Atlassian Financial Analyst Day - May 6, 2026

Thank you, Martin. Good morning, everyone. Good afternoon. Sorry, it's morning where I'm from. That's my only excuse. Good afternoon. Thank you for being here. I hope you all had a good morning this morning. Did you all attend the keynote? Just so I know what I have to replicate. Okay. Well, this will be way more fun. Don't worry.

And thank you. It's good to see so many familiar faces. I should say that. As Martin mentioned, we're coming off a very strong quarter. We total revenue 1.8 billion, 32% year-on-year. Cloud at 1.1, 29% year-on-year. RPO passed 4 billion at 37% year-on-year. I'm sure you all know those numbers as well as I do. But a really strong quarter, another chapter in our story. It is an example I would say at the highest level of our three strategic pillars: the enterprise, the AI, and the system of work all coming together. And I hope over the three or four presentations today you see how those continues to thread together and lead to that strength and growth as we have shown continually.

But as Martin said, it's not about that quarter. We want to spend time talking a bit more about the longer-term story and what that means because underestimated, misunderstood, all these things that you said, I think it is totally true. There is a big disconnect I believe in how we are seen and what we are actually delivering. And so I thought we'd go through some of those doubts and give you a lot of facts and figures and other things to go through those. So, you've probably familiarly heard a bunch of the AI is going to make devs redundant. We only serve devs. Seat growth is going to die. Seats are going to disappear. AI agents are going to make everything less critical. People going, I don't know, make their own SaaS by themselves, make their own operating system. They'll probably make everything. AI native startups are going to just kill everybody. We don't have the right monetization model. I'm sure you've heard some version of all of these things. Let's go through some of them.

Fundamental problem I would say is that's very much looking backwards, right? That might be looking at Atlassian 10 years ago and assuming we're a static company. We've never been a static company. We've probably always been underestimated and misunderstood. Awesome. Bring it on. The platform we built, transformations we're delivering. I hope we're showing you every quarter that we are delivering the numbers that we say we're going to deliver. Durable growth that you can see in those numbers. I do think it misunderstands our runway going forward and we'll try to give you some indication on that. Let me tell you what Atlassian's about. Granted, in real numbers. So, I know a lot of you, despite being extremely smart, struggle to model Atlassian. You see a bunch of apps and you usually talk a lot about Jira and Confluence, although I still don't know how many Confluence questions we've had in any earnings call. I think I've said this a couple years in a row. Like, it's still amazing to me. So, we'll get to that in a second. But Jira and Confluence is not how Atlassian works. It's really not how we work, right? We are building a singular platform. As you now see, we have all five collections. And plenty of companies claim to have a platform. Most of them, I would argue as a technical person, do not have a platform. Not like we do, right? We have a single platform that delivers a single system of work that continues to compound and multiply the more collections and apps that you have on top of it. It delivers a common way to do things through the flexibility for an organization. And the value is in not the data, but the graph, the ontology. We will spend a little bit of time talking about that. And that's why I'd argue we're becoming an operating system for work for a lot of the world's largest companies.

Customers are increasingly committing on a platform level. Brian will go through that. We have more and more platform-level committed customers. I've talked a bunch even this week that are making even greater commitments to us, which feels excellent. It's a justification of all the things that we've invested in. As they add collections, they deepen their investment in us.

It also makes our AI smarter. I hope you say that. We'll have a lot of slides on. I'm sure there'll be at least a couple of questions on AI as we get there. Now, one of the reasons that our growth is so durable is that it's incredibly diversified. So, we told you in our shareholder letter last week, the service collection has passed a billion dollars ARR and is continuing to grow at 30%. That's ARR, not even revenue. Now that's just a service collection. Confluence by itself has passed a billion and a half dollars in ARR. Jira is passed two and a half billion in ARR. So, we've built multiple billion-dollar businesses, all of which work on a single platform, which is really important for our customers that serve every industry and every team from finance to HR to IT to software teams to designers. And that is an incredible set.

And people keep asking well how did Jira and Confluence keep chugging? They must be slowing down right and it's not the case today. Jira and Confluence are accelerating as we have said in the cloud. And it's because of the platform right we serve more and more workflows and business processes which I think people greatly underappreciate. Right? With the teamwork collection people aren't buying point products anymore. They're buying a collection of things that work together that are part of the platform. And that's a massive signal for us as we've shared over a thousand customers. That was a quarter and a bit ago I should say that was in previous quarters results and more than a million seats in the first six months. So those are some really really strong numbers but the point is diversified business multiple large businesses all of which are growing very strongly. And again, the collections make it easier to expand. The changes we've made from a set of products three years ago to the apps and collections that we have today working on a singular cloud platform make it easier for customers to consume our software. We have less things for them to buy with far more value. And part of the reason we're seeing that runway ahead of us for durable growth and the growth we're seeing today.

Now, you can see all of this diversification playing out in our numbers, right? Customers aren't just buying in, they keep expanding. So, let me give you an interesting chart. I think it'll be interesting for you. Let's look at total cloud seats excluding all migrations, no migrations involved. And despite the oh seat-based it's going to disappear, can get out your rulers if you want. I know you do. You can see visually it's not slowing down. It's a pretty amazing curve. Again, this is excluding all migrations. Cloud seats, they continue to grow every quarter, every year. Durable growth as we talk about. Why? Because workflows continue to get more complex, more intertwined. Teams and companies are buying more into the Atlassian platform and getting exponential value as they increase their commitments. That's really important. And we think that only keeps accelerating from here. Teams start orchestrating the AI agents alongside their people. You heard me talk just a little bit this morning about the teamwork graph. I think we have more ahead of us that we can continue to do because of our investments in that platform.

Now you might be asking okay they're adding those seats but seats for whom? Right? This is where the old narrative I think breaks down. People pigeonhole Atlassian as a developer company. Now I might argue there's going to be more developers in the AI era. I think that's going to be true, but fine. You think we're the developer company, or some people do. We love that heritage. I will say developers are awesome. Technology and business teams working together is the core of what we do. We think developers are incredibly important to the future of every single large business on this planet. Technology is the core strategic advantage of almost every single big company that you will talk to. If not, they have some sort of regulatory barrier, etc. But the growth we're seeing hasn't been driven by developers for a long time. The system of work is for the entire company. It's for finance teams. It's for HR teams. It's for marketing teams. It's for operations teams and service teams. When we talk about assets and buildings and laptops and everything else, we're talking about far more than developers. We're powering hundreds of millions of workflows every month. Now, you've heard us talk before about how half our users are not in technology teams and we've got a half technology, half non-tech business. We shared that before. So, how about this one instead? Break it down and let's look at developers versus everybody else. Knowledge workers in Confluence. Seven out of 10 users for that one and a half billion dollar plus business that's growing well very well in the cloud. Seven out of 10 of our users are knowledge workers non-developers. In Jira Service Management it's over three quarters. Even on Jira it's roughly two-thirds of the users are non-developers. That's HR and finance and legal and marketing and operations staff and design. We spent two decades connecting these business teams with their technology teams and we have a lot more to do. Again a different way of showing that we are a well diversified durable growth business.

Now let's look at the customer segmentations. So when you're embedded across that many teams inside a company, customers are expanding. And how do we see that? Well, we talk about having 350,000 paying customers. We know that that's the bottom of this kind of pyramid illustration. How about at the top end? So, our million-dollar customer base, which I believe we said a quarter and a bit ago, had passed 600 customers spending more than a million dollars a year. That has grown sixfold in the last four years. In the last year alone, it grew at 39% year-on-year. That category, these customers have more than a 99% retention year, and they are almost all expanding. If we look at our $3 million cohort over the last four years, when we talk about the enterprise investments we've made on the technology side, on Brian's side, that $3 million cohort has grown tenfold in the last four years. 54% year-on-year in the very last year alone. And we have quite a number now of those $10 million plus ARR customers. These are ARR numbers as well, not revenue numbers.

Takeaway I want you to get is we're not a nice-to-have tool. We are part of how these organizations run. We are a strategic partner. That has been our goal as we've said in every shareholders letter for the last four years. That is our enterprise goal. We've been working on the enterprise for a decade now since data center launched a decade and a bit ago. And I think that's reflected in the movement of our customer base. So the top end of the pyramid is going very well. The important part is we have an awful lot of customers in that bottom end of the pyramid who are moving up there. So the platform works, customers stay, they expand, they deepen their commitment to Atlassian. Natural question is but do you have all the businesses? What is the runway? So we've updated all our SAM numbers. The way we've recalculated it now updated the calculations is that our SAM is about $140 billion. We have a lot of runway as a simple thing to take away from this. See it broken down by different collections and other bits and pieces there. So there's a lot ahead of us and then the question naturally is well how do you go after that? How does that actually happen? So we've broken out these four growth levers which are the ways that we grow typically right expanding inside the customers we already have. Those million-dollar customers have become $3 million customers become $10 million customers that started as $10 customers. That is expanding inside customers we already have. When we move to new groups inside those companies, we don't count them as a new customer. They're the same customer that we've always had. Most of the customers you'll hear from today, and I'll show you some examples in a second, have been with us for 20 plus years. I routinely speak to customers who've been with us for more than two decades. None of them are spending less than they were two years ago, let alone less than they were 10 years ago. And their commitment to Atlassian keeps growing. We obviously cross-sell across our portfolio. Show you some stats about that in a second. But we obviously have far more apps I think you can see across the moonrise than we have ever had in collections. Upselling into new value tiers as we've added the premium and enterprise tiers in the cloud. And of course winning brand new customers is still something that's greatly important to you to us.

When we look at that 350,000 customers across the globe, they're in literally every industry on the planet. I have spoken to customers in every single one of these industries in the last maybe quarter at least year every single one of these industries and for every single one of these industries they're driven by technology. But the technology and business teams connecting together is how they're trying to win in the future and that's exactly where we sit with our platform and it's a massive number but we have barely scratched the surface of the opportunity in most of these accounts. How do we know that again we talk about the Fortune 500 that are already Atlassian customers 85% of them but again representing only 10% of our business today and I think we're only just past 10% very recently. We have a huge amount of growth in that Fortune 500 cohort alone.

But the headroom inside all the other companies we serve is massive. We are in the European equivalent of the Fortune 500, the Australian equivalent of the Fortune 500, the Asian APAC equivalent of the Fortune 500. So across the global enterprise landscape, we have a huge amount of runway ahead of us. How do we know that in terms of those knowledge workers? Well, if you look at the billion knowledge workers on the planet, about 900 million of them are outside of technology. About 70 million technical knowledge workers and about 30 million of them are in development. Call these order of magnitude rough numbers. There's various surveys. They all end up about this sort of proportionality. If you think about the fastest growing segment of our customer base, which is that non-developer audience, we have an awful long way to go with our tens of millions of users today to that billion dollars. So, a few different ways you can think about our potential. And again, when we land a new department, we don't add a new customer. Just two, three months ago, we landed a 200 person marketing organization that had never touched Jira in one of the 10 largest companies on the planet. What was important is those 10 largest companies, they said they had never used Jira. In fact, one of the people said, 'I didn't know this was Jira. I thought this was someone else.' I won't say which competitor. And that was awesome, right? That was amazing. And then when they use it, they're really happy. Why? Because it connected to their technology team. They almost literally repeated our core mission back to me in a meeting. And it was a truly amazing moment. So massive opportunity ahead of us.

We do have significant cross-sell opportunity just in the Jira base. So how do I keep illustrating this in different ways? Here's a different way to look at it. If you look at the Jira base in the cloud, 150,000-ish customers call this a sort of a round number. And again as I said before Jira is growing extremely fast in the cloud by itself. So this number keeps going up. However, if you look at service collection as an equivalent it's only 65,000 odd customers. There is a huge runway just if service collection did nothing other than sell to the Jira base right that's over... should have done maths before my coffee what is that 80,000-ish 85,000 Jira customers where service collection is not attached today that is a huge number when you look at enterprises around the world and these are only significant customers I would say so the reason is 150,000 I've excluded a lot of the smaller ones and stuff like that so they're of size let's say. But those aren't cold conversations. When Brian's team go in and say, 'Look, your teamwork collection is going really well. Let's talk about the service collection and you've got the same data, the same platform, the same teamwork graph.' That's not a cold conversation. That is an amazing conversation. Part of the reason why the service collection continues to take share, and do really well in a lot of those increasingly in the enterprise and strategic segments.

I talked about upgrading editions. This gives you some interesting statistics on where we were. So if you look back five years again, this is Q3 number. So not quite the end of FY26 yet, but roughly a five-year period called four and a half to five years. You can see that our mix here has moved from the standard premium enterprise we had five years ago to where we are today. It's an example of our enterprise journey continuing. Now I drew this chart for you so it was illustrative on the left to the right. The right-hand bar obviously in quantum is far larger than the left-hand bar. We have far more customers than we had five years ago. But just as a proportionality, it shows that our customers are increasingly opting for premium and enterprise as we continue to solve scale, security, regulatory, compliance and other issues that they can opt into. At the same time, the standard continues to grow well because we get that broad base of millions of companies around the world.

How big is that broad base? Well, there are about six million companies roughly that we would estimate are in our target market, right? That aren't Atlassian customers today. We have a few hundred thousand free instances in businesses of any significant size. So, again, we're not talking about a one-person instance, someone's created as a test, etc. Excluding that. So, it sort of shows you where some large amount of opportunity when you look through those different things.

So we talked to the system of work, a growth, lots of opportunities. I thought it would be helpful if I broke it down into some actual customer examples. So this is real world customer data I've anonymized. Neither of these are two customers are coming to talk to you today. There are two examples of thousands of customers that I could pull out literally that show a multi-year journey. So I'm going to start with a global auto manufacturer, 100,000 plus employees, very big company. Let's look at their journey over 15 plus years with Atlassian.

This is a bit of an eye chart. So, let me walk you through it for a second. If you see the line at the bottom, the first line is their time on server for those who've been with us for a while. The second line is their time on data center. And the third bit of the line is their time on cloud. So, they're on cloud for the last five years. They spent three or four years on data center and what is that, six, seven years on server. So, they moved our deployment options over time as this example of a customer. They've been with us for 15, 16 years at this point. And you can see at the very bottom what applications they've bought. You're always asking where does all the R&D go? Well, here is a good example of where they've built things that we didn't have and they've bought things that we didn't have over time. They're now sitting... Oh, and I should say at the top. Sorry, it's probably the most important part that I missed. This is obviously their ARR in millions of dollars at the top. So, you know, they were at 1 to 2 million five years ago. They're now sitting what is that sort of eight to nine. Maybe nine and change. Sorry, my eyes aren't that good anymore. But you can see as they've moved where those jumps in revenue relate to their movements. So you can see when they moved to data center it moved from what was actually an exponential chart for the first five years. It is actually exponential for the first five years. It's just you know the left-hand side they're probably spending five grand 10 grand like near you can't see the bars. Move to data center they're getting to the 50 to 100 grand. They get to the million dollar in data center range. Then as you see as they move to cloud they continue to ramp up. We've talked a lot about why that is but it's fundamentally they have many more things they can buy. Their expansion opportunities their expansion speed in the cloud is a lot faster and they've moved to many more users back here. They're in the 5 10,000 user range at the end. Now they have 70,000 users running on cloud enterprise and the scale of what they're doing is absolutely wild right millions and millions in fact more than 10 million automation rules running every quarter hundreds of thousands of manual tasks disappearing massive Rovo adoption across the organization agents running AI Rovo is their default for AI they like it more than any of their other AI solutions etc. So, and you can see when they've started to add strategy collection and Jira Product Discovery. Albeit those are small and still have some growth. So, one example of a customer auto manufacturer.

So, we got one more. Oh, no, I forgot something. Oh, no, I didn't. They're allowing on Rovo. I already said that. And it's all about the platform. When you talk to this customer, the platform is what has enabled them to keep going. A typical pattern that we'll see with the cloud 21 22 23 they're actually adopting cloud moving to cloud moving users over once that two or three year period is done you start to see that acceleration afterwards as they then take on JPD service collection and onwards to the strategy collection which is now running their enterprise dashboard for this large organization.

Here is a totally different customer. This is a major financial services firm. Different continent, different part of the world, different industry. Again, a second of many hundreds of customers I show you that look exactly the same. They again have been with us for about 15 16 years. I actually cut this one off. I think they actually have been with us since 2004 from memory. So actually 22 years as a customer, but the first few years are literally just blank from this scale.

Very similar journey to show you this one again. I believe they're at 30 35,000 users something in that realm. So about half the size of the prior customer in users. However, very close in spend. And you see them in the last couple years again once they've moved to cloud, a year or two of adopting and moving themselves to cloud, moving their data across after a long journey with us. And then starting adopted product collection three years ago, Rovo two years ago, they again have tens of thousands of AI now they're running with Rovo. They really really like it. They use it in automations in everything. It's one of their default things. They built a bunch of agents that do critical work inside compliance in HR in lots of other places that run natively on the Atlassian platform. They're a big user of the Teamwork CLI. They're in our alpha program for the team CLI. So they're actually using the command line interface. They think it will unlock a whole lot more usage of the platform.

They have an incredibly strong responsible AI framework. They spent six months putting us through their AI paces and we were one of the first AI tools that they turned on. Which we're really proud of. We love customers that have very strict guardrails and barriers and then we pass those parts. One of the biggest goals they have is what they call the connective spine of their organization. So Rovo is part of their connective spine. Automating reporting cross-team overhead thousands of engineers like it's a really core part of what they do. And in the last 12 months they've adopted DX and the strategy collection. So you can see that nice jump as they've come on board with those types of things. It's not entirely due to that but just like a general movement. It's an amazing example customer and it works because of the platform. So two of many hundreds of customer examples. I hope they were illustrative to try to show you what it is that we deliver for our customers. And I think they show you the power of being an R&D company.

We've always been an R&D company. We've made a deliberate choice to build a true large-scale platform, a single platform, not taking any shortcuts, even if that meant taking margins down temporarily as we invested in that platform as I believe we've tried to explain every single time what it is that we do. Right? We have certainly ramped R&D over the last few years in a very deliberate effort to build that multi-year period of time to build that platform. Right? What have we done in that period of time? Many shifts simultaneously. Taking our largest customers and moving them to the cloud, building that singular cloud platform, which we're seeing the results of today, as we saw this morning, delivering all the enterprise reliability, governance, compliance, scale of those world's largest companies to 50,000 person plus companies right there, 30,000, 40,000, 80,000 seats, whatever it was, 70,000 seats. And moving from those point products to those integrated collections, a huge amount of work to do all of those. What does that deliver for customers? Well, I thought I'd give you an example, one way of looking at what it is we deliver for customers today.

So, all of this is what we deliver for customers today. So, when I say that, we look at our three, we think about our three transformations, right? We think about our three pillars. We've got the enterprise, the AI, the system of work. Tried to organize the things we do into those, sort of put it into the same lens that we explain in our shareholder letter. All of this stuff on the left, isolated cloud, not easy. Giant customers really want it. Government cloud, we're in Google cloud, FedRAMP moderate, so multi-cloud is Google for now alongside AWS. All of the things on the left, guard security clients we talked about in the middle obviously all the AI capabilities that we've talked about from Rovo search and Rovo chat which are as the first customer there. It's like their best AI tool. To give them the best answers in Rovo chat of any tool that they use. The CLI, all the things you saw this morning, MCP, etc. We talk a lot about AI. I'm sure there'll be some questions obviously all powered by the teamwork graph. Worth pointing that out. That's very important. And on the right, those collections, all the third-party apps, all the platform apps that we've built in terms of goals, etc., etc., etc. You see the icons, you get it. And our Forge development platform. I didn't know where to put that. It's not technically in any of the three, so I put in the system of work.

Now we can support our biggest customers in the cloud after all of that R&D. We've built the world's best context graph at a time when context graphs are incredibly important and it's running at absolutely massive scale. Like we're preparing for trillion object scale. We have to, right? 150 billion plus at the moment. It's non-trivial size and scale of anything. Even at a consumer internet company, that's a big scale. Delivered FedRAMP, all of the things that we've talked about there for banks, government, healthcare around the world. That's what unlocks all the enterprise expansion that I'm sure you'll hear a lot about from Brian. So, I put this down for one reason because you're always asking where does R&D go? So, we look at that. Let's have a look at what this looked like two years ago. So, 2024, it looked like this.

So we had apps, we had no collections, most of the AI stuff wasn't there. Very little of that enterprise stuff had been delivered. Everything on that previous slide, by the way, was GA shipped out to customers being used today. 2026, 2024. That is a massive change in our delivery of product. That those two customer examples hopefully are showing you how that is turning up.

Hopefully that was illustrative. I always struggle to explain where R&D goes. And that platform investment, R&D investment is not just going into product capability. All of those things you show, it's delivering leverage that I hope you can see showing up in our financials. What does that leverage look like? Well, you probably already know these numbers, but for FY26, whole year is not finished yet, etc. Expected non-GAAP gross margins of 88%. Right? Three points year-over-year by continued optimization and scale and a lot of R&D investment that goes into creating that scale and optimization of our cloud infrastructure which now is running at massive scale.

We are hosting more customers. We are hosting larger customers. We are running more workloads. We are powering far more usage through AI. We're doing an absolute boatload of AI traffic. And our margins are going up, not down when it comes to COGS in R&D. And that is an incredible effort thanks to our R&D leaders. I don't know if we have any in the room at the moment. I think we have at least one. And all of the R&D team that have done that over the last few years. That's two charts you would expect to go in opposite directions. And that's a leverage I would argue you get when you build a real platform, right?

Now going to front-run some of the questions that you're going to ask. Know a few of you very well at this point. How are you going to moderate that R&D expenses? I get it. That all sounds wonderful. What does that mean? Well, quite simply, like we've done a lot of the heavy lifting. So, we keep trying to get our language correct here. The unified platform, all of the enterprise capabilities, the unique data graph that has to be built up front. That is an upfront spend to get all that. We can't move a single one of those two customer examples without all the things that we built in the enterprise. That takes years, five, six, seven years to build properly and to do it at scale and for them to test you and trust you to get onto that. We believe we have done most of that work in the enterprise capability and in the system of work capability. A lot of the heavy lifting is there. We will keep investing in all of those areas, but in terms of proportionality to revenue, it will moderate. And I'm trying to explain the reasons why it does means R&D doesn't need to grow at the same pace as revenue going forward. We're obviously going to keep investing in AI. AI will likely to continue to grow. Enterprise will moderate. We're bouncing between those two but moderate as an overall share of revenue right and that's about the leverage we're getting from the R&D investments that we have made every new capability we build in the cloud and as we migrate more customers to the cloud sits on a singular foundation because of the investments we've made one platform not lots of different platforms we don't have lots of different apps we built in M&A we replatform everything it's a long-term R&D story that I'm going to be here in a long time it makes a huge amount of technical sense for us and it gives us that customer advantage as well. Means every incremental R&D dollar we do now benefits the entire cloud platform. And a huge credit to R&D team. I can't explain to you how different this is to the vast majority of other SaaS companies out there, especially anyone with our breadth of product and customer portfolios.

So, we talked a lot about the platform R&D investment. So, people can ask about AI. Look, every SaaS company has an AI story right now. And so we are trying to work out how we explain why ours is different. And we truly believe it is differentiated and different. Right? I can tell you having talked to that customer a couple days ago, they probably have seven, eight apps that have a chatbot, chat sidebar, chat thing, chat app, chat something. Majority of them are just utter crap, right? They don't work very well. They don't give you what you need. Why are we winning in that organization? Because our chat is awesome. Because it's backed by the graph. It's backed by contextual massive amount of work in architectural intelligence smarts and understanding of what it is. We built it properly. We built it really well. We adopt modern models a whole lot of other things. It is a big investment. I believe it will pay off in time and it's very unique.

That's all I need to say about that. Context. You probably heard a lot about it this morning, so I'm not going to repeat any of that. I'm happy to answer any questions on that. I do think in a world of increasing agentic capability, agents floating around, personal agents, team agents, etc., our context is going to become really important. I have a little video coming up which I think will be hopefully interesting. But we do think that as something that is both durable and expanding to our... if I had to simplify from an investment point of view, it's really tricky to work out how to do this. We have tons of AI advantages. I try to get down to three. Enterprise is really hard. One of the reasons is that platform we've built Rovo teamwork graph runs on top of that platform. So for those customers, we can operationalize that at quite some scale. When we have tens of thousands of AI users in some of these companies, that's a non-trivial thing to do and most other vendors actually can't deliver that today. And so we've got that. We continue to add more and more permissions and compliance and controls alongside our customers as they're learning about AI alongside us. We're really on the cutting edge of doing that and it's very non-trivial and backed by the teamwork graph and the platform that we've built. Permissions and AI don't go super well together. It takes an incredible amount of really hard work. Obviously got the teamwork graph. We believe we have a big differentiator in our context and ability to context not just across Atlassian apps but across all the apps and work that we do for those companies that have moved from the cloud to data center. The two examples I showed you, 15 to 20 years worth of workflow data, code data, understanding of their knowledge, which we can give them back in a graph instantly that is accessible to all of their AI tools is a really unique differentiator that I don't think anybody else has in availability today. And we're not stopping. We're going to keep moving that advantage. And hopefully you saw a whole bunch of examples today of this whole like Jira's going to disappear. Call on that. But as a control plane, as a part of the agentic and human collaboration, we see more and more customers using it. We've given you a bunch of stats. I've got a few more coming for you in a second.

The teamwork graph, as we talked about this morning, what can I say differently? Most SaaS companies see only a slice of data. If you look at any of the people who live in a vertical, they don't see all of the information, which means they can't give you great answers. We see more. We have more links. We have more connectivity because of our breadth of workflows than most other SaaS companies, the vast majority of other SaaS companies. And I think we've built a better engineering system underneath that and a better platform. So we believe that's different and we have a singular platform. If you got a lot of different platforms and your data is all scattered around right now and I wouldn't work there for the next couple years, it's going to be miserable. And as we try to show this morning that it compounds. The more usage we have from customers, the more our AI now grows. The more that compounds the data they have and we create a wonderful data flywheel. We're seeing this already working.

Models are continuing to improve. That's wonderful. We have great relationships with all of the foundation model vendors. It's not our job. Our job is to take these wonderful models that are built and deploy them as quickly as possible into use cases that customers want. We're down to sub 24 48 hours on full model transitions where we have it running in our gateway. We often get early access to all foundational model vendors now. We get it running in 24 to 48 hours of public usage and we can start running 1% of traffic through it to see how it performs really really quickly and if it works well, we can move it. If it's cost us more money, but the results are better, we make these trade-offs. It's incredibly advanced orchestration system that we have, but it's really important at the scale we're doing.

And we think it's a moat. We talk a lot about AI. Sorry, I'll keep moving quicker here. We've made the teamwork graph a lot richer as I hope you can see from this morning. Lots of new connectors, lots of new types of processes, lots of new categories of content. Code was a massive lift. It is a huge differentiator to us. The code intelligence internally. It is getting used everywhere. Because the understanding of code is so critical to business processes, not just technical processes. And it's not just about writing the code. We see it used in all sorts of different ways. We try to show that with the example in service collection today where in IT ops scenario to fix an issue. Understanding the code makes a huge difference to how quickly you can fix an issue. Again, a true differentiator in that service collection space. And how it does reasoning over all the connections etc. The graph is just amazing. And now we're opening it up with MCP with CLI and with DIA. So again, if you want the breadth of what we're trying to explain here, as someone pointed out this morning, we showed everything from a terminal to a browser. There are few companies in the world that can actually show you that and actually deliver all the R&D in between and huge customer benefits at all points. So a lot of excitement there. I'll stop myself before I go on too long on AI and the cool things that we're doing there. Instead, I wanted to get one of our engineers to tell you about this. So there's about a 4-minute video and it's kind of nerdy. Let you not hear from me for a second. Trying to understand what is the ROI of the teamwork graph for our customers. What is the opportunity for us if we can get this out there and show customers how it works. So, watch this video. I hope you follow along and it doesn't go too deep.

Okay so I think hopefully Kun's giving you some idea that might have gone too nerdy. If you want to just zoom out, the exact same agenticus in this case Claude Code probably the most popular at the moment. $268 to run that task. A real world quite complicated engineering task without teamwork graph, $132 with...

Teamwork graph. You don't have to be a Brian-level genius salesperson to go to a customer and explain why we can help them. Secondly, we actually finished in a minute and 10 seconds less and we got a better result. The code needed less tweaking afterwards. It was more clear because it did a lot of searching of the context first. It understood business and technical data to get a better result. Exact same coding engine, exact same harness. The only difference is we added the TWWG CLI and we obviously have a lot of our own code index, etc. So hopefully that is a different example of the graph in action. You can multiply that across all the business agents that are coming across all the other areas. This didn't use people data at all in this case but we have great access to that, etc. So when we say cheaper, better, and faster with a teamwork graph, it's a very simple message to customers and it's a very true message backed up and nobody else can do this right now.

So it's not theoretical. It's already showing up in the numbers. Let me show you what we are seeing with some AI stats. Some, you know, some that I think are new. So, as we said in our shareholder, Rovo customers' AI credit usage, their Rovo credit usage is growing at 20% month over month. That is a pretty good number. We're early in the curve, but we're already a very large player in terms of AI MO and usage, and the density of usage is growing very fast. Secondly, when customers adopt Rovo, they grow their ARR at twice the rate, twice the growth rate. And our expansion rate, as you know, is quite good. Our NRR, they're growing at twice the growth rate of customers that haven't turned on Rovo. And lastly, it is delivering value, right? They are stickier, they move more. Again, we've given all these stats. I don't know if the 75% of the Fortune 500 companies that have turned on Rovo is a new stat, but it's there. And you can see our agentic automations are growing really, really strongly. One way of using agents again is through automations putting them into various rules that happen automatically and can access all of the teamwork graph. So some AI stats.

And when you look at the teamwork collection, which is our primary AI monetization vehicle right now, again, north of a thousand customers, million seats inside the first six months of upgrades of existing customers. Some new in there but mainly upgrades. Choosing to upgrade? Why? Roughly 10 times the AI or Rovo credits when you upgrade. We have a lot of other economic advantages and I would argue now advantages for the customer. You get the same number of Confluence, Jira, and Loom seats which increases your collaboration broadly but again far more AI credits. TWWC customers use twice as many, consume twice as many Rovo credits per paid user as non-teamware collection customers and they have twice as many active agents. Now they have more credits. So you well, they've got more credits. They've opted in. Awesome. Give people more credits. They use it more. As long as that keeps growing, it's a really good wicket to be on. And I say this often enough because sometimes I don't think it gets differentiated. These aren't roadmaps. These are delivered in-market features being used by customers today. We delivered the teamwork graph CLI today. The teamwork graph is used by all our customers and available to all our customers. They can log in at teamworkgraph.com and see it today. Almost nothing we showed this morning is not available today. It's like one or two features that are coming in the next maybe two months, three months. Everything else delivered on the day. Right? That is our amazing capability.

So obviously you're asking, okay, well how do we capture the value in that model? We're going to get asked about AI pricing and monetization so I put this together, I hope it's useful. We have multiple pricing models. We're trying to be customer-led, we're trying to meet customers where they are. Most of our apps are priced per seat. I still think that's the way most customers want to purchase software. When I talk to customers that is what they say. They want a very generous number of Rovo credits involved in those per seat accounts. So we have the price per seat, I'm sure you're familiar with that part of our model and these are sort of illustrative down the bottom. There's other things we could put in. Secondly, we do have usage-based pricing, consumption-based pricing. We have a growing set of consumption-based offerings, whether that is Rovo credits, whether that's customer service management resolutions, Bitbucket pipelines, we have assets, which is increasingly growing with some customers. We have Forge and Forge compute and Forge SQL and our extension framework. So, we have a lot of usage-based models that are growing, right? And established revenue streams there. And we have our hybrid pricing. So that is things like the teamwork collection. I didn't quite know where to put that where you can buy these apps individually. Most of them you can buy the usage-based pricing individually and then when you buy something like the teamwork collection you get a set of those usage meters together inside that collection pricing. Right? So it's a different way of thinking about it. And we have a flex-based model that we are working on with customers at the moment that we're actually talking to a whole bunch of customers this week which is more of the overall sort of commitment-based model as I would say is the way to think about it. So as our bigger customers that get well north of a million dollars say here's what I want to commit to your platform. I want to be able to move it around seats, move it around applications and collections and I want more usage-based certainty. That is another model that we have. Again, we're here for the long term. This is us being customer-led as they ask. We have the ability to move around this and again I would say the early signals are strong. Customers using MCP grow their ARR at twice the rate of those that do not. So the 'people use AI, run away from Atlassian' and I'm like, certainly not seeing that in the data. Seeing quite the opposite. I would say customers using our MCP server that was before the CLI. We obviously don't have any stats on that. Early signals, MCP is a pretty advanced organization, so we need a lot more data to have that growing, but at the moment, twice the rate in ARR. And as we said, our Rovo credit usage growing at 20% month over month moves you between different pricing models. If you're seeing value, I think I've covered all that.

I didn't know where to put this stuff. So AI isn't just adapting how we price, right? It's also creating new product categories. So here we have Focus and Talent and DX. Reason I put these up here, these are different applications to what we've traditionally sold. They're really only enterprise applications sold at large scale. If you're using DX to measure the productivity of an engineering organization, you probably have 500 or a thousand engineers to start with, right? You're not buying this for 10 people. You don't need Talent for 10 people. You need to look around the room. As workforces adopt AI, where we're seeing those customers like the financial institution I showed earlier, they are using us in their 'how do I think about myself moving from AI novice to AI native, how do I look at my talent, my skill mix, who can help me see that'. DX is all about understanding how AI native my engineering force is and which teams, which services, which parts of my organization are faster and slower, which are using more AI and which are quicker and not quick. That is a phenomenal business. Wanted to make sure I put DX down there. It's ahead of our projections. We're feeling really good about that business. It's only a few months in, but again, all in that area. It's not necessarily a different pricing model, but a different type of application for us. Again, as we have these customers who've come in and opted into us as a platform, it's those customers that you saw earlier that are likely to open it up. And these are all used by the C-suite as we continue our enterprise journey. I spend a lot more time with CEOs than I ever have and CIOs. They're using these applications day-to-day. They don't probably sit in Jira so much, but they certainly sit in Talent. They certainly sit in DX. They certainly sit in Focus. They're very important to them. Helps continue our journey on that.

And there's a prerequisite for all of this. Martin's going to kill me. We should probably talk about cloud migrations. A little bit of a topic. I haven't gotten there yet. I'm taking too long. Customers are moving to the cloud. We're doing really well. I think you know that and you've seen it. It is the ultimate destination. It's the value of Atlassian. It's where customers get the most value. Can't get AI, can't get the teamwork graph, can't get anything. This I think I should say is illustrative by the way. So we've been very thoughtful and systematic. I hope you can see about our multi-year, decade-long cloud transition. Both in terms of the building of the future ahead and moving customers. I think we've executed extremely well across the hundreds of thousands of server customers. Now we're getting the data center customers at some scale. But the migration itself still has a ways to go in terms of the number of seats we have in the data center. That's a good sign. What does this look like? What is an illustrative example of customer pricing? It's always hard. So I picked an example. 93% of our data center customers that are upgrading to the cloud are landing in Premium or Enterprise. And I know this because in some of the models and some of the things we've seen, you can think, oh well, a data center customer could go backwards moving to Cloud Standard. That doesn't happen for 93% of those data center customers. It can mathematically happen. But I thought it was useful to say this. This is a 5,000-user data center tier. So that's 4,200. Again, in the cloud, you buy what you need. You don't buy sort of bigger tiers infrequently. So we've talked about that in the past. The interesting part, this probably isn't news. The interesting part is what happens after they migrate. So now we have many years of history of moving large scale customers. So let's look at multi-year. Let's take a three-year period. Let's take a thousand-plus user customers. So only the large customers have moved, thousand-plus users that have upgraded to the cloud. What happens in their three years after they move to the cloud? Well, they grow about 1.75x, one and a half to 2x growth in the three years after they migrate. Why? All those things I talked about before. Seat expansion, cross-sell, they can get Focus, they can get Talent, they can get DX, they can get the product collection, they can get the service collection with all the capabilities. So, you saw that in some of those customer examples earlier. It's saying that we're being successful at moving those customers and when we move them, we have a good couple of years after they move. They continue to expand their footprint after they move because of all the reasons we've talked about. And their ARR growth continues strongly after they migrate. We're not collecting all of the value at the point of upgrade. In fact, we're trying to trade that off over that three-year period. And you've probably seen this chart before, but the cloud is a flywheel. It's not a single project to upgrade. It is a flywheel that moves them to the cloud and they continue to grow. That's what we're trying to show over time. It allows us to continue to ship our AI faster, monetize all those new use cases, capture those workflows, right? Compounding our momentum with consistent 120% plus NRR growth at scale in the cloud. That is what we're seeing. We had this rainbow chart, we went public. I love that we just keep adding years to the rainbow chart and it keeps going.

So we have a huge opportunity. We're crushing it with customers voting ever more for us as a platform. We feel incredibly strongly. Brian will come up. You will hear from him. Our cloud growth is extremely healthy. Our AI progress continues to be extremely strong and hopefully you can feel from me and everybody on stage. We're so bullish about what we're doing in that area. NRR 120% strong. You might be asking, it can be difficult to see this in your financial statements on the face of your financial statements with ASC 606 through this migration. So, what can we talk about that? Well, I want to cut through a little bit of noise before I hand over to Brian. And again, is anyone familiar with this logo? Extra points for investors if you can tell me what it means. Open company, no bullshit. Love it. Yes. This logo means open company, no bullshit. It's one of our five company values and we want to be direct, right? So 2024, 2 years ago, we issued expectations on a three-year 20% plus revenue CAGR through FY27. Since then, we've had a few major changes. In September of 2025, last year, yeah, that's right, calendar year. We announced Ascent, so the end of life of data center by March 2029. First thing I want to stress, that is a great thing for our customers, is a great thing for our R&D organization and our business. The challenge it made for us, we were a year ahead of schedule. We delivered Ascent in September of 2025, not September of 2026. Due to all the enterprise progress we had made and the R&D we invested in, that was ahead of our schedule. That's great for customers. That's great for our business. Enabled us to accelerate our customers' journey to the cloud. However, as a result, as you saw last quarter, that creates three interesting dynamics that affect the data center revenue line. First, with ASC 606, we move from 20% upfront revenue to 50% upfront revenue. And you model that with the one-year acceleration creates a challenge for us on the license line in data center subscriptions. Secondly, we moved our customers, which was not predicted three years ago, from multi-year deals to one-year deals. Couple of reasons why we did that. Firstly, when you have a three-year end of life, you can't sell someone a three-year deal a year later. It doesn't make any sense. Secondly, we want to have multiple opportunities to talk to that customer. So, we've moved the vast majority of our data center customers to one-year licenses. Model both of those together, you see what the effect is. Those one-year licenses give us three opportunities to talk to that customer over time. They often say, 'I get it, but not right now. Got busy things. There's this AI thing. Have you not heard about it?' We have a conversation. Yes, we're good at that, etc. And lastly, data center customer purchasing patterns have continued to emerge and accelerate as we move to cloud. Again, all these are good things. We saw that play out in a pretty big way last quarter as I know a number of you heard about with a lot of pull-forward activity into FY26 from FY27 which results in greater licensing revenue in DC in 26 far more than we had expected which is a good thing in general. Timing dynamic creates a problem. So we continue to see strong cloud growth rate. Great for our customers, great for our business and data center retention, but the greater term revenue in 26 in data center. We now expect negative data center revenue growth in 27. We've pulled all that forward which is a great thing for us. So I tried to explain this both open, no bullshit, and I'll give you some illustrative charts. I thought I'd say all that so you were listening and I saw you writing before I showed you the charts. So this is an illustrative revenue growth. Number one, we're expecting a trough in total revenue growth in FY27. Number two, we expect that to significantly re-accelerate in FY28 as we lap that data center effect going through. You can see why that one-year acceleration is a credit to the engineering team creates a challenge for the finance team. And given these dynamics, the three-year 20% CAGR that we set two and a bit years ago is no longer a relevant target to anchor on. What is relevant and a much better measure of the strength of our business is ARR. Again, this is illustrative. Don't get out your rulers. So why is that? Well, ARR normalizes the effect of ASC 606, that revenue recognition and helps everyone I think much better understand the overall health of our business. So if you take our subscription business, so data center and cloud, put it together, do a lot of great mathematics that our finance team is able to do, you see a very different pattern here is our subscription ARR for the last seven quarters. What you can see in the last three quarters is a pretty good pattern of acceleration of ARR at the overall level of the business. One of many indicators, but I think a really strong one showing how strongly we feel about how our business is operating and trying to explain the dynamics between all of these different things. I'm sure we'll have time for questions on that.

Last one, I wanted to talk about one more thing before Brian comes on. What do we mean by the phrase durable profitable growth? Well, I hope we've shown that we have a durable growth story both in our results and in the go-forward opportunities we have in AI, in the system of work, in the enterprise and all the things we're doing in cloud. The customer stories, the customer scale, all the things we've done. The profitable word is also really important to us. We've been a capital-efficient business for 24 and a half years and I think I will make sure that we are continuing to be so. We also expect as a result of all the changes that we've made that was not taken into account two and a bit years ago to accelerate and grow our GAAP operating profit beginning in FY27. Sure. We'll have more on that in the future, but wanted to put the profitable and the durable and the growth all three words incredibly important to us. So, we've made a lot of the great investments, enterprise AI, system of work. Hopefully, they add together to see why we have that durable profitable growth over time. But you probably want to hear a lot more about our large customers. Let me bring up Brian, our fabulous hero, who has lapped one year and a little bit in the seat, so he has a lot more to tell you than he did a year and a bit ago. Here's Brian. Thank you.