Team ’26 Anaheim – Key Atlassian Announcements

The most significant announcement at Team ’26 was Atlassian’s decision to open up the Teamwork Graph: customers can now connect third-party systems and business context into the Graph, without additional consumption-based fees.

The Teamwork Graph is Atlassian’s underlying data and relationship model that connects work, people, knowledge, assets, and activity across the Atlassian ecosystem. Atlassian now positions it as the foundational context layer for enterprise AI.

Supported integrations include platforms such as Microsoft Teams, SharePoint, Google Drive, GitHub, and other external systems. Atlassian wants customers to connect freely to get the maximum value out of Rovo. The more context lives in the graph, the more capable Rovo becomes.

Visit https://teamworkgraph.com to "experience the invisible " and see your own Teamwork Graph size.

Since February 2026, Atlassian started rolling out Assets to be included in Standard Plans for Service Collection.

Over time, Atlassian plans to extend access to other Atlassian products and collections, including Jira and Confluence (Standard and above). Advanced capabilities, though, such as Assets Data Manager will remain tied to Premium and Enterprise editions.

What we also learned during the conference:

• Rovo memory has been significantly improved over the last 6 months, now with two layers: Rovo observations and direct input memory.
• The connector capabilities have been expanded, including indexing of Microsoft Teams transcripts and image text extraction in Google Drive.
• There are new code intelligence capabilities spanning GitHub, Bitbucket Cloud, and Bitbucket Data Center repositories.
• An open beta MCP server allows any external AI applications that you may use to access Teamwork Graph context. Atlassian reported internal benchmark results showing higher-quality AI responses while reducing token usage when Teamwork Graph context is available.
• There is a Teamwork Graph CLI (Open Beta), including an option to visualize the graph. Watch Teamwork Graph through the Dia browser.

AI capabilities were present throughout nearly every product announcement at Team ’26. A recurring theme was the transition from AI assistants towards operational AI agents capable of participating directly in workflows.

Several important updates were announced for Rovo:

• Rovo now asks for input when it needs it. Previously if a thinking fork was 50-50, Rovo would make a choice that proved sometimes wrong. Now, Rovo will ask user input when its confidence drops. This is similar to how Claude works.
• Rovo Plan generates implementation plans, and will even propose new whiteboards if existing ones no longer match context.
• Rovo desktop entered Open Beta!

These developments reflect Atlassian’s ongoing effort to make Rovo more interactive, context-aware, and integrated into day-to-day collaboration

Atlassian now presents Jira not only as a work management platform for teams, but increasingly as a coordination layer for both human contributors and AI agents.

Several new capabilities were announced:

• Agents in Jira is now generally available.
• Agent Briefings (a "Loom-style record for AI"): record a briefing in Loom, and AI produces an action plan with linked Jira work items.
• Agents can be linked to Kanban columns to automatically pick up tasks. Drag Jira work item to a Kanban column assigned to an agent, and Jira agent picks it up (e.g., design → code → build → done).
• Agents work directly in Jira tickets, ask for input when needed, and can be corrected just by talking to them.
• You can also simply assign agents to tasks.
• Jira agent in other apps (e.g., Slack): tag and ask to create items from the chat.
• Continue work on tickets on the go by talking to Rovo when an agent needs input.
• Example workflow: Jira tasks auto-picked up by Claude Code → auto-built → put in review for human approval.
• An AI Planner in Jira is coming soon.

For Confluence, the most visible announcement was Confluence Slides. This new capability allows users to generate editable presentation slides directly from Confluence content using AI, while preserving company styling and formatting. Atlassian indicated that the feature will enter beta this month.

Team ’26 also included several important announcements for Jira Service Management and the broader Service Collection.

Customer Service Management (CSM) now extends beyond traditional ticketing workflows with support for WhatsApp, SMS, and native voice interactions. Atlassian demonstrated AI-backed workflows capable of resolving tickets automatically before escalation to a human agent becomes necessary. Also included is a seamless handoff between AI and human support channels, even mid-conversation. When a human agent takes a call, they get suggestions for fixes from AI and a live transcript.

Additional operational capabilities that were announced include:

• An Incident Command Center in JSM kicks off Rovo Ops when an incident comes in, analyzes it, looks for root causes, and auto-updates status pages. Customers using the Service Collection are saving 55 minutes on average per incident.
• An Incident Prevention Center works proactive: auto-reviews change requests, looks up dependencies, changes calendars, and runs a risk assessment.
• Added hardware asset management.
• The data manager gets a visual refresh.
• Rovo-assisted provisioning of configured JSM environments via Solution Composer.
• Rovo Service hands off work directly to Rovo.

These updates reinforce Atlassian’s strategy of consolidating service management, operations, AI, and asset management into a unified platform approach.

Several announcements focused specifically on governance and enterprise administration.

New capabilities include:

• Rovo Analytics (Beta) brings natural-language questioning and dashboard generation.
• Analytics adds Data Catalog, Business Glossary, and Quality Monitoring. These components were developed by Secoda (acquired last year) and are now fully integrated into the platform.
• Atlassian Guard Scan auto-finds and redacts confidential data, including historical data, and auto-applies classification labels and controls access. This is key to prevent sensitive unprotected data from being found quicker than before with AI.
• Atlassian Guard for Rovo Chat auto-redacts sensitive information that users put into AI.
• Atlassian Guard for Rovo Connectors: protects data from third-party connectors.
• Studio: now shows all agents in a single admin view.

These announcements acknowledge a growing concern among enterprises: ensuring that AI capabilities remain aligned with governance, data protection, and compliance requirements.

From a Brainsquare perspective, Team ’26 confirmed three major trends:

• Atlassian is rapidly evolving into an AI-native platform.
• Organizational context and connected data are becoming strategic assets.
• Governance, security, and operational integration are becoming increasingly important alongside AI adoption.

For many organizations, the challenge will no longer be whether AI capabilities are available, but how to introduce them in a controlled, valuable, and sustainable way within existing operating models.

Brainsquare continues to support customers in evaluating these evolutions, assessing platform impact, and translating Atlassian’s roadmap into practical implementation strategies.

If you would like to discuss any of these announcements or assess their impact on your environment, feel free to contact the Brainsquare Atlassian team.