Atlassian (TEAM) Q1 2027 Earnings Call Transcript

DATE

Thursday, Nov. 5, 2026

CALL PARTICIPANTS

• Head of Investor Relations - Martin Lam
• Chief Executive Officer and Co-Founder - Mike Cannon-Brookes
• Chief Financial Officer - James Chuong

TAKEAWAYS

• Total Revenue -- $1,772 million, representing 24% year-over-year growth driven by strong subscription demand across the Atlassian platform.
• Cloud Revenue -- $1,302 million, an increase of 31% reflecting continued seat expansion in Jira and Confluence and cross-sell momentum into product collections.
• Subscription ARR -- $6,812 million, growing 23% year over year as customers transition to cloud-based and data center subscription models.
• Remaining Performance Obligations -- $4,746 million, a 44% increase driven by larger, multiyear enterprise commitments.
• GAAP Operating Margin -- 11%, compared to a negative 7% margin in the first quarter of fiscal 2026.
• Non-GAAP Operating Margin -- 32%, expanding from 23% in the prior year due to disciplined operational execution.
• Free Cash Flow -- $463 million, representing a 304% increase year over year and a 26% free cash flow margin.
• High-Value Customer Growth -- The cohort of customers spending over $1 million annually grew north of 30% year over year.
• Service Collection Performance -- The collection surpassed 70,000 customers with ARR growth exceeding 30% as the company captures market share from legacy vendors.
• Teamwork Collection Adoption -- Over 3,000 customers have upgraded to this collection, representing a sevenfold increase compared to the prior year.
• Agentic Collaboration Volume -- Human-agent collaborations reached 10 million monthly interactions, doubling over the last six months.
• MCP Server Engagement -- The Atlassian MCP server reached more than 2 million monthly users and 15 million daily tool calls.
• Enterprise AI Adoption -- Over 87% of enterprise Cloud customers are now utilizing Rovo for AI-powered workflows.
• Migration Contribution -- Data Center to Cloud migrations contributed approximately mid- to high single digits to Cloud revenue growth during the quarter.
• Customer Expansion Multiple -- Customers transitioning from Data Center to Cloud increased their total spend by an average of 1.75x after three years.
• Marketplace Lifetime Sales -- Total sales through the Atlassian Marketplace surpassed $7 billion since its 2012 inception.
• Q2 FY2027 Revenue Guidance -- Total revenue is projected between $1,825 million to $1,835 million, with Cloud revenue growth expected at 27%.
• Full-Year FY2027 Revenue Guidance -- Management targeted total revenue growth of approximately 13.8% and Cloud revenue growth of approximately 26%.
• Full-Year Subscription ARR Guidance -- Subscription ARR is expected to grow approximately 18.5% year over year.
• Data Center Guidance -- Data Center revenue is projected to decline approximately 14% in the second quarter and 16% for the full fiscal year.

Need a quote from a Motley Fool analyst? Email pr@fool.com

RISKS

• Chuong warned that the company is "balancing the momentum that we're seeing in the business... with the uncertainty around the evolving dynamics in the macro environment, the fiscal policy, geopolitical landscape," indicating potential volatility in future periods.
• Chuong noted that while hybrid deployments reflect long-term Cloud commitments, they resulted in "slightly more revenue on Data Center and slightly less on Cloud this quarter" than previously expected.
• Chuong indicated that the company will face "tougher comps" in the second half of fiscal 2027 following the significant acceleration achieved in the second half of fiscal 2026.

SUMMARY

Atlassian Corporation (NASDAQ:TEAM) reported growth across its enterprise and AI strategic priorities, including expansion in Cloud subscriptions and multiyear customer commitments. Management stated that customers are increasingly consolidating workflows and agents onto the company platform to utilize integrated AI capabilities. The company indicated that its Teamwork Graph and Agentic Multiplayer Protocol are central to its strategy of providing context-aware collaboration for both humans and agents.

• Strategic partnership with OpenAI. Mike Cannon-Brookes stated, "Atlassian and OpenAI are grounding frontier intelligence in enterprise context, pairing OpenAI's models with the Atlassian Teamwork Graph so teams can connect ChatGPT and Codex to the real shape of their work."
• Launch of Agentic Multiplayer Protocol (AMP). The company introduced AMP as a platform-wide collaboration layer that enables agents to work alongside humans with shared context, distinct identities, and governed authority.
• Expansion of the Forward Deployed Engineer (FDE) program. Cannon-Brookes noted that FDEs are fully qualified AI and machine learning engineers who write production code at customer sites to accelerate AI adoption.
• Usage-based pricing implementation. Management indicated that enforcement of usage-based pricing for AI credits and automation will begin in early December 2026, though no material revenue is anticipated from this in fiscal 2027.
• Public sector roadmap acceleration. The company announced plans to submit for Impact Level 5 authorization in July 2028 and FedRAMP High in January 2029 to deepen its engagement with federal agencies.
• Marketplace milestone. The Atlassian Marketplace reached $7 billion in lifetime sales, supported by over 2,000 partners and more than 6,000 available integrations and apps.

INDUSTRY GLOSSARY

• Rovo: Atlassian's AI-powered agent designed to help teams find, learn, and act on information across diverse applications.
• Agentic Multiplayer Protocol (AMP): A technology layer that allows AI agents and humans to collaborate within the same workflows with clear attribution and identity.
• Teamwork Graph: A data structure that maps the relationships between people, projects, goals, and knowledge within an organization.
• Remaining Performance Obligations (RPO): The total amount of contracted revenue that has not yet been recognized, including deferred revenue and non-cancelable backlogs.
• Service Collection: A bundle of Atlassian products focused on service management, including Jira Service Management and Assets.
• Teamwork Collection: A set of collaboration tools including Confluence, Trello, and Loom designed for cross-functional team productivity.
• Forge: Atlassian's cloud-native development platform used by partners and customers to build custom apps and integrations.
• MCP (Model Context Protocol): An open standard used to connect AI models to specific data sets and tools.
• FedRAMP: A U.S. government program providing a standardized approach to security assessment and authorization for cloud products.
• IL5 (Impact Level 5): A Department of Defense security standard for cloud services handling highly sensitive, unclassified information.

Full Conference Call Transcript

Operator: Good afternoon, and thank you for joining Atlassian's earnings conference call for the first quarter of fiscal year 2027. As a reminder, this conference call is being recorded and will be available for replay on the Investor Relations section of Atlassian's website following this call. I will now hand the call over to Martin Lam, Atlassian's Head of Investor Relations.

Martin Lam: Welcome to Atlassian's First Quarter Fiscal Year 2027 Earnings Call. Thank you for joining us today. On the call with me today, we have Atlassian's CEO and Co-Founder, Mike Cannon-Brookes; and James Chuong. Earlier today, we published the shareholder letter and press release with our financial results and commentary for the first quarter of fiscal year 2027. The shareholder letter is available on the Investor Relations section of our website, where you will also find our other earnings-related materials, including the earnings press release and supplemental investor data sheet. As always, our shareholder letter contains management's insight and commentary for the quarter. So during the call today, we'll have brief opening remarks and then focus our time on Q&A.

This call will include forward-looking statements. Forward-looking statements involve known and unknown risks, uncertainties and assumptions. If any such risks or uncertainties materialize or if any of the assumptions prove incorrect, our results could differ materially from the results expressed or implied by the forward-looking statements we make. You should not rely upon forward-looking statements as predictions of future events. Forward-looking statements represent our management's beliefs and assumptions only as of the date such statements are made, and we undertake no obligation to update or revise such statements should they change or cease to be current.

Further information on these and other factors that could affect our business performance and financial results is included in filings we make with the Securities and Exchange Commission from time to time, including the section titled Risk Factors in our most recently filed annual and quarterly reports. During today's call, we will also discuss non-GAAP financial measures. These non-GAAP financial measures are in addition to and are not a substitute for or superior to measures of financial performance prepared in accordance with GAAP. A reconciliation between GAAP and non-GAAP financial measures is available in our shareholder letter and earnings release on the Investor Relations section of our website.

We'd like to allow as many of you to participate in Q&A as possible, so out of respect for others on the call, we'll take one question at a time. With that, I'll turn the call over to Mike for opening remarks.

Michael Cannon-Brookes: Thank you all for joining us today. Now as you've already read in our shareholder letter, we had a great start to fiscal 2027. Total revenue grew 24% to $1.8 billion. Cloud revenue grew 31% to $1.3 billion, and subscription ARR grew 23% to $6.8 billion. We also delivered GAAP operating margin of 11% and free cash flow of $463 million, an increase of 304% year-on-year, representing a free cash flow margin of 26%. These results reflect strong customer demand and execution across our big strategic priorities of enterprise, AI and the system of work, our continued focus on driving durable, profitable growth.

Customers are bringing more people, more agents and more workflows onto the Atlassian platform, and they're making larger and longer-term commitments. This quarter, Infosys, SAP, Workday and Westpac are just a few examples of global enterprises that expanded greatly with us, standardizing how their teams collaborate, operate and execute business processes on the Atlassian platform. You can see that in our RPO, which grew 44% year-over-year to $4.7 billion, and customers spending more than $1 million a year grew well north of 30% year-over-year. In the Cloud, we saw continued strong seat expansion in Jira and Confluence, along with strong cross-sell into our collections.

More than 3,000 customers have now upgraded to the Teamwork Collection for expanded Rovo credits and platform capabilities. That's a 7x increase year-over-year. The Service Collection has now surpassed 70,000 customers, with ARR continuing to grow over 30% as we continue to take market share. What makes our system of work valuable in the AI era is a combination -- a unique combination of context, collaboration and confidence. With context, yes, models are getting smarter, but to be effective at work, they need to understand an organization's goals, knowledge, people, decisions and history. The Teamwork Graph now connects more than 250 billion objects and relationships and extends across customers' third-party tools to more than 80 out-of-the-box connectors.

That context translates into real value for our customers. Customers with a richer Teamwork Graph are twice as likely to become deep Rovo adopters, and deep adopters grow ARR more than twice as fast as customers with light Rovo usage. Teamwork Collection customers are running twice as many agents while expanding their Jira and Confluence seats much faster than stand-alone customers. Next, to collaboration. At Team '26 Europe, we introduced our Agentic Multiplayer Protocol, or AMP, as a collaboration layer built across the Atlassian platform, not as a separate product that customers have to buy. It helps people and agents work together with shared context, clear identity, attribution and governed authority.

More than 10 million human-agent collaborations now happen on our platform every month, double the level of 6 months ago. To learn more about AMP, I just shared a Loom on our Investor Relations website. And finally, to customer confidence. As agents take on more work, enterprises need visibility, security and governance of where that work is happening. We continue to build those controls into our platform so customers can scale their AI responsibly. More than 87% of our enterprise Cloud customers are now using Rovo, and our larger, longer commitments show how deeply customers are investing in this foundation. Overall, we're executing extremely strongly our strategy from a position of strength.

We're seeing this play out again in our results. I'm super excited about the year ahead. Connecting agents and humans on the Atlassian platform will continue to unlock huge value for our customers, and we're extremely proud to be building for that future. With that, I'll pass the call to the operator for Q&A.

Operator: [Operator Instructions] Your first question comes from Ryan MacWilliams from Wells Fargo.

Ryan MacWilliams: Really strong result on the Data Center side. But then I guess like the full year guide was pretty similar. We've talked to some of your customers, some of your largest customers, and it seems like they're prioritizing the migration to Cloud in the coming years due to agentic coding and some of the new features that you're offering. So I'd love to hear just kind of like what drove the strong Data Center result in the quarter? And then maybe how your customers are thinking about migrations for the rest of this year and at this point?

James Chuong: Yes. Thanks for the question, Ryan. Yes, I think, just starting on the overall performance on the Data Center side. As we continue to see customers migrate over to the Cloud right now, we're now sort of seeing some of the largest, most complex customers. And one of the things that we're seeing in the quarter right now is really strong retention. And a big part of that is obviously the Cloud road map that we have, but also the commitments that we're making, for example, in areas like the public sector opportunity, right?

We talked about submitting for IL5 or Impact Level 5 authorization 6 months early, ahead of schedule for July 2028, FedRAMP High authorization submission in January '29 to follow that, and then submitting for Rovo and AI on our Atlassian Government Cloud platform in June 2027. So I think what we're seeing is that in that commitment that we're making to our customers here, we're really being rewarded by some of the high retention rates that we're seeing, and that's outpacing even our expectations here. So really pleased with what we're seeing on that side of it. And I'll also note that right now, Data Center migrations to Cloud contributed approximately mid- to high single digits to Cloud revenue growth.

But in terms of one of the areas where we want to make sure we meet our customers where they are commercially is to make available for them hybrid deployments, right? In particular, in Q2, there were a number of very large customers in the quarter, who as part of their migration journey, signed Cloud migration commitments through these hybrid deployments that enable them to migrate to the -- from Data Center to Cloud over a multiyear period, right? So this is a great sign. Customers are deepening their commitment to Atlassian. They see Cloud as the final destination. And because we don't charge customers twice on these hybrid deals, hybrid deployments did split revenue between Data Center and Cloud.

And as a result, that meant slightly more revenue on Data Center and slightly less on Cloud this quarter. But if you zoom out, the key takeaway here is that the largest, most complex customers are moving ahead with their multiyear journeys to Cloud, where they can really unlock all the benefits of the Atlassian platform.

Michael Cannon-Brookes: Yes, Ryan. I guess I'll just add on a little customer color from my point of view. We've spent nigh on a decade now managing these migrations between server and then Data Center to the Cloud. Having had more than 100 customer conversations in the last quarter, well over 100, I would say the customers are very excited about what we've built in the Cloud, right? They continue to be so. They see the value of AI. It is a big catalyst, beyond all the enterprise and compliance and infrastructural improvements that James talked about, to driving that momentum forward. We landed some very big migrations during the quarter, and we continue to work on them for the quarters ahead.

So I would say the customer feeling and drive towards the Cloud remains incredibly strong as they see how powerful, what a huge upgrade that the Cloud platform is from where they are in Data Center.

Operator: Your next question comes from Fatima Boolani from Citi.

Fatima Boolani: Mike, this one is for you. It's a little bit of a bigger picture question. As organizations shift to more of an AI software development life cycle away from the predecessor agile movement just based on agent decoding becoming the de facto standard on how software engineering is being done, can you talk about how Jira and Confluence benefit from what is essentially, I would argue, becoming a diminished coordination or collaboration tax between human engineers and more presumably seamless collaboration between agents? And then just some of the commercial and monetization trajectory implications for these core products where the functional reason for their existence is to drive that collaboration. So would just love to hear your perspective on that.

Michael Cannon-Brookes: Thanks, Fatima. Yes, great question. Look, we've often agreed on things in the past. I'd have to say we disagree on this question personally. The value of Jira and Confluence for coordination in the AI era is even stronger than it has been in the past. I think this is often mistaken, right? In fact, we shared an example at Team '26 Europe where Morgan Stanley, somewhere on the call, announced they're moving their Jira and Confluence to the Cloud at large scale and rolling out Rovo to thousands of users.

And the main reason to turn even more so to the Atlassian platform than they have been before as a long-time customer is for their software development and to get a better view of what's happening across their teams and to connect their technology teams with their business teams, which is almost exactly out of our system of work playbook, right? I think there are multiple factors happening simultaneously when you talk about this. Firstly, it's about bringing all of that agentic work into a collaboration platform. The human role is incredibly important in intent, in applying intuition and understanding, in guiding and handling exceptions, in initiating work.

So we shipped a whole series of features about agentic sessions coming into Jira at Team '26 Europe, and they were incredibly positively received. There's no doubt the amount of work happening is going to go up, precipitously so. The coordination tax of that then becomes even more so. If you're trying to understand 10x as much work, you need to understand more coordination, more connections than you have been beforehand. The context that Jira and Confluence provides of your history and your future are 2 of the most essential ingredients. We can see that.

We know we're in the top handful of MCP servers of all of the major foundation labs, and not just for reading, but for writing as well, as organizations continue to try to work out how to manage that across their systems. And lastly, as I said, it's about connecting those technology teams to business teams. Increasingly, that code writing, which is incredibly exciting, is being done by people in finance, by employees in marketing and HR and other areas. And so you have even more of a coordination challenge, a larger opportunity for us to connect technology and business teams than we've ever, ever seen before. I believe you can see that showing up in our numbers today.

Our customers would say that. You can see that in our seat expansion numbers being incredibly strong this quarter. Our RPO number, again, accelerating to 44.5% this quarter, reflecting just increasing longer and larger commitments from customers are going out multiple years as they see the value of the Atlassian platform and the context we have in the Teamwork Graph and that collaboration happening across multiple teams, be that in the Service Collection or be that in the Teamwork Collection or the Software Collection. So we're incredibly bullish on our role in the AI future.

And that's before we even get to AMP, which we've talked about, and I recommend watching the Team '26 keynote or the Loom that I just shipped today.

Operator: Your next question comes from Matt Hedberg from RBC Capital Markets.

Matthew Hedberg: One thing I noticed is you're expanding your forward-deployed engineer motion. It was interesting, ServiceNow noted something similar last week. I guess I'm wondering, can you expand upon that motion? Is this indicative of kind of where customers are at in their kind of AI decision-making? Just kind of trying to plan things out here just kind of given how quickly technology is moving. Just color on that would be helpful.

Michael Cannon-Brookes: Thanks, Matt. Look, I can talk to our FDE motion. Firstly, I would encourage, as I encourage all customers and encourage all investors, all FDEs are not built the same. Our FDEs are fully qualified AI and ML engineers who are writing full production customer code and product code at the customer site. So they're trying to help customers to get their AI motions moving, to get workflows moving onto the platform. We have had -- that's different to some other places where they're rebadged customer success staff, et cetera. It's extremely hard to scale that program fast. As you can well appreciate, those are very rare individuals.

Our FDE program, though, is going extremely well, couple of quarters in now. We are working with many, many large customers on helping them get more value from AI, right? They bring processes and improvements that they want to see, and our FDEs help them connect the Teamwork Graph. They help them explain to engineers and staff at the customer site how they can continue to roll the Atlassian platform out across more and more of their world, how they can continue to build out their ontology into the Teamwork Graph and how that yields better results with Rovo, with coding agents, with service agents, et cetera. So still early in the program for us.

The goal is delivering AI usage and leaving the customer with a trained group of people who can then continue that rollout by themselves, who have confidence in Forge as an extensibility platform in the Teamwork Graph, in our connectors, in everything that exists in the Atlassian platform, and it's been going very, very well. Again, our goal is not building a service business. These aren't professional services folk. They are rarely ever charged for. So it's pretty different to what other people are doing in terms of professional services and customer success. Lastly, I will say that philosophically, we are seeing great speed ups in our ability to build product with FDEs.

So increasingly, we are doing more and more core software engineering at the customer site. That is very unique. It's an ability of our platform and our really world-class R&D organization to be doing this. It helps us speed up the customer request to delivery loop incredibly fast. It's something we're very bullish on. We'll probably talk more about that in the coming quarters as we keep accelerating that program.

Operator: Your next question comes from Adam Wood from Morgan Stanley.

Adam Wood: Congrats on a good start to the year. Maybe if I could ask about AMP. I think you're one of many companies that are claiming the right to execute against owning and managing agent identities, permissions and audits. Could you just talk a little bit about why you think you have the right to win here? And then I think you said you're not monetizing this directly. Do you always see it being that way? And if so, where do we see that drive the revenues for you coming into the business, please?

Michael Cannon-Brookes: Thanks, Adam. How would I answer that? Look, a couple things. I think "the right" to sort of orchestrate, manage compliance agents, et cetera, that's a very broad term. So the reason you're seeing a lot of companies kind of say things like this is it means a lot of different things to a lot of different customers. I can only talk about what it is that we are doing. If you talk about what, I don't know, an Okta or a Workday or someone else is doing, it's very, very different even though the words may sound the same, and part of the problem is just everyone saying agents are lost.

We're trying to show in 2 different places, I think, incredible differentiation and uniqueness. So the first I would point to is AMP. We are trying to bring agents into customers' workflows, structured or unstructured workflows into their collaboration. That collaboration happens an awful lot on the Atlassian platform inside Confluence or inside service management. It happens an awful lot off the Atlassian platform. That may be in a partner app like Figma, it may be in a command line tool like Codex. All of that is contributing to your collaboration and your workflows.

What we're doing in AMP is bringing you a set of experiences, really highly designed experiences, which are truly unique in the world today as well as bringing all the technological standards, so your MCPs, your A2As, all the technology standards that are underneath AMP, and bringing them that in a very human-centric way so that you can quickly roll out the agentic use cases in ways that are understandable. And whether your staff are operating on or off the Atlassian platform, you have understanding about what is happening.

So when we talk about traceability and accountability, it is saying that people can see where a human has done something, where an agent has done something on behalf of a human and if so, who it was on behalf of. If it's just agents operating by themselves, which does happen quite a lot. And if you need to pull other SaaS applications or other agents in, no matter whether that's on or off the Atlassian platform, it's understandable. It was incredibly well received by customers at Team '26 Europe because they're trying to bring the humanity, the design and experience and the power of the agentic world together into understandable experiences across Jira, Confluence, Loom, et cetera.

So we are super bullish about that. It's very, very unique and very different to what is happening elsewhere. We do have a lot of agentic governance features focused more on agents in the Atlassian platform. So when you're building Rovo agents, customers need to be very clear on the controls, the cost measures, the permissioning and the compliance of those agents. We continue to improve that. We ship nonhuman identities, for example, and where those agents can get to our world with MCP servers and the CLI. Again, there's a lot of controls, but that's not so much about control at the orchestration layer overall.

You can see that's going really well, I would say, more than 10 million human-agent interactions, MCP servers past 2 million now, 15 million tool calls. So all of the numbers are going an incredibly rapid pace in the right direction, but with our goal of helping you collaborate across those business processes everywhere that you speak to. And we really think it expands our opportunity as we continue to win more and more workflows and business processes across all the types of teams, from leadership teams to service teams and everyone in between.

How that shows up in the experiences for users is going to be incredibly important, I believe, and letting us harness the best of all of those models. So it's a pretty unique viewpoint, I think, but it's very customer-centric and customer-driven.

Operator: Your next question comes from Gregg Moskowitz from Mizuho.

Gregg Moskowitz: Two related questions, if I may, because I think this is really affecting the share price right now with the investor concern being one of potentially slowing growth outlook at Atlassian. First, the Cloud revenue guide, James, for Q2 reflects about 4 points of deceleration. That is quite a bit more than the guidance from 90 days ago, and it would just be helpful to understand why, if we could. And second, your Q1 subscription ARR growth was really strong, but you're forecasting a meaningful decline over the next 3 quarters. I know the compares get a little tougher certainly due to the Data Center pull forward and to DX in the back half of the year.

But beyond that, are there any other factors we should be aware of that could weigh on the growth rate?

James Chuong: Yes. Thanks for the question, Gregg. Yes, look, I think from the starting point of what we saw in Q1, we were really pleased with the performance that we saw across that Cloud business. As I mentioned a little bit earlier, sustaining north of 30% year-over-year growth and really strong NRR sort of once again here, right? So on what we're seeing here and what we're anticipating is the continued momentum on cross-sell, right? We saw that Service Collection in Q1 against cross 70,000 customers at $1 billion of ARR, growing north of 30%. And in terms of seat growth from competitive displacements, that was up over 40% year-over-year.

So I think we feel really good about what we're seeing there. And as it relates to the Teamwork Collection, right, over 3,000 customers, 7x year-over-year now. And again, still remains the best way for us to help customers adopt and unleash AI across the entire Atlassian platform. When it comes to the guide here, I think we're still early in the year, and we're going to continue to take a thoughtful and prudent approach here, balancing the momentum that we're seeing in the business with RPO at 44%, cRPO at 28%, and balance that with the uncertainty around the evolving dynamics in the macro environment, the fiscal policy, geopolitical landscape.

So again, going to continue to take a prudent approach here. In Q2, we'll begin to lap the DX acquisition. And in the second half, we'll begin to face some tougher comps given the acceleration that we saw in the second half of fiscal '26. And of course, we're still scaling our enterprise go-to-market sales motion to unlock the massive opportunity that we have here. We're in 85% of the Fortune 500, and that represents really just about 10% of revenue. So a ton of opportunity still ahead of us and for us to continue to invest and scale the capacity on the enterprise sales side.

If you look at our $1 million customer plus cohorts, it's continued to grow north of 30% year-over-year. And at the same time, as the business continues to mature, especially on the enterprise side, I do expect to see a little bit more predictability in the business and the forecast. And that's just a natural evolution as we mix shift towards more annual and multiyear deals. But all up, feel really good about the state of the business, coming off a quarter where we posted really strong RPO, subscription, ARR growth of 22.5% and Cloud revenue growth still north of 30%.

Operator: Your next question comes from Allan Verkhovski from U.S. Bancorp BTIG.

Allan M. Verkhovski: Mike, you said you don't want Atlassian to be a centralized control tower, but rather a highly connected subway station. So as enterprises work through their broader AI strategy, what feedback are you getting on Atlassian's approach? What is resonating most with customers? What parts of that vision are maybe taking longer to land? And how is all of that affecting sales cycles and deployment decisions? And then, James, just a quick follow-up for you because I think it's important, can you quantify the downside impact to Cloud revenue in the quarter from the hybrid deployments you mentioned relative to expectations?

Michael Cannon-Brookes: Thanks, Allan. Great question. There are a lot of things I would say here. Let me try to put it into a concise answer for you. Overall, the feedback we're getting from customers is -- ranges from excitement to queries about how we are doing so well, which is a great question to get from customers. Rovo continues to massively outperform other AI systems or services that they are using. And we hear that consistently from customers, to credit to our engineering team. All of the layers from the platform through the Teamwork Graph, through the search and Rovo and chat capabilities, and the integration into our products, our agentic capabilities.

So when you're building agents with Studio, these are truly, truly world-class and fantastic and deliver amazing results. And we hear that over and over again from customers. When I say skepticism, the question is more like, how are you doing this when X can't or I tried Y and it doesn't work as well as Rovo, why is that? I love those sort of questions. The answer is we have a kick*** engineering team. We've invested very heavily in the fundamentals and the architecture. We have a great ability to use models and harness them, and we have amazing organizational context, right?

We have the best enterprise context graph in the world, and it continues to grow and get stronger. As you saw, we just added assets and agentic sessions and more and more inference that we run on top of that graph to fundamentally give better answers to agents. I think we're seeing that in the pull-through from customers, right? Our AI numbers are fantastic, right? Agentic automation is up 9x year-on-year, now more than 10 million a month. 15 million tool calls from MCP a day. We just shipped only a few weeks ago a V2 of our MCP server, which greatly reduces token usage, has hundreds more tools and availability.

So the ability to create work, to manage work on the Atlassian platform, to handle business processes and workflows from incident management and service to HRSM, all the way through software teams and strategy, people managing their goals and processes. Agents are able to use the Atlassian platform, and humans are able to understand the agents that are using the Atlassian platform and interact back and forth with them. And that's what we want to be, right? I totally think the subway station analogy or being part of the subway network, that's where Atlassian has philosophically done well in the past. It is where we build deep and meaningful customer relationships.

Our goal is to help you get things done as a customer. It is not to be in control of your world. It's your world. And I think that's landing really well, and you can see that in overall customers using Atlassian's AI technologies. The deep Rovo users are growing twice as fast as those that aren't. And obviously, we're adding to the pile of customers that are using AI heavily on a continued basis. So part of the reason we feel incredibly bullish about the future. I will say it's very easy to claim these things about AI. So I tell every single customer, put us to the test.

Take our Teamwork Graph, take our context graph, assess us against other people. I'll send you FDEs, I'll send you people to help. We will win that head-to-head battle. Test us. Secondly, don't believe everything you read in marketing and from any vendor at the moment. Test it. There's a lot of claims being made about agents and this and that. And we are asking customers to prove to themselves that we can do what we say we can do, and we stand behind all the engineering and the deep architectural and R&D investments we've made. This stuff is really hard.

This stuff is not simple to build, certainly not to scale to incredibly high levels of throughput when you add compliance and governance, hundreds of millions, if not billions of objects being processed simultaneously to try to give great answers. We have a truly unique AI platform, and it goes all the way up to the design and experience of how users use it. So I will say I feel incredibly bullish, and I would tell every customer, test us, we'll stand up against anybody.

James Chuong: And Allan, just to answer your question there, we haven't broken out that color, but I would just characterize it as modestly less than what we had expected in terms of impact. And I would just point you again to overall DC migrations to Cloud contributed that mid- to single -- mid- to high single digits to Cloud revenue growth this quarter.

Operator: Your next question comes from Keith Bachman from BMO Capital Markets.

Keith Bachman: I want to return to Gregg's question, James, to you. You actually had a reasonable beat on the quarter, maybe a little less Cloud and a little more DC, but you're raising the full year guide by less than the beat. That's unusual. And the message is you're less confident about the next 3 quarters. Is there anything that you can respond to that? And in particular, was there any pull forwards in the quarter? Or is there something on mix that we're not appreciating? But if you could just speak to why isn't the beat being passed into the year?

James Chuong: Yes. Thanks, Keith. So if you look at the Cloud revenue beat of $20 million, right, we're flowing through slightly more than that through the entire year there. And the mix that you're seeing, marketplace is also flowing through as well. It's really the Data Center side. So if you recall, the Data Center beat in Q1 is $33 million. But again, there's some timing effects related to the pull forwards of ASC 606 on the rev rec. So that's why you're not seeing the full total revenue sort of flow through from the Q1 beat through the year, right? So it's really sort of timing mechanics related to that.

Operator: Your next question comes from Koji Ikeda from Bank of America.

Koji Ikeda: With AMP, do you see the Teamwork Graph evolving from primarily a context layer into a broader coordination and interface layer for humans and agents? And how does that expand Atlassian's long-term opportunity?

Michael Cannon-Brookes: Koji, I'm going to guess that I'm taking that one. I don't -- I see them as sort of 2 layers. It gets a little nuanced and detailed here. The Teamwork Graph is the fundamental context layer underneath AMP and the Atlassian platform, and increasingly a lot of customer usage off the Atlassian platform. So that is taking all of your knowledge, your work. We're now semantically indexing the entire code base if you want us to, to give all of your agents fantastic answers and help them get the right information, getting high-quality answers, significant token savings.

And we are continuing the Teamwork Graph to do more and more inference on your knowledge to pull out objects that exist, so we can now infer things like projects and teams that aren't actually specified as objects, but we can see people working together. We are looking increasingly at inferring other things. So for example, we showed demonstrations of taking any agentic session that is in the Teamwork Graph and pulling out learnings to contribute to the very next session. So that's all about helping any agentic use case, any search use case, whether that's human search or agent search, if you want to think about it that way.

The Teamwork Graph is a large-scale knowledge graph, an ontology of everything your organization brings, highly customizable through Forge, through Assets, through lots of other technologies to get that data layer in a very AI-specific way with an incredible search engine and an incredible graph query engine, which are a little different, but both give great answers to agents, and agents are able to use them. AMP, think about it as more at the interface level for humans. It's more about experiences and designs. How do we bring all the agents that you're using on and off the Atlassian platform into workflows in ways that humans can cooperate with? Now underneath AMP are a lot of technologies.

So the Teamwork Graph, yes, MCP, A2A, so agent protocols to other tools. We're trying to bring that all together into a package. Again, maybe an interesting analogy, when you used the first iPhone, you didn't care about GPRS and GPS and 5G, third-generation WiFi, 2.4 gigahertz. All the technology standards were hidden inside the phone and just make a simple experience for you to use between Safari, between your phone, between mail, et cetera. AMP is about bringing all those agentic experiences into our products and off our products, and dealing with the modalities of how agents and humans are going to come together.

So think about it more as an experience layer that is across the Atlassian platform, but also helps inform third parties and how others will use our platform as well. So it's built on top of the Teamwork Graph. Long-term opportunity you asked about, I'm sorry about that. I think it continues to expand our long-term opportunity greatly.

I think we are, again, durable, profitable growth is about continuing to deliver for customers in every single one of our teams, leadership teams, service teams, technology teams, business teams, product teams, showing how we can deliver incredible value across more workflows, more business processes, structured and unstructured across your organization, and between the Atlassian platform and all of the other technology tools that you use. We are seeing that in customers as they understand how to utilize agents. Again, we have incredibly high AI usage on our platform because of things like AMP. Customers see that, and then they bring more workflows onto our platform.

Many of the customers I spoke to this quarter are massively increasing the number of workflows they run through the Atlassian platform, right, in the Service Collection space, moving off legacy vendors onto the Service Collection because of our AI features, and not just sort of we'll run your service tickets cheaper, but the way your agents are going to interact with that platform, how it all flows through and how service is integrated into the broader Atlassian platform to connect to your technology business teams and others. So I think it's -- obviously, we're investing very heavily in it, both at Teamwork Graph and AMP, because I think it shows a large and multiyear expansion opportunity for us.

Operator: Your next question comes from Rob Owens from Piper Sandler.

Robbie Owens: I wanted to ask on Rovo pricing and some of the thought process with the changes that are coming in December. And if we look at current consumption rates, is there any way you can somehow quantify what could be incremental here?

Michael Cannon-Brookes: Rob, yes. Let me talk to that. Look, the headline I would say is, as we've said repeatedly, and I hope it's coming through, the Teamwork Collection, and slightly less, the Service Collection, are the primary ways that we think about monetizing AI today. We are -- you get a largely increased token usage or credit usage. So you get 10x as many credits in the Teamwork Collection. It's now over 3,000 customers, up 7x year-on-year. And those customers are running twice as many agents. They're growing their seats significantly faster than non-Teamwork Collection and non-AI deep usage customers.

So that is our major motion, we believe, for delivering customer value, and then getting that value back for Atlassian in terms of monetization. That is really, really important that is understood. That continues to be our way. We are shipping a bunch of usage-based pricing or UBP features, with enforcement beginning in early December. We were talking to customers about that for a long time. That's about aligning value delivered, especially for extreme customer usage. It is not a near-term revenue driver. We've been very clear about that. That's in our guidance. We do not expect that to be a large revenue generation activity.

We are focusing our monetization efforts on continuing to grow to -- the previous question to Koji's question, bringing -- growing your long-term opportunity of more and more workflows running on the Atlassian platform through Teamwork Collection and Service Collection. UBP is about meeting customers where they're at. We're getting increasing questions around pricing and packaging, around controls, around understanding what that usage is, how they understand their credit usage, who's using it, which agents, which staff members, how that's flowing through and where they're getting value for that. And we continue to see that in lots of different places, in automation, in Rovo credits, in index objects, in Teamwork Graph queries.

So there's a lot of different meters inside usage-based pricing. But again, we're not assuming any meaningful UBP revenue in FY '27 at the moment. We're obviously continuing to work with customers, help them with their understanding. We've been very happy with the controls and offerings that we're showing today. And again, our goal is to have very generous credit usage. Two other things I wanted to say on the back of that. I think I'd give huge credit to our finance and engineering teams. Our gross margin is continuing to grow despite massively increased AI usage. That's a no mean feat. That's an incredible achievement from those teams. Up to 85.2%, 3% year-on-year, with AI usage greatly expanding.

That is our platform investments paying off. That is very strong collaboration between our finance and engineering teams, our infrastructure teams, on how we are blending models, how we're helping improve the token efficiency of AI features that we are delivering to customers, improving quality and cost simultaneously. Our AI Gateway continues to be there. We continue to show incredibly high quality in Rovo Chat, despite cost per chat coming down on a continual and ongoing basis.

So that's a huge credit to the team to do both of those things simultaneously, having the long-term opportunity to grow our customers in their workflows while expanding gross margins and delivering a significant AI value to customers in the core packages of Teamwork Collection, Service Collection, et cetera. And those customers continue to grow really strongly, as I've said.

James Chuong: And Rob, I would just maybe add to that. As Mike mentioned a little bit earlier, from an AI monetization perspective, what we hear from our customers is that they're looking for predictability and they're looking for the ability to load balance those tokens. And I think we sort of see this in the customer journey, right, as they upgrade from standard to premium, premium to enterprise additions, they're receiving 2 to 3x more Rovo credits at each turn. And ultimately, as they upgrade to Teamwork Collection, getting 10x more Rovo credits, right? So we're seeing that in our ARPU uplift. We're seeing that in the seat expansions as well, as customers continue to consolidate on that platform.

So again, important to meet customers where they are, but we really like the traction that we're seeing here.

Operator: Your next question comes from Arjun Bhatia from William Blair.

Arjun Bhatia: Perfect. Michael, I have a market structure question for you in terms of just how you think about growth going forward. Obviously, you've kind of delivered a lot of innovation on the platform. And I remember, I think, in the past in the enterprise, there used to be some maybe holdouts that wouldn't move to Jira that had custom-built systems. And I'm curious how you're seeing that evolve with how quickly AI is moving and how that's changing sort of the DevOps landscape? And just how do you think about the net new customer opportunity from here versus sort of expanding with the customers that you already have?

Michael Cannon-Brookes: Thanks, Arjun. How would I think about that? Look, I would say at the headline, there's a lot of parts to that question. Let me talk to the headline. I think the demand is extremely healthy. So we're seeing strong demand at the SMB level and at the enterprise level. We continue to see strong seat expansion that's very broad-based, business teams, software teams, service teams, which is, I think, excellent and reflects the -- maybe not the thinking about growth, as you asked, but the -- where that demand and growth is coming from. Again, we're a very patient and durable company in terms of building out real deep customer value over time.

You could see that, subscription ARR at 22.5%, Cloud growing north of 30%. As James mentioned, net retention, again, staying extremely strong, well over sort of the 120 mark and obviously, RPO at 44%. So very strong future growth indicators, I would say, and demand continues to be healthy. I think we're seeing extremely strong -- I'm not sure whether we talk about net new customers. Again, we have an awful lot of customers that -- our 10,000 customer number and overall customer numbers continue to grow strongly. We're seeing very strong momentum, for example, in both collections. So we talked about Teamwork Collections, over 3,000 customers, up 7x.

And Service Collection now passed 70,000 customers with ARR growing north of 30% and strongly taking share. So not necessarily net new customer opportunities, but existing customers continuing to grow strongly. There are many, many, many, workflows and processes within our existing customer base that are not currently on the Atlassian platform. And that's where those customers are expanding and bringing more workflows onto the platform. That continues to be an extremely healthy demand flywheel that we continue to deliver on features to bring in there. Customers north of 3 million growing at over 50% year-on-year rate, and those at 5 million level growing at 70% year-on-year rate.

So certainly, at the enterprise end, I think you can see very strong, healthy customer growth resulting in monetization as they bring more and more workflows on. And we continue to improve, I will say, like how we do that. So you're seeing all of that in lots of different places. I think Jira's role is incredibly important in that world going ahead. Structural workflows are very important. I think you're seeing more and more customers adopting the Teamwork Collection to get Loom and Confluence, to get projects and goals and some of the platform applications as those workflows increasingly become unstructured as well, as they bring agents into those workflows.

So I'm incredibly bullish on our opportunity for growth going forward. I hope you can feel that and hear that.

Operator: Your next question comes from Ittai Kidron from Oppenheimer.

Ittai Kidron: Guys, I wanted to ask about the Data Center. James, you kind of listed before early in your comments, a time line for government certifications, Impact 5, FedRAMP, Rovo. And those kind of seem like carry into late '27, '28, even touching on '29. So I guess it's obvious at this point that you're going to have an unsignificant part of your Data Center customer base remain in Data Center beyond the March '29 end-of-life notice.

So I guess my question is, one, can you -- is there a way for you to roughly quantify what percent of your Data Center business right here right now do you expect will remain "longer term" beyond the deadline of March '29, number one? And number two, is that figure greater than what you have potentially expected a year or 2 ago? I'm just trying to think if the conversion, the Data Center to Cloud conversion opportunity, might be smaller insofar what's remaining here, given that a not insignificant part of your Data Center business is just likely to stay on that platform for longer beyond March '29.

James Chuong: Yes. Thanks, Ittai. No, I would just say that and reiterate that our migrations continue to be on pace. Our customers are incredibly excited about the value they can unlock there, right? We talked about it earlier, Rovo threaded throughout Teamwork Graph, all the collections. And we see that in customers that move from Data Center to Cloud, right? 3 years hence, they're increasing their spend 1.75x. And so we feel really good about the migration pace that we're seeing right now. But again, important to make sure that we're meeting our customers where they are. And I also reiterated earlier that for the quarter, mid- to high single digits in terms of contribution to that Cloud revenue.

So all up, I think the announcements that we're making around the public sector side is just a recommitment to our customers and making sure that they have the visibility that we're going to be able to unlock all of that value for them as they continue to migrate.

Michael Cannon-Brookes: Ittai, if I might just add, and thank you to the amazing people at Atlassian who fed me the numbers, I've seen more than 100 customers in the last quarter in more than 11 different countries, in 4 different continents. So I have a lot of customer detail and knowledge about these types of questions, right? I think one of the things that give me the most strength on Data Center, we talk a lot about customers, talking about when and not if. I also think our history of delivery is incredibly impressive for those customers.

Many customers who I saw a year ago or 2 years ago, see the progress we've made in Isolated Cloud, in Government Cloud, in European data residency in various ways. I've been in Singapore, I've been in India, I've been in America, lots of countries in Europe. And whether that's in financial organizations, IT, telecommunications, large-scale automotive, all of those customers see the progress we've made, our delivery on the platform. And it's great that they see that. It's great that they're heading in the right direction.

I think importantly, it's their faith in the delivery going forward that is important and the realization of how difficult that is to do, delivering large-scale AI solutions that are European data resident with amazing design and experience on top, connected to the best Teamwork Graph and doing that all with bring your own key encryption, for example, and meeting various different standards. That's incredibly hard. I think that's a big moat for us. It's a big challenge for others to build at that scale and delivering a set of workflows that we're delivering. That's why customers are adopting more and more of the platform as they move more and more workflows onto that. So that's all coming through.

And fundamentally, you can see it. Look, the 44% RPO number is incredibly strong, continued to grow from last quarter, and we've had a series of strong quarters there, and 28% in current RPO as well. So that doesn't happen without recognizing that the value of that overall platform to continue to deliver for all of those customers around the globe. It's very exciting.

Operator: Thank you. And that concludes our question-and-answer session. I will now turn the call over to Mike for closing remarks.

Michael Cannon-Brookes: Thanks, everyone, for joining the call today. Thanks for those who came to Team '26 Europe a couple of weeks ago. I appreciate all the thoughtful questions and continued support. We'll continue, get cracking through fiscal 2027. So thanks to all the Atlassians out there and everyone else. Have a kick*** day and kick*** weekend.

This article is a transcript of this conference call produced for The Motley Fool. While we strive for our Foolish Best, there may be errors, omissions, or inaccuracies in this transcript. Parts of this article were created using Large Language Models (LLMs) based on The Motley Fool's insights and investing approach. It has been reviewed by our AI quality control systems. Since LLMs cannot (currently) own stocks, it has no positions in any of the stocks mentioned. As with all our articles, The Motley Fool does not assume any responsibility for your use of this content, and we strongly encourage you to do your own research, including listening to the call yourself and reading the company's SEC filings. Please see our Terms and Conditions for additional details, including our Obligatory Capitalized Disclaimers of Liability.

The Motley Fool has positions in and recommends Atlassian. The Motley Fool has a disclosure policy.