Accelerate your organisation with more context: The latest announcements from Atlassian Team ‘26
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Accelerate your organisation with more context: The latest announcements from Atlassian Team ‘26
The Adaptavist Group
Published on May 7, 2026
8 min read
The Adaptavist Group
Published on May 7, 2026
8 min read
Find out what's coming, what's been launched, and how you can start reaping the benefits.
Atlassian's annual Team conference is always full of announcements, and Team '26 is no exception. This year AI is in the spotlight and there’s a clear central theme: context. Specifically, how the data already living inside your tools provides AI differentiation for your business.
From harnessing the power of context for AI agents, to the launch of a new collection that makes product decisions easier than ever before, this blog rounds up the Atlassian announcements and what they mean for you and your teams.
From AI-ready to AI-leading
While individuals have been seeing their productivity improve by using AI, this is often only on a task-by-task basis. Where true productivity gains are seen is when AI is embedded into workflows, across teams, departments, and the organisation as a whole.
AI models can no longer be a differentiator for businesses because AI is only as smart as the data it has access to – this is where your unique organisational context is key.
Bring the context of how your business actually runs to every AI request
Enterprise teams work across lots of different platforms every day, with each containing data and knowledge on your business. By connecting these data sources into Teamwork Graph, organisation-specific context grows and AI becomes more effective.
Teamwork Graph builds a picture for your organisation, mapping out work, people, and now even assets and code. This provides that all important layer of how your business and teams actually operate into the AI models.
As more tools are connected and more content is added to the Teamwork Graph, value compounds, making your AI processes even smarter. But within the Atlassian Platform is not the only place to use Teamwork Graph data anymore.
Teamwork Graph is now open
Introducing Teamwork Graph tools in MCP Server, and Teamwork Graph CLI, both in open beta.
The Teamwork Graph in MCP Server gives any Model Context Protocol-compatible tool, for example Figma or Claude, a way to query and act on your organisational context, just like Rovo does.
The Teamwork Graph CLI does the same for developers and coding agents working in the terminal, with 360+ commands and the ability to both read from and write back to the graph.
Rovo capabilities move beyond tech-built, single task AI agents
Rovo Studio is now generally available and not just for technical users
Rovo Studio is the place for creating agents, automations, and custom apps. It’s now available to everyone, not just technical users, with governance and visibility built in.
Max mode in Rovo Chat coming soon, providing multi-step execution
Rather than only answering a question or completing a single task, Max mode takes a complex, open-ended instruction, breaks it into a sequence of actions, executes them across Atlassian and connected tools, and returns a complete output.
AI agents are welcomed into Jira as your new teammates
Agents in Jira brings together the power of your whole team, both humans and AI agents
Use Jira as a coordination engine to orchestrate your agent and human workflows. AI agents can now be assigned work, mentioned in comments, and embedded directly into workflows and automations. Every action they take is logged, auditable, and visible alongside your team, showing how work moves between human and agent.
New Atlassian Product Collection launches in early access
How do product teams decide the right products and features to ship? The Product Collection provides a cohesive way for product builders to make feedback-aligned decisions by bringing together Jira Product Discovery, with a new app: Feedback.
The Feedback app collects signals from support tools, review sites, and demand platforms, and ties them back to goals and plans in Jira Product Discovery.
Alongside this, Atlassian announced a Pendo integration to provide product teams with even more context.
Dia accelerates your working day and becomes enterprise-ready
AI-powered browser Dia includes a morning briefing that provides a tailored daily overview of your tasks, schedule, and work highlights. The morning briefing pulls data from your calendar, your messages, your action items, and more, to give a quick overview of everything that matters for you on that day.
Group browser tabs by context so your projects are kept together, and even create curated landing pages based on your requirements.
Dia is now enterprise-ready by providing the level of data protection, governance and control capabilities that enterprises rely on, plus security compliance such as SOC 2 Type II.
Accelerating processes, measurement and incident response for engineering and service teams
Rovo Code Intelligence
Rovo Code Intelligence is available in early access and lets engineers and AI agents ask questions about code intent across multiple repositories, not just search for specific strings. By pulling context from Jira and Confluence alongside your source code, answers come from one place rather than several tools.
DX AI experience
DX which was acquired by Atlassian last year gives engineering leaders a way to measure the ROI of AI tooling, not just adopt it. Three capabilities sit at the centre of this: Agent Experience, which maps how an agent moves through a process the same way DX already maps how a developer does; AI Code Insights, which shows where AI is generating code; and AI Pulse, which tracks the impact on productivity. Together, they make AI activity visible and governable within the software development lifecycle. Features like the Agent Experience Score mean teams can identify and fix bottlenecks in agent performance the same way they would in human workflows, moving from "we're using AI" to "here's what it's producing, and here's the measurable difference it's making."
Incident Command Center
The new Incident Command Center consolidates alerting, investigation, and communication into a single, AI-native workflow. It draws signals from across the Teamwork Graph to surface root causes, blast radius, and business impact without teams wading through disconnected alerts. After the incident, Rovo Ops drafts the post-incident review automatically, and Rovo Dev converts findings into work issues, closing the loop from incident to improvement.
The future of an AI-native organisation: what these announcements show about modern businesses
Above are just some of the new innovations announced at Team ‘26, and the future of what is possible is still evolving. Here are a few takeaways:
Context unlocks quality
Teamwork Graph gets more valuable the longer you invest in it. Every connected tool, project, and piece of knowledge adds to what your AI can reason over. Organisations that start building that context now will have a structural advantage.
The human is firmly in the loop
As agents take on more execution, work may adapt as knowledge workers focus more time on tasks that genuinely require human judgment, like setting intent and navigating ambiguity.
Visibility of your agents, measurement of their impact
As AI agents are integrated into your workflows, understanding what they are doing and how this impacts your team and processes is important.
Governance unlocks growth
Understanding when an AI agent can make a decision without human approval vs when to escalate, and how these decisions are documented, are just some of the questions that need answers before agents run at scale.
Read more about these announcements here.
Want to explore the opportunities that these new innovations provide for your business?
Get in touch with our solutions experts.
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Atlassian
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