‘Astonishing’: Atlassian survives generative AI fears, surges 32 per cent after results released
📅 Aug 12, 2026News249 MIN1502 VIEWS18 SEGMENTS · 2 SPEAKERS
Atlassian CEO and Co-founder Mike Cannon-Brookes has commented on his company’s 32 per cent share surge after its results were released last week.
What Michael Cannon-brookes said
Written from the verified transcript and checked against it. Every figure links to the moment it was said.
Michael Cannon-Brookes said generative AI fears about Atlassian were overstated, arguing that AI has helped the company deliver more customer value, leading to larger and longer deals. He emphasized that software is more than code, and that Atlassian uses AI itself to improve products. He noted the company uses more than 70 AI models in production, blending them rather than building foundational models, and has no capital expenditure on data centers or chips. He explained that AI requires context, which Atlassian provides through its Teamwork Graph. He addressed the layoffs of 1,600 staff, calling them difficult but necessary for durable, profitable growth, and cited strong financial results: revenue up 28% in the quarter, cloud growth over 30%, and long-term commitments up 44% to about $4 billion.
Key takeaways
Atlassian's revenue grew 26% to $6.57 billion, with a quarterly profit of $139 million.
Cloud business grew north of 30%, and long-term commitments (ACVs) grew 44% to about $4 billion.
Atlassian uses more than 70 AI models in production, blending them rather than building foundational models.
Atlassian has no capital expenditure on data centers or chips, renting compute instead.
Layoffs of 1,600 staff were difficult but necessary for durable, profitable growth.
0:00Is there a lesson here in people being too quick to judge companies that might otherwise have been affected by generative artificial intelligence?
1:41And that's really in some ways the defense of Atlassian, isn't it?
3:18Okay, so does it also enable you to be able to sell even more products to your customers, to make their experience even better, to provide more solutions to them?
4:12Do you have to keep on spending in order to get those returns, or is the situation where you can incrementally add to what you've already got?
8:02Is that the way in which we should look at that?
So, let's get to those Atlassian results out Friday our time. For a company that some thought would be mortally wounded by generative artificial intelligence, it was simply astonishing. In the past year, Atlassian's revenue grew by 26% to $6.57 billion. For the year, its loss narrowed from $256 million to $53 million. But more important, in the quarter to June 30th this year, Atlassian made a profit of $139 million. It seems that a big corner has been turned. And that caused a huge rebound in Atlassian share price on Friday, a hit more than 30% after the release, adding around $10 billion to the company's value. So, let's get to the reasons behind this turnaround and whether it's a lesson that AI doesn't necessarily kill off a range of companies. Mike Cannon-Brookes is the chief executive and co-founder of Atlassian and joins me now. Mike, many thanks for your time. Is there a lesson here in people being too quick to judge companies that might otherwise have been affected by generative artificial intelligence?
I think that's probably a fair lesson to take away, yes. I think artificial intelligence or AI adds a lot of value to a lot of businesses. In our case, we had an incredible quarter capping off an incredible year because of the capabilities we've added to our software that deliver incredible customer value. And that customer value is largely being delivered by AI. So, customers are voting with their feet to sign longer, bigger deals with Atlassian for more seats. More parts of their business are using us. So, I think yes, the simplistic narratives aren't particularly useful.
So, the idea was that maybe a lot of your coders would be really fundamentally in difficulty in terms of their employment in the future because of the change in generative artificial intelligence. People who use code know it generates code. But the fact of the matter is that in many cases your clients had a suite of products and literally a platform that they were used to using. And that's really in some ways the defense of Atlassian, isn't it?
Look, I think there's two important points to make there. One is software is not code. Software is a solution to a problem a customer has. Software is a whole set of services, the humans that go behind helping the customer to achieve those outcomes. So there are a lot of things in terms of what customers are buying from software. They're also buying us improving it every single week, every single month, and making it better to solve more of their problems. All of those things stay true in the world of AI. Secondly, that AI that's going to be disruptive to software company narrative seems to forget the fact that software companies themselves have AI. So we have increased our pace of delivery, we solve more customer problems, we solve them cheaper, we solve them better than we ever have.
And we do that because we have access to the exact same AI, right? And we're actually pretty damn good at writing software, pretty damn good at solving customer problems. So in a way, think about it in reverse, that AI enables us to solve more customer problems more quickly, and hence it's very good for our business. I've said from the start, AI is one of the best things to ever happen to Atlassian, and I continue to believe that.
Okay, so does it also enable you to be able to sell even more products to your customers, to make their experience even better, to provide more solutions to them?
Absolutely, right? That's exactly what it allows us to do. Our platform as a whole, the Atlassian platform writ large, Rovo, our AI offerings, our teamwork graph, which is our knowledge graph, it's the best source of enterprise organizational memory across all of the applications in your history. All of those tools are made with AI and very smart engineers around the world that have worked incredibly hard to build things that really solve customer problems. So, we can use that AI to solve more customer problems more quickly, to launch more products, to improve the quality, speed, performance of those products, and customers again are staying with us for longer and larger times.
Okay, so one of the things that a lot of the large AI-related companies have been caught up with now is almost a race to spend capital to really build out the AI capabilities. In your case, is that an issue? Do you have to keep on spending in order to get those returns, or is the situation where you can incrementally add to what you've already got?
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Cannon-brookes, M. (2026, August 12). ‘Astonishing’: Atlassian survives generative AI fears, surges 32 per cent after results released [Interview transcript]. News24. CEOInterviews.AI. https://ceointerviews.ai/interview/1216958/
MLA
Michael Cannon-brookes. "‘Astonishing’: Atlassian survives generative AI fears, surges 32 per cent after results released." News24, 12 Aug. 2026. Transcript, CEOInterviews.AI, https://ceointerviews.ai/interview/1216958/.
BibTeX
@misc{cannonbrookes2026_1216958,
author = {Michael Cannon-brookes},
title = {‘Astonishing’: Atlassian survives generative AI fears, surges 32 per cent after results released},
howpublished = {Interview transcript, News24. CEOInterviews.AI},
year = {2026},
month = {aug},
url = {https://ceointerviews.ai/interview/1216958/},
note = {Speaker-attributed transcript with timestamps}
}
