Thousands of companies across the globe use Atlassian’s collaboration tools—which include Jira, Confluence, Trello and Loom—to work together and manage projects. I talked to President Anu Bharadwaj about how Atlassian serves companies’ tech and AI needs, the culture at the 22-year-old company—which is still founder-led, and its growth prospects.

This interview has been edited for length, clarity and continuity. It was excerpted in the Forbes CEO newsletter.

How are things going at Atlassian?

Bharadwaj: Overall, I’d say it’s going great. At Atlassian, we’re a company of builders, so we are really building our way through the next phase of growth for ourselves. We’re right now at about a $4.5 billion run rate. We’ve been fortunate enough to get to this point over the last decade or so of being a public company. The way we think about the future at Atlassian is how can we continue to build products and services that can really unleash the potential of teams. We think a lot of teamwork, people working together in different contexts—whether you’re a team building a Mars rover, or a team building physical things [or] virtual things. We think a lot about collaboration. It’s an exciting time to be in this kind of business to be pursuing this mission, especially given all the technology that is now available to fulfill the mission.

Atlassian President Anu Bharadwaj.

What are you seeing in the way of AI demand from enterprises, and what are you doing to meet it?

AI demand for enterprises has gone through a bit of a crest and a trough over the last year and a half. Atlassian builds a lot of collaboration software—mostly things like project management tools, knowledge management tools like company intranets, wiki or tools like Trello, Jira. We announced over the last year a number of AI-driven offerings in our portfolio. One, Atlassian Intelligence, really helps users in the workflow of project management, of writing content, writing articles or sharing collaborative documents with their teams. We brought a lot of AI features in the middle of that workflow to help summarize, edit your content, figure out how to draw information from multiple sources and answer a question that a new employee might have. We built that into the platform.

In addition, we have an AI-centric offering that we call Rovo, which really helps teams build agents which can automate and take the next step and action in a smart and intelligent way in any use case that they might be operating in.

I’ve worked at Atlassian for 10 years. When we launched it 18 months ago, it was the most positive reception that we’ve ever received across our products. We have millions of users on an active basis. Enterprises, especially, were battling with the problem of: We have a lot of information and a lot of data across the company, but how do we really make use of this? How do we make this accessible and actionable to all of our employees? The two offerings across Atlassian Intelligence and Rovo helped answer that particular question for our enterprises.

We’ve already seen several thousands of customers adopt our AI products. As a technologist, I feel like this is amazing that enterprises are [not just] seeking these sorts of tools, but adopting them at speed. Because, as you know, large companies can be slow at adopting new technology, but I’ve been very positively surprised by how quickly companies are starting to adopt it.

The one thing that I would say is different over the past years is more and more enterprises and now asking specific questions about what are the use cases where this is going to make my team productive? And where, specifically, do you see this being additive? Where specifically do you see this being a complete automation replacement of certain workflows? And how many of these tools do I actually need?

I think there’s also been a bit of a trough of disillusionment. Companies have bought into large packages that seek to AI-ify everything they do.

You said you’ve seen AI enthusiasm peak and also go down into a trough in the last 18 months. What has brought it down, and where are things right now?

Initially when the technology wave broke out, there was a lot of promise around what can AI do. It’s hard to predict timelines. But when people talked........

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