Atlassian

AI at work has a physical dimension that almost no one is talking about. Across industries, companies have spent the last two years accelerating individual productivity with AI. Drafts get written in seconds. Code gets reviewed in minutes. Research now takes days, instead of weeks. And yet teams don’t feel faster. Decisions still stall. Projects still drag on. The bottleneck hasn’t disappeared, it’s just moved elsewhere.

Your AI strategy is only as good as your data security foundation AI makes your organization’s knowledge easier to find and use. That’s the whole point. But it also means sensitive data moves faster, surfaces in more places, and becomes harder to track. The pressure to act is real, but the playbook isn’t new. You still need to know where sensitive data lives, govern how it’s being used, and prevent it from unauthorized exposure.

Less than six months ago, the Atlassian Rovo Model Context Protocol (MCP) server went GA, giving Claude, Cursor, and every major AI agent direct access to Atlassian for our customers. Today, over one million users trust it every month to do real work through agents. But that number isn’t the story. The story is what’s happening inside those interactions: how AI agents are actually being used at enterprise scale, and who’s getting the most value.

Adopting AI technology without an effective strategy is costing the Fortune 500 an estimated $161 billion a year.* Enterprises are making big investments in this space but are struggling to realise the returns. We know the technology is designed to make businesses more efficient, but we’re still seeing the opposite because most businesses are treating AI as purely a technology transformation. That’s where they get stuck.

Earlier this year, we introduced the beta version of the Bamboo to Bitbucket Pipelines migration tool. Since then, we’ve listened closely to your feedback and expanded its capabilities to make your transition to the cloud smoother. We are thrilled to announce the general availability (GA) version of the Bamboo to Pipelines migration tool.

Government technology teams face a growing mandate: modernize faster, strengthen security, and prepare for an AI-powered future all without disrupting mission-critical systems. To help agencies meet these demands, Atlassian and Amazon Web Services (AWS) have expanded our Strategic Collaboration Agreement. Together, we’re delivering public sector teams cloud native capabilities to modernize at speed on trusted AWS infrastructure.

The best ideas often come from false starts, conflicting opinions, and rapid iteration. Teamwork is messy, and AI might make it even messier. But the Chief Design Officers of Atlassian and Figma are designing for that reality to turn friction into a creative edge. In this conversation, Charlie Sutton (Atlassian) and Loredana Crisan (Figma) discuss why design shouldn’t eliminate the “mess” of collaboration, but rather the friction surrounding it—like busywork, duplicate effort, and tool sprawl.

As AI takes on more of the work around people decisions, our opportunity is to become fully present in the moments that define them. We believe this is a once-in-a-career moment for the HR craft.

Turn Slack threads into agent-ready Jira work items, without leaving the conversation. The Jira Cloud for Slack app is already one of the top five apps in the Slack Marketplace, trusted by 3.5 million people every month. Today, it gets a whole lot smarter. You can now mention @Jira in any Slack channel to create a Jira work item right from the conversation you’re already in.

How specialist agent orchestration anchored to Jira keeps complex coding tasks on spec. You have probably felt this. You hand a capable AI agent a real piece of work, a proper spec with edge cases and acceptance criteria, and for a few minutes it is sharp.