And the ROI or the dollars you can charge for our customers over time is changing whether that’s usage-based or some other business model, but we’re now providing so much more value for our customers than we were before the AI revolution came over the last 1.5 years that our opportunities there are alive. So I can go on and on. I don’t know if it’s Mike or Joe want to add anything to that.
Mike Cannon-Brookes: Yes. The only thing I would add, Scott covered all of the basics. And obviously, we’re incredibly bullish about AI. We got some exciting stuff coming up next week. We hope to see you all there at Team 24. The Atlassian platform is probably one of the areas that I always think is underestimated in terms of durable growth and in terms of long-term advantage. Again, Atlassian is a company that thinks very long term and very strategically and thoughtfully as we go through Equinox and Solstice and Equinox and Solstice and Equinox and Solstice, the world goes around and around, and we try to think about that across more than just a singular quarter. In terms of engineering, you see we have significant R&D investments, right?
That is a part of how we think about the world. And in the cloud, a large amount of that goes into the Atlassian platform. Building out the platform to scale across our products is a unique, competitive advantage. It is increasingly resonant with customers as a differentiator and as a moat that allows them to choose multiple products, allows them to adopt our products more seamlessly, more quickly, get automation across those products, get analytics across those products and build out the teamwork graph that underpins a lot of our Atlassian intelligence and other future capabilities. That is a super unique advantage that comes only from our large R&D investments and our long-term thinking and our ability to, in a capital-efficient way, fund that build out over a many, many year period, and it will continue to be so over the future periods.
Nick Altmann : Awesome. Thanks guys.
Operator: Your next question comes from Kasthuri Rangan from Goldman Sachs. Please go ahead.
Kasthuri Rangan: Yes. Toggling from one call to the other. Thank you so much for the time here. My question is, it looks like given the continued strength in the data center product, this is going to be here to stay for quite a while. So I’m curious, when you look at the product road map ahead, how much of an emphasis is being placed on the development side on the cloud, particularly with respect to the functionality. And when are we going to start to see a divergence by design, by intention between the cloud and the surviving entity. And what new incentives are we going to see in the fiscal years ahead and also migrations, are we going to make those migrations easier going forward? Thank you so much. Appreciate it.
Mike Cannon-Brookes: Sure, Kash, I can take that. Look, I would say from our customers’ point of view, it is well understood that the cloud is our future and our customers know that. As Scott mentioned earlier, five years ago, you had a lot of customers that said, I’m not going to the cloud. Now it is a when, not an if, right? I do not run into customers who say they will not go to the cloud. I run into customers who say, we can’t go now because of this reason, or that reason, either internal reasons or Atlassian related reasons. The divergence of features to some extent has already happened, because of the nature of the cloud. So you need to look no further than Atlassian Intelligence, right? AI and LLM driven features with large-scale foundational models requiring teamwork graph in the Atlassian cloud platform is not something that we can bring to a data center customer, and they understand that.
It’s a completely logical reason. And hence, an extra reason or incentive for them to migrate. Now we are building continually hybrid supporting features in things like our migration tooling and in other areas as those customers move parts of their workload to the cloud, if you think about it that way. And that is helpful to those customers over time. Beyond that, we do continue to invest in the capabilities of data center for those customers, right in terms of security, in terms of their scale and compliance and in terms of features where we can take certain features, which makes sense to build in data center and in the cloud simultaneously. So I think the customers understand that. In terms of additional incentives for DC customers to move from a financial and other point of view.
We continue to work with our customers and our partners as to the best way to do that. Often, it’s not financially driven, right? It can be as much about compliance and data residency and Fed ramp and enterprise scale and all the things that we are continuing to work on with those customers.
Operator: Your next question comes from Fatima Boolani from Citi. Please go ahead.
Fatima Boolani: Good afternoon. Thank you for taking my question. And Scott, congratulations to you for absolutely legendary run. Just on the point of the carats or the incentives for your existing data center customers to move to the cloud. I wanted to ask you the question in a different way. You always make substantial progress in solving for data residency demands and other compliance and security blockers for some of your most regulated and complex customers. So I’m curious what is left to address or alleviate from a “cloud” blockers standpoint? And what type of investment should we expect that will entail in the medium-term? And the reason I ask this is because the expectation is that your data center migrations to cloud are going to accelerate, presumably most of those blockers have been renewed. So I would just love a little bit more color on that front. Thank you.
Mike Cannon-Brookes: Sure, Fatima. I can take some part of that. Look, I think at the highest level, it is a pretty big testament to our enterprise maturity that three-quarters of our enterprise customers in regulated industries have a cloud footprint today. So you talked about our achievements and thank you for noticing that, by the way that’s very gratifying. We have been working incredibly hard on those areas, and it is resonating with customers, and that’s an important place to start. Second, I’d say, these customers, we call them our largest, the most complex, most enmeshed customers. That is one of the things that just takes time for them to move. Like for a lot of these customers, it is a three, five year road map they’re running in these large complex IT organizations.
That’s not about — I think you referred to them as cloud blockers. That is just about that company saying, yes, I get it. I have these projects going on. It’s going to take me a year, two years, three years. I’m going to move this piece first, and this piece second. Some of that’s the natural progression pace of those customers. There are certainly things we can do, improving migration tooling and lots of other things that we are working on. But some part of the paces were in terms of the customers. And there is no doubt, we will continue to work on governance, as we mentioned, we’re in process with FedRAMP Moderate and we continue to work on things like that for governmental customers. We have more data residency regions we’d love to roll to for sure.
There is always more performance and scale that we can [kick-out] (ph) for our largest customers. So there are a lot of things that we have to continue to work on. In the app and extensibility area, we continue to ship improvements every single quarter. Now the other thing is building customer trust. We see our relationship with the customers, especially in the subscription environments like data center and cloud is about demonstrating continued trust over time. They’re subscribing to get our future offerings. We can see that in the last two quarters, we’ve hit 100% of our cloud road map in R&D in terms of delivery. So when these customers are making a multi-year or even decade-long commitment to Atlassian as a partner, they want to say that we’re going to deliver on the things that we tell them we’re going to deliver on, which is certainly what we’ve done over the last period of time.
That said, having customer conversations, they acknowledge they are clear and they see that we are continuing to remove the, as you call them, cloud blockers over time. So that trust is going up when you talk to customers. They are seeing our progress just as you are. So I hope that’s helpful.
Fatima Boolani : Okay, thank you so much.
Operator: Your next question comes from Arjun Bhatia from William Blair. Please go ahead.
Arjun Bhatia: Perfect. Thank you. Maybe one for Mike or Scott, I just wanted to touch on the AI landscape, but maybe more from the sense of what it means for the role of the developer, right? We’re hearing a lot more about text to code capabilities and how that’s automating a lot of the workflow for the developer role and you have companies popping up that are addressing these start-ups that are doing this more and more. But from your perspective, how do you see the role of the developer changing? And maybe what does it mean from an Atlassian perspective? What does it mean about how Jira might need to change or evolve to manage the agile process overall.
Mike Cannon-Brookes: Yes. Thanks, Matt. I can certainly take that one. Lots of thoughts here. Firstly, AI is awesome for software development in the broadest sense, right? Large language models, their ability to generate code, their ability to understand code, which is arguably more important is phenomenal for the world. It — we take the position that the world has a supply constraint in the number of engineers, not a demand constraint in the amount of ideas we have for software that we would like to be built. What AI does is loosens that supply constraint. We’re not going to hit demand ceiling. So people will be able to do more with the number of engineers that they have is the way we think of it. That is good for us for a number of reasons.
Firstly, most developer time is not spent on coding. It’s spent on coordination activities, it’s spent on how developers work with product managers and marketing teams and service teams, how they support and operate the software and services that they’ve built rather than just the sort of classical view of coding a piece of software and then delivering it. That is a collaboration activity. That is a difficult hard problem that we spent 20-plus years working on, and I suspect to spend most of the next 20 years continuing to work on. Secondly, AI, we believe, will generate far more software, far more services and apps and tools, and that is a great thing for us, especially for things like Compass, which are about managing developer experience, managing your software sprawl.
Again, resonating extremely well with customers only a few months into GA, but obviously — but already taking off on a pretty strong growth path and well ahead of our expectations. So Compass and AI is a great thing that have more software. And thirdly and lastly, the ability of AI to allow non-developers to “right” code in some sort of a form to be able to do more programmatic capabilities is quite fantastic. You can see this in Atlassian analytics, where the ability to use natural language to turn into SQL and then chart and dashboards, it’s kind of a developer like activity but allows a democratization of the ability to get to that analytics, to get your data to understand it. I think there’ll be many, many more things like that, that allow these AI capabilities to democratize what we used to think of as software development, maybe that’s the way to say it.
So Scott, I don’t know if you have any follow-ons.
Scott Farquhar: I just do it to bring in the first point you made, which is just that I think — for people that don’t write software, I think it may be not well known how little time people actually spend hands on keyboard writing code. A lot of software is working at the requirements and what it success looks like and how do we want to build things and where is data going to come from. And so you can make huge differences in how much time developer spends with hands on keyboard. But percentage-wise, it actually doesn’t change their weeks that much because they spend a lot of their time in Jira, in Confluence in like talking to customers, gathering requirements and you look at where our products touch our customers, that’s a way larger percentage of a customer’s week than a developer’s week than writing in an IDE.
