Atlassian Corp. today unveiled a sweeping set of artificial intelligence updates at its annual Team ’26 conference, headlined by the broad opening of its Teamwork Graph and the evolution of its Rovo AI assistant from a helper into an agent that can plan and execute multistep work autonomously.
The company said the Teamwork Graph, which it describes as a living shared context layer connecting people, projects, documents and decisions across Atlassian and third-party tools, now contains more than 150 billion connections. Atlassian is also opening the graph to outside agents and tools through two new interfaces in open beta: a Teamwork Graph command-line interface for developers and Teamwork Graph tools delivered through Rovo’s Model Context Protocol server.
The CLI, with more than 300 commands, lets coding agents such as Anthropic PBC’s Claude Code and Cursor query work and relationships across Atlassian products through a single interface rather than stitching together individual product application programming interfaces. The MCP integration allows any compliant assistant, including third-party tools, to read from and write back to the graph.
Atlassian said its own benchmarks show that grounding AI responses in Teamwork Graph data delivered 44% more accurate results while using 48% fewer tokens.
Teamwork Graph Connectors built on Atlassian’s Forge platform have also moved to general availability to allow customers to pipe data from proprietary or legacy systems into the graph with permissions intact.
On the Rovo side, Atlassian said customers performed more than 14 million Rovo-assisted actions in the past month and that agentic automations across its platform are up sevenfold over the past six months.
The company is adding a new reasoning mode called Max to Rovo Chat, available soon in early access, which breaks complex requests into multistep plans, executes them across connected tools, and loops users back in for review. Rovo Studio, a no-code environment for building agents and automations grounded in the Teamwork Graph, is now generally available with built-in roles, approvals, versioning and audit controls.
Atlassian says that more than 90% of its enterprise cloud customers are now using Rovo.
The company also announced expansions across its product collections. Agents in Jira are now generally available and can be assigned work items with full audit logging. Jira Product Discovery Enterprise reached general availability with portfolio-level governance and a new Feedback capability for capturing customer signals entered early access. A new Incident Command Center unifies incident detection, investigation and resolution with Rovo-assisted root-cause analysis and Rovo Service offers autonomous or supervised Level 1 support.
A new product called Dia Reports that generates proactive browser-native briefings such as interview prep documents and decision memos by combining Teamwork Graph context with everyday tools was also announced today. Atlassian said the feature is designed to surface personalized reports before users ask for them, reducing the need for prompting over time.
For engineering teams, Atlassian introduced Agent Experience for measuring how agents interact with codebases, AI Code Insights for tracking AI-generated code at the commit level and AI Pulse for surfacing productivity signals to engineering managers.
Atlassian also bolstered its administrative tooling for managing AI at scale.
Announced today, new org-wide agent lists give administrators a live inventory of who built which agents, where they are running and how often they are used. Permissions for AI access and agent building can now be separated, allowing broader usage without uncontrolled agent sprawl. New dashboards and audit logs track AI adoption and credit consumption and policies governing what third-party data Rovo can ingest sit alongside controls for data residency and Atlassian-hosted large language model selection.
“Rovo and Atlassian’s Teamwork Graph are the connective spine, pulling together Jira, Confluence, JSM, Slack, email and more, so agents can reason across all of it,” Matthew Hargreaves, head of product delivery and automation at Lendi Group Pty. Ltd., said in a statement. “That’s what takes us from AI hovering at the edges to AI embedded in the core of how the organization operates.”
Andrew Boyagi, customer chief technology officer of Atlassian, spoke with theCUBE, SiliconANGLE Media’s livestreaming studio yesterday, discussing why AI agents need organizational context to deliver value and how Atlassian is applying developer experience principles to enterprise productivity.
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