# Atlassian Team '26 Recap: The Shift to the AI-Native Organization and the Role of the Teamwork Graph

> All the key announcements from Atlassian Team

Source: https://www.xalt.de/en/blog/atlassian-team-26-recap-teamwork-graph/

All the key announcements from Atlassian Team '26 at a glance: Teamwork Graph, Rovo, and the Teamwork, Service, Product, Software, and Strategy Collections.

TEAM XALT Atlassian Platinum Partner · 20 May 2026 · 14 min

Imagine your company had a perfect memory. Every decision, every snippet of code, and every piece of customer feedback would be immediately available to every employee (and every AI). It became clear at Atlassian Team ’26 in Anaheim: this is no longer a distant future. Atlassian is ushering in the era of the “AI-native organisation”.

XALT was on the ground to sort through the flood of innovations for you. The key insight: pure AI intelligence is now a commodity. The real competitive advantage lies in **context**.

> The success formula of Team ’26:
> Acceleration = Context x Intelligence

In the following, we go into detail on these innovations and show you what they mean for your business.

## The Teamwork Graph: Context is everything

AI agents are only as good as what they know. The problem: information is often trapped in silos. The **Teamwork Graph** solves this by creating over 150 billion connections between people, goals, code, and content.

> The new success formula for businesses is: Acceleration = Context x Intelligence. Those who have their data in the Teamwork Graph under control will win the AI race.
> **Mike Cannon-Brookes, Atlassian CEO & Co-founder**

Tests show: With this context, agents deliver 44% more precise answers with 48% less token consumption.

New developments regarding the Teamwork Graph:

- **Teamwork Graph CLI (available as a beta version):** Developers can now pull graph context directly into their terminals and CI/CD pipelines. With over 300 commands, coding agents such as Claude Code or Cursor can make complex queries (e.g., “Who is the true owner of this decision?”) without having to query APIs individually and laboriously.
- **Rovo MCP Server (available as a beta version):** Via the Model Context Protocol (MCP), the Teamwork Graph becomes accessible to *any* compatible agent (e.g., ChatGPT or Claude). Agents can not only read the graph but also actively update it.
- **Integrate your own data (Forge Connectors generally available):** Via Atlassian’s developer platform Forge, companies can now build their own connectors for proprietary legacy systems. **Mercedes-Benz** is already using this to link specialised automotive systems (defect management, requirements). The result: **90% better quality** in defect capture and a **10-times faster software delivery**.

![Diagram of the Atlassian platform: a semicircle with the Service, Software, Teamwork and Strategy collections, below it Rovo with Teamwork Graph and Forge](https://cdn.sanity.io/images/c475o02b/production/ab1b81b12c6baf9740575dbf881c649586b187f6-2611x2157.png?w=1504&q=75&fit=max&auto=format)

100 out-of-the-box Konnektoren können nun mit dem Teamwork Graph verbunden werden.Die zusammenfließenden Informationen schaffen den wertvollen Unternehmenskontext auf dessen Basis KI Unternehmen dabei unterstützt ihre Prozesse drastisch zu beschleunigen.

## Rovo: From AI assistant to autonomous team member

Rovo is the link that brings the Teamwork Graph to life in everyday work. With over **14 million Rovo actions** in the last month alone, the tool has firmly established itself. At Team ’26, the next level was now ignited:

### 1. Rovo Studio (generally available)

From now on, anyone (not just developers) can create their own AI agents, automations, and apps. Without writing a single line of code, you can design workflows that react to events (e.g., “A new employee starts” or “A Prio-1 ticket is opened”) and coordinate tasks across Jira, Confluence, and third-party systems.

### 2. Rovo Chat “Max” (coming soon)

The new reasoning mode “Max” not only answers questions but creates a **multi-stage action plan**. It breaks down complex requests, pulls status information from Jira, decisions from Confluence, and signals from support. It drafts documents, creates slides, updates Jira tickets, and even finds appointments in the calendar, while you focus on the final decisions.

### 3. Enterprise Governance & Control

Rovo now offers comprehensive admin controls. There are central lists of all active agents in the organisation, detailed audit logs, and granular permissions for who can build or run agents. In addition, **Atlassian Guard** ensures that sensitive data remains protected.

### 4. Rovo everywhere

Whether in the browser, on the desktop, on mobile, or directly in your favourite apps via MCP (Model Context Protocol): Rovo brings organisational memory exactly where you need it.

## Teamwork Collection: AI orchestration directly in the workflow

The [Teamwork Collection](https://www.xalt.de/en/blog/atlassian-teamwork-collection-remote-collaboration/) is about bringing AI agents to where the actual work happens. Moving away from separate chat windows towards direct collaboration within the ticket or on the page.

### 1. Agents in Jira (generally available)

AI agents are now full team members in Jira. You can assign Jira issues directly to an agent. It appears as an assignee on your board, so you can see at any time which tasks are currently being handled by an AI and how they fit into your sprint or release plan.

- **Collaboration via @-mention:** Instead of copying context to separate tools, you bring the agent directly into the comments of a ticket via @-mention. It can summarise long comment threads, conduct research, or propose solutions. The entire history remains documented in the ticket for everyone.
- **Automation in the workflow:** You can integrate agents firmly into your Jira workflows. For example, an agent can automatically become active as soon as a ticket reaches the status “In Design”, create a first draft, and make it available for human review.
- **Open ecosystem (MCP)**: Thanks to the open standard (Model Context Protocol), you can not only use Rovo agents, but also integrate specialised agents from third parties such as GitHub Copilot, Figma, Canva, or HubSpot. Jira respects all existing permissions and ensures a seamless audit trail.

### 2. AI Planner in Jira (coming soon)

The Atlassian AI Planner supports teams with automated sprint and capacity planning. Based on historical data, team availability, and task priorities, it creates optimised project plans and suggests the best distribution of tickets. This saves valuable time in weekly planning and helps teams identify bottlenecks early and set more realistic deadlines.

### 3. Third-Party Agents in Confluence (available as beta version)

You can simply tag AI agents (e.g., from Lovable or Replit) on a Confluence page via @-mention, just like a human colleague. The agent reads the context of the page and performs actions in your connected tools without you having to leave the page.

### 4. Remix with Rovo (available as beta version)

Long texts can be visualised in seconds with Remix. Simply highlight a section of text in Confluence, and Rovo automatically creates diagrams, timelines, infographics or org charts from it. As visual content is proven to be read twice as often, you massively increase the reach of your documentation.

### 5. Confluence Slides (available as a beta version)

Create presentation-ready slides directly from your Confluence content. Rovo uses the Teamwork Graph to define the structure, write the content and even build visualisations. You can even present the slides directly in Confluence without switching tools.

### 6. Create with Rovo in Jira (available as a beta version)

Rovo automatically converts meeting notes, emails or Confluence docs into structured Jira issues (e.g., Rovo creates work items in Jira, writes status updates and breaks down extensive tasks into smaller subtasks).

### 7. Loom integrations

- **Agent Briefings in Loom (soon available as a beta version):** Instead of writing complex prompts, you simply record a Loom video. What you say and show is translated into a structured action plan and can be imported directly into Jira.
- **Bug Reporting (generally available):** Instead of painstakingly typing bug reports, you record a short video. Loom automatically detects the technical background (logs, environment variables) and creates a ready-made action plan in Jira for the developer.

![A section of the Teamwork Graph: connected nodes labelled Code, Design, Product, Work Item, Engineering, Recording and Roadmap](https://cdn.sanity.io/images/c475o02b/production/591f2e558a5bfc364773457f17fbe13944904b9b-1716x886.png?w=1504&q=75&fit=max&auto=format)

So sieht die neue Arbeitsrealität mit Jira aus: Die Idee wird mit Loom aufgezeichnet, Rovo erstellt die Work Items in Jira, 3rd-Party Agents wie Loveable sind eingebunden, um z.B. Design-Vorschläge zu erstellen, um zuletzt mit RovoDev den Code anzupassen. Ohne jemals Jira selbst zu verlassen.

## Service Collection: Proactive IT and Service Management

Atlassian is burying the concept of the classic service desk with its endless queues and static forms. In the AI era, service is no longer an isolated process, but a living system that solves problems before they arise.

Service now happens invisibly in the background. AI agents detect incidents in real time (e.g., through code deploys or system metrics) and automatically route them to the right place – often before a user even needs to seek help.

### 1. Optimize in Customer Service Management (available as a beta version)

This feature closes the gap between what teams know but the AI does not yet know. It identifies gaps by finding tickets that the team has resolved itself and uses the information from them to automatically create new articles for the knowledge base. Once the team approves the article, the AI has the basis to handle similar requests itself in the future.

![Vier Vorschauansichten der kommenden Optimize-Funktionen: Inhaltsaktualisierungen, sich selbst verbessernde Runbooks, proaktive Personalisierung und Broadcast-Benachrichtigungen](https://cdn.sanity.io/images/c475o02b/production/7d90ade3ffff360d94b79c6ecf392d00ab700ff6-2560x1435.png?w=1504&q=75&fit=max&auto=format)

### 2. Incident Command Center in Jira Service Management (available as a beta version)

In an IT outage, every second counts. This new hub bundles alerts from tools like Datadog, visually shows which systems are affected ("Blast Radius") and immediately suggests solutions. After an incident, **Rovo Ops** takes over writing the Post-Incident Review (PIR), while **Rovo Dev** directly creates the resulting development tickets to permanently fix the error.

### 3. Incident Prevention Center in Jira Service Management (available as a beta version)

Rather than merely avoiding the recurrence of Incidents, the Incident Prevention Center aims to ensure that Incidents are detected and prevented before they even occur for the first time. To achieve this, Rovo is used to pull all information from the Teamwork Graph, providing a bird's-eye view of all services, dependencies, and current changes.

Every Change Request is analysed by Rovo Ops with regard to potential risks and contributing factors, in order to then provide recommendations for action that minimise the risk.

![The "Risk assessment and mitigation" tab on a change: reported gaps in the test plan and two mitigation actions with owners and risk labels](https://cdn.sanity.io/images/c475o02b/production/7107856bdee83277f4f9ac6ef572e8c4d0bc4297-2560x1413.png?w=1504&q=75&fit=max&auto=format)

Rovo Ops analysiert, welche weiteren Changes bereits geplant sind, findet Abhängigkeiten und ermittelt die Risiken, die durch einen neu angefragten Change bestehen. Dann erstellt es Action Items, die helfen sollen, das Risiko des Changes gering zu halten bzw. zu beseitigen.

### 4. Hardware Asset Management in Jira Service Management (coming soon)

IT teams receive a unified, integrated view of all hardware assets within Jira Service Management. It provides information on hardware types, their locations, costs, warranty contracts, security risks, and automates the entire hardware lifecycle.

![The hardware overview in Jira Service Management: metrics such as total hardware in use and total cost, below two bar charts by type and location](https://cdn.sanity.io/images/c475o02b/production/aa3f2c4a0b4d0e86da4e67ce488e76b9e952ef0b-2560x1468.png?w=1504&q=75&fit=max&auto=format)

Hardware Asset Management: Asset Admins erhalten Out-of-the-Box eine vollständige Echtzeit-Übersicht über Hardware und deren finanzielle Auswirkungen.

A practical example of this is the task of assigning a new laptop to a user: The ticket with the user's request for a new laptop comes in via JSM, and with the help of Rovo Skills, a suitable device is found for the user that meets the requirements of their job role and is available at their location. Once the admin confirms the new device, it is automatically assigned to the user within the same system. No manual searching, no context switching, the task is completed in the shortest possible time.

![Screenshot einer Jira-Service-Management-Anfrage „Need a laptop replacement", daneben der Rovo-Assistent mit vorgeschlagenen Fähigkeiten wie Hardware auswählen und zuweisen](https://cdn.sanity.io/images/c475o02b/production/43ea686e7e453d9ff5514ea10eb2a26a67f4600e-2560x1409.png?w=1504&q=75&fit=max&auto=format)

### 5. Data Manager in Assets

Data Manager receives a refresh that makes it easier and more intuitive to manage assets across the enterprise.

![Vier Ansichten des Atlassian Data Manager: Cloud-zu-Cloud-Konnektoren mit Lansweeper, die vereinfachte Navigation und die Konfigurationsschritte Fetch, Transform, Map, Cleanse und Merge](https://cdn.sanity.io/images/c475o02b/production/62541caf24ab7f02f4cc8b159e42d5e77340723a-2560x1398.png?w=1504&q=75&fit=max&auto=format)

### 6. Solution Composer (coming soon)

Administrators no longer need to laboriously configure portals manually. You simply describe the desired experience via text input, and Rovo designs the appropriate workflows, automations, and AI agents in minutes.

"I need a portal for holiday requests with approval by the manager", and Rovo builds the entire portal including logic in a few minutes.

### 7. Rovo Service (generally available)

Rovo Service acts as an autonomous team member that takes on complex end-to-end workflows (e.g., software provisioning, HR onboarding, or access management). It understands roles and permissions via the Teamwork Graph and orchestrates approvals across Jira, Confluence, and third-party apps.

## The new Product Collection: From idea to data-driven implementation

In a world where AI is extremely accelerating the building of prototypes, the right decision becomes the real bottleneck. Product teams often struggle to set the right priorities from a flood of feedback. With [Jira Product Discovery](https://www.xalt.de/en/blog/jira-product-discovery-strategy-and-software-delivery/), product teams can already manage ideas, requirements, and roadmaps via a central platform.

Atlassian has now announced the Product Collection (Early Access) as an AI-supported system that ensures teams not only build *quickly* but build the *right thing*, based on customer feedback and usage analyses. It includes Jira Product Discovery, the new Feedback App, and Rovo. In addition, an integration with Pendo, a product analytics and user feedback platform that helps companies better understand user behaviour in software applications, is to be available soon.

### 1. Feedback App (Early Access)

No more relying on "gut feeling" or the loudest voice in the room. This tool collects customer feedback from support tickets, sales calls (e.g., Salesforce), Slack, and surveys in one central place. The AI automatically structures these countless signals into clear themes and trends that flow directly into the Jira Product Discovery backlog.

![Screenshot der Atlassian-App Feedback: eine Voice-of-Customer-Übersicht mit Top-Erkenntnissen, betroffenen Kundensegmenten als Ringdiagramm und einer Feedback-Liste](https://cdn.sanity.io/images/c475o02b/production/216f09f61ab77aa998415a82d563a0d1cb9a2323-2560x1382.png?w=1504&q=75&fit=max&auto=format)

### 2. Pendo Integration (Early Access)

For the first time, qualitative statements ("customers say...") are juxtaposed with quantitative data ("customers do..."). Through the integration of Pendo, actual usage data and feature adoption rates flow directly into the Teamwork Graph, and thus into prioritization. This allows you to make decisions based on real user behavior and creates an integrated cycle between customer feedback, product planning, and development.

### 3. Agentic Roadmapping with Rovo (Early Access)

Atlassian is working on a feature where Rovo actively assists in creating and adjusting roadmaps. The AI identifies goal conflicts, highlights compromises, and dynamically adapts plans when business objectives change.

![Screenshot von Jira Product Discovery mit einer Chancenanalyse zum Freigabeprozess für Ausgaben, rechts daneben ein Rovo-Bereich mit einem fertigen Bericht und Vorschlägen](https://cdn.sanity.io/images/c475o02b/production/13fb27dca786633b6615567bbf6eb8de5655715c-3840x2156.gif)

### 4. Jira Product Discovery Enterprise (generally available soon)

Developed specifically for large organizations, this version offers central visibility across all portfolios. With enterprise-grade security and governance, executives can seamlessly track decisions from the first customer signal to the final release (via Atlassian Data Lake).

## Software Collection: Focus on AI-native Engineering (DX)

The way software is developed is changing rapidly due to AI assistants and agents. Atlassian (via DX) now provides the tools to make the effectiveness and ROI of this new way of working measurable.

### 1. AI Code Insights

Executives receive full transparency for the first time on how much code in their company is actually generated by AI. Reports show exactly which pull requests contain AI contributions and how this code moves through the development lifecycle (SDLC) compared to human-written code.

### 2. Agent Experience (AX)

A completely new approach to measuring success. Instead of just checking the result, the AI agent itself "reports" on its experience. It provides feedback on whether the requirements were clear, whether the documentation was sufficient, or whether the code structure hindered it. This allows companies to specifically improve the conditions under which AI agents work.

### 3. AI Cost Management

This tool translates investments in AI tools (such as token costs and licenses) into concrete financial metrics. This finally allows the question "Is AI worth it for us?" to be answered with hard facts for budget reporting.

![Screenshot eines Dashboards zur Kostenkontrolle von KI-Werkzeugen: Gesamtkosten von 341.000 Dollar mit Prognose und eine Tabelle der Kosten je Team](https://cdn.sanity.io/images/c475o02b/production/47213c30fb97ebac688b1d6280debac9b071bf31-2560x1466.png?w=1504&q=75&fit=max&auto=format)

### 4. Pulse & DX AI

A proactive alert system for engineering managers. **Pulse** delivers the most important trends and deviations directly to Slack or Teams on a weekly basis. Through the new **DX AI** interface, managers can dive deeper into the data via chat, find the causes of anomalies, or have qualitative developer comments summarised.

### 5. Code Intelligence in Rovo (Early Access)

A powerful tool for developers that provides deep semantic understanding across millions of lines of code. This enables Rovo to answer intent-based questions and link code with the business context from Jira and Confluence.

## Strategy Collection: Dynamic linking of strategy and execution

Fewer than 1 in 3 organisations can make a decision within a week. Two-thirds require a month or more. This highlights the “Mean Time to Pivot” and thus the hindered responsiveness to new competitors, market opportunities, and priority changes.

The [Strategy Collection](https://www.xalt.de/en/blog/atlassian-strategy-collection-enterprise-strategy/) aims to accelerate responsiveness by serving as a central hub for real-time information on project deviations, investments, action options, and dynamic resource planning. The newly announced features include:

### 1. Strategic Intelligence in Focus App (Beta version from June 2026)

A customisable executive command centre that monitors the status of goals and projects. Rovo proactively reports what is on track, what poses risks, and where decisions are needed.

### 2. Funds in Focus App (Generally available from June 2026)

Links the strategic view directly to the financial level, allowing budgets, costs, and forecasts to be monitored in real time alongside “project health”.

### 3. Strategic Planning in Focus (Early Adopter Program from June 2026)

Dynamic, adaptable corporate planning. When priorities change, Rovo adjusts the plan immediately, uncovers dependencies, and notifies the relevant teams in real time.

### 4. Human & AI Capital Management in Talent App (coming soon)

Atlassian addresses one of the biggest challenges for modern companies: the question of who has which skills and whether AI investments are truly worthwhile.

- **Workforce Skills:** Instead of relying on outdated CVs or manual surveys, the AI automatically derives the actual skills of your employees from their work (e.g., code written, Confluence pages created, Jira tickets resolved). This allows you to immediately find the right experts for critical projects and identify skill gaps in real time.
- **AI Investment Tracking:** For the first time, it becomes visible what your AI tools actually cost and what ROI they deliver. You receive a detailed view of spending per model provider, broken down by teams and strategic priorities. This finally allows you to answer whether the AI investment actually increases productivity or is merely an unclarified cost factor.

![Vier Produktansichten der Atlassian Strategy Collection: Strategic Intelligence mit Zielstatus, Funds mit Budgetabweichung, Human & AI Capital Management sowie Strategic Planning](https://cdn.sanity.io/images/c475o02b/production/14ac78c2ebfb4588bb6ab8da48f020b8913decfb-2560x1416.png?w=1504&q=75&fit=max&auto=format)

## Dia: The browser that thinks

It was already announced at Team’25, and now it is officially here: [the Dia Browser](https://www.atlassian.com/blog/announcements/atlassian-acquires-the-browser-company). It knows which tabs you have open, what is in your calendar, and what you are writing about in Slack. In the morning, it greets you with a "Morning Briefing" of the most important events of the night and can even generate interactive websites to help you with a specific task (e.g., travel planning).

- **Benefit:** A central entry point that actively consolidates information, rather than just displaying it passively.
- **Availability:** Enterprise-ready with SSO and SOC 2 protection.

## What does this mean for XALT customers?

The complexity in collaboration and classic knowledge silos are directly addressed by the Teamwork Graph and Rovo. For the **German market**, it is particularly important that Atlassian is investing heavily in **governance and security**. With **Atlassian Guard**, sensitive data is blocked before it reaches external AI models, and agents are given their own, auditable identities.

### Recommendations for action

1. **Lay the data foundation:**The Teamwork Graph is only as good as the data it finds. Start now to structure your Confluence and Jira instances.
2. **Start small, think big:** Use Rovo Studio to build initial small automations for standard processes (e.g., PIR creation or onboarding).
3. **Security first:** Rely on Atlassian Guard to ensure that the use of AI in the company is secure and GDPR-compliant.

### Conclusion

1. **Context beats intelligence:** The Teamwork Graph is the most important foundation for efficient AI.
2. **Agents instead of assistants:** AI now actively processes tickets in Jira and makes decisions.
3. **Governance is key:** New security features make the use of AI in the enterprise environment safe.
4. **Strategic transparency:** Tools like Focus finally bring AI power to the management level as well.

Do you want to know how to optimally integrate Rovo and the new agent functions into your existing infrastructure? Book a consultation appointment with our experts now to see the features live in action.

[**Start your AI transformation now**](https://www.xalt.de/en/contact/)

## See Rovo and the new agent features live

Want to know how to integrate Rovo and the new agent features into your existing infrastructure? Book a consultation with our experts.

[Talk to us](https://www.xalt.de/en/contact/)

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### [BaFin Compliance for Atlassian Cloud – What Financial Institutions Need to Know Now](https://www.xalt.de/en/blog/bafin-compliance-atlassian-cloud-migration/)

New EU FSA rules have been in effect for Atlassian Cloud in financial services since December 2024. We show what has changed and how you can migrate to the cloud in a BaFin-compliant way.

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### [Atlassian Is Changing Data Use for AI as of August 17, 2026: Your Checklist](https://www.xalt.de/en/blog/atlassian-changes-ai-data-use-checklist/)

Atlassian is updating its data-use policy for AI and rolling out new data contribution settings. What admins need to know and do before the August 17, 2026 deadline – including a 6-step checklist.

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