the high side. I think we recognize that. We need to bring that down over time. So we're looking at different ways that we can perhaps modify our stock comp program, how do we distribute stock comp. Because it is an important part of compensation, but in perhaps a more disciplined way and do we look at different levels. Like these are things that we think have to think about as we move forward. And yes, like it's priority for us to kind of accelerate GAAP profitability. And so we hear you, and we think about this quite a bit.

Is that something that we should [indiscernible]? How does it [indiscernible] as but is it something [indiscernible]?

I guess I won't -- the question was like how do we think about timing on this? I won't provide a specific timeline. I would say there's different actions that we look at and how do we think about -- again, part of the balance is, of course, retaining and hiring key talent. So that's the balance of this all that we have to contemplate. I think two things that I would, I guess, play out. Number one is part of what's driven that is the significant hiring that we've done over the past several years, both in terms of investing in AI as well as building out our platforms, that's been central to our three strategic priorities. I think we've cracked the back of a lot of those platform investments. And so you're actually seeing us moderate the pace of head count growth and you're actually starting to see that play out. And so we're able to reallocate some of that R&D talent that's been exclusively focused on platform initiatives into other product-specific areas. And so that rate of hiring as that starts to moderate and slow, that should help in some regards. The other aspect, as we move into the enterprise that Tom talked about earlier is we've talked about R&D as a percentage of revenue coming down. Meanwhile, sales and marketing will continue to tick up slightly. Structurally, that should help. Now we'll always be R&D and product-led first. So those will never cross. But as they come down and come closer together, that should structurally help from the stock-based compensation perspective since R&D tends to be where that's concentrated. And on sales and marketing, you tend to not have to give as much.

That's helpful. And maybe jogs the question about, what did they say? Drinking your own champagne or reading your own dog food. Given you have these great AI tools and from a workflow management perspective and the new coding tools coming out. Talk to us about where you are in the journey of benefiting from AI efficiencies internally.

Yes. It's a top priority of ours across the company. So for R&D, I think that is where a lot of the focus is, but even within areas like HR, marketing, even within finance, we're looking at ways how do we continue to drive productivity with adoption of AI tools, our own products as well as third-party products. So actually really pleased with the adoption across the company, but you always can do more. Some of it is just change management, right? Like there's a lot of exciting capabilities available. I have a lot of agents today at my disposal that I've built, but there's always opportunity for more. So it's taking the time and thinking kind of creatively about where I can apply agents into my daily work life and kind of speeding up processes, which would have taken me longer from a manual perspective.

Interesting. You have your own agents. I like that. But from a journey perspective, are we early...

Still quite early.

I guess everybody is quite early.

Again, a lot of it is just thinking about how do we reinvent certain workflows to utilize and leverage AI. I think, like one of the interesting ones is we get asked a lot about our R&D team, right? Are you using some of these co-gen tools? I think what people miss is coding is only about 30%. We do surveys. You can look at third-party surveys. Coding's only 30% of the developer's time today, hands on keyboard development time coding time. So where we try to apply our AI capabilities is on that other 70% as well. Like how can you speed up some of the other 70% of what they do in collaborating, how do you figure out what we're trying to build? On the whole, we use cursor. We use cloud. We use a lot of tools, Rovo dev in the mix. Kind of the net-net of that is our developer is about 25% more efficient, which I think shows there's a lot of opportunity.

Yes. And you addressed the 70% too, so that could be your secret sauce. You mentioned like shifting some dollars from R&D to sales and marketing, that's a part and parcel to the enterprise initiatives that you've started and are being early successful early on with. Talk about some of your channel endeavors, too. I think Atlassian is a multifaceted growth story to me, there's the DC to cloud. There's the new channel initiatives, there is the enterprise movements? Does the seat growth even still that nobody wants to talk about. So this would be the fourth or fifth. I don't know what number am I. On the fourth row of growth opportunities for Atlassian. And maybe again, share some history with the team, with the audience about how dependent you used to be on the channel, and where your kind of initiatives are.

Yes. The channel plays an important role for Atlassian's go-to-market effort. So today, the channel touches about 50% of our revenues. So they've kind of -- many of them have grown up alongside us. However, many of them have also driven a lot of their business purely by just reselling Atlassian products. And as part of the evolution that Tom was poking at is, we're trying to evolve channel from just purely reselling Jira seats, adding your licenses into the mix to more value-added services. So we've been trying to paint the opportunity for our partners of hey, there's actually a significant dollar size just as much dollar opportunity, but you have to earn it in a different way by value-added services. Some of it is actually pretty compelling from a change management perspective, AI adoption perspective that we just talked about. How can that help our customers be more successful? Especially as we push more into the enterprise, some of that relationship may be more direct with us as we grow our quota-carrying sales force.

And so we've -- I think I've asked you this before, Martin, so I apologize, has there been like any like size of appropriate -- can you put a number on what you think that the benefit to like the longer-term sustainable growth of this company could be from those channel initiatives? Because it is a large piece of your business, over 50%. The channel speaks very highly viewed. So -- but is there -- for the reason you're doing it, is there a calculable number that you think that, that can be added to the sustainable growth rate from moving some of these from account ownerships in-house. And managing the reselling of extended cloud service?

The evolution with the channel is a multiyear journey as well, right? Some of these channel partners are a little more resistant to the change. Some partners are much more on the forefront and they've been adapting actually even ahead of us announcing some of these channel initiative changes. And so this will be a multiyear journey with them, again, as they more move into value-added services. I think of this as this benefit that you're pointing at is kind of a multiyear process plan.

Any more question from the audience?

[indiscernible].

So the question was, do we see the need for different -- or new products into the mix evolve into this Agentic world. I think we'll look hard at how our customers are using products. I think like actually one exciting development with Jira that we just announced, I think, 2 weeks ago now is the ability to assign work to agents directly in Jira. That includes not only our first-party Rovo agents, but third-party agents as well. So for example, we're working on something, and I say, let's spec out and drop the product specs. You can assign that to a sigma agent today. You can sign that to a Rovo agent today. So that, I think, is an exciting step back to that point that we talked about earlier of you still need to track and manage where all this work is happening. And even if third-party agents are doing some of that work, you still need a place to track all that complexity, especially with -- as this continues to grow. And so I think that's an exciting aspect of Jira placed as kind of this pane of glass of tracking where all those agents are doing and what are they actually working on? And are they actually delivering the results that we wanted.

I know I only have 15 seconds left, but I'd like to maybe ask about the M&A strategy. We get a lot of questions from investors, relatively acquisitive at the end of last year, some cool companies like the browser company. Maybe just kind of update us on the M&A strategy and where there maybe are some more holes in.

I don't know if I can do that 15 seconds. Two sizable acquisitions last year for us, DX and the browser company of New York. So DX is a product that is kind of a natural product to cross-sell into our software team or software collection, as we call it, where you can measure the ROI of different AI tools that your teams are adopting. You can see where kind of the bottlenecks start to appear within development process. So it's a very valuable tool, especially in this moment in time. But even beyond this, like understanding, especially as teams get more efficient at perhaps the coding aspect, where is the next bottleneck in their development process. The browser company is a very different type of product and very strategic approach. I think most of you probably do most of your work in your browser today. So we can envision a world where you can offer a lot of compelling AI added to features into the mix, especially when you think about all the different SaaS applications that you have in the tabs across your browser and how can you string together different context across that? How can you provide compelling AI capabilities by pulling in data from those various tabs in the browser that most of us sit in all day. So that's typically the kind of the first port of entry into a lot of our daily work. And so I think that's actually a pretty compelling possibilities that we can give to our customers.

You did that well in a short period of time. Thank you so much, Martin. Thank you for coming.