Atlassian in the AI stack

The business and what the filings show

Atlassian makes Jira, Confluence and other tools that software, IT and business teams use to plan and track work, priced mainly per user. Over its latest four quarters it reported $6.6B of revenue, +26% on the year before, at an 85% gross margin and a 0% operating margin, while free cash flow was $1.3B: the gap between the two is mostly stock-based compensation, a large non-cash cost.

Atlassian is in the middle of a platform move. In September 2025 it announced the end of life of its Data Center products, which customers run on their own servers; since March 2026 it no longer sells them to new customers. Its AI offering, Rovo, runs on the Teamwork Graph, the data Atlassian holds on how its customers’ people, projects and documents connect, and works in its cloud, which is part of why Atlassian is moving customers there.

Per-user pricing exposes Atlassian to the same question as Salesforce and Workday: if AI agents write code and manage tickets, do customers need fewer seats? Its 10-K adds a cost risk: providing AI tools at no or low cost to most cloud customers could raise hosting costs without matching revenue. Gross margin through the cloud migration is the number that would show it.

How AI shows up in the numbers

AI shows up at Atlassian as Rovo and AI features across Jira and Confluence, much of it included in cloud plans rather than sold separately. That makes the cloud migration and gross margin the places to read AI’s effect: it helps if it speeds migrations and justifies higher cloud prices, and hurts if its hosting cost rises faster than revenue.

For scale, Atlassian’s revenue over the latest four quarters equals 1% of the $566B the five largest buyers spent on capital projects over their latest four quarters. Their capex rose +81% on the year before, while Atlassian’s revenue grew +26%: slower than the spending, so it is capturing a smaller share of each new capex dollar, or more of its business sits outside the build-out.

How it talks about AI

In its latest earnings release, furnished to the SEC on August 6, 2026, Atlassian mentioned AI 23 times in 2,215 words of narrative text, about 10.4 mentions per 1,000 words. Of its 17 sentences about AI, 1 included a number: a revenue figure, a growth rate, a customer count or another measurable result. Across the 8 releases we read, back to October 31, 2024, AI mentions per 1,000 words went from 2.4 to 10.4.

Specific claims are easier to check against the numbers than general enthusiasm, which is why the share of AI sentences that carry a figure is worth watching alongside how often AI is mentioned. The sentences below are quoted from the release as published, after removing safe-harbor text and company boilerplate.

• “Atlassian Announces Fourth Quarter and Fiscal Year 2026 Results Quarterly revenue of $1,766 million, up 28% year-over-year Quarterly cloud revenue of $1,213 million, up 31% year-over-year Subscription ARR of $6,606 million, up 23% year-over-year Remaining performance obligations of $4,817 million , up 44% year-over-…”
• “In the AI era, context is the edge but it's hard to build and can't be hired.”
• “Thanks to 25 years of connecting teams, customers get one of the best context graphs for orchestrating agentic workflows.”

Source: earnings release (Form 8-K, Exhibit 99.1), August 6, 2026.

The trend in the numbers

Since the start of 2023, Atlassian’s largest quarter by revenue was Q1 2026 at $1.8B, and its highest gross margin was 87% in Q2 2026. The latest quarter was below that peak.

Quarter by quarter, Atlassian’s revenue grew +21% in Q3 2025, +23% in Q4 2025, +32% in Q1 2026, +28% in Q2 2026 on the same quarter a year earlier. Growth has been accelerating.

Gross margin in the latest quarter was 87%, against 83% a year earlier, so it is keeping more of each dollar as it grows. Operating margin moved from −2% to 12% over the same span. Over the latest four quarters it turned 21% of its revenue into operating cash flow and spent 1% of revenue on capital projects, against 1% a year earlier.

Where it sits in the stack

Atlassian sits in the software and applications layer of the AI stack. It sits at the top of the stack, where revenue from end customers has to come from; its own spending flows to AI clouds.

Among the 27 companies in this layer on our map, it ranks number 9 by revenue and number 7 of 27 by revenue growth. Its gross margin of 85% compares with 78% for the layer as a whole, a sign that it keeps more of each dollar than its neighbors. The full layer analysis is on the software page.

Latest four quarters for 10-Q filers; latest fiscal year for 20-F filers. Companies under $100 million of revenue are left out.

Against the 27 US-listed companies in its layer, Atlassian grew +26% over the latest year versus +19% for the layer combined, and converted 20% of revenue into free cash flow versus 33% for the layer. It is taking share of the layer’s revenue.

What has to go right, and what could go wrong

What has to go right. Customers have to move to Atlassian’s cloud and pay more there, with Rovo a reason to do so, while AI makes teams more productive without reducing the seats they buy.

What could go wrong. If AI coding and project agents shrink the number of people who need Jira seats, or AI-native tools replace Atlassian’s workflows, the cloud migration could happen at lower revenue per customer.

These describe the conditions the business depends on, as the filings show them. They are not a view on the stock.

Through the lens of Investing in AI

Rob May’s book offers six mental models for telling AI moats from traps. The one most useful for Atlassian’s layer is “AI challenges traditional SaaS assumptions”: Per-seat pricing, zero marginal cost, smooth ARR curves, and automatic land-and-expand break down when software does work on your behalf. The mistake is not using SaaS instincts. It is using them automatically.

The question it asks of any company is: What work is this product actually doing, and how does pricing map to it? Applied to Atlassian, the filings on this page are the place to start: the margin trend shows whether it holds scarce value or passes it through, the customer and financing disclosures show who it depends on, and the commitments show what it has promised before the revenue arrives.

Customers and concentration

US companies must disclose any customer that accounts for 10% or more of revenue, and foreign filers usually describe their largest customers. Concentration matters because a company’s growth is only as durable as the handful of buyers behind it, and in the AI stack those buyers are often the same few companies.

• “rs ended June 30, 2026, 2025, and 2024, no customer represented more than 10% of the total revenues.” 10-K, August 14, 2026

Commitments and backlog

• Backlog. Atlassian reports $4.8B of remaining performance obligations, 0.7 times its revenue over the latest four quarters: contracted revenue not yet earned.
• Purchase commitments. $960M of unconditional purchase obligations as of June 30, 2026 (10-K): what it has contracted to buy from its own suppliers.

What to watch

Atlassian’s next quarterly report will cover the quarter ending around September 29, 2026. Large companies must file a 10-Q within 40 days of a quarter’s end and a 10-K within 60 days of the fiscal year’s end, so the new figures should arrive by about November 28, 2026 at the latest. This page, the layer pages and the next quarterly report all update from that filing.

• Revenue growth through the Data Center end of life, as customers move to cloud or leave.
• Gross margin, where the hosting cost of AI tools would show.
• Remaining performance obligations, a read on how many customers commit to the cloud for multiple years.
• Its place in the next quarterly AI Stack Report, which updates every company on the map from the new filings.

Figures from Atlassian’s SEC filings, latest period ended June 30, 2026. Other companies: all company pages.