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Atlassian has rolled out a series of updates to its Rovo AI platform, including a generally available no-code workspace for building agents and automations, a new autonomous reasoning mode and expanded governance tools for enterprise administrators.
The company reports that agentic automations across its platform have increased sevenfold in the past six months, with Rovo-assisted actions exceeding 14 million in the most recent month alone. More than 90 per cent of Atlassian’s enterprise cloud customers are now using Rovo, according to the company.
Rovo Studio reaches general availability
The centrepiece of the update is Rovo Studio, a workspace that Atlassian describes as an enterprise-grade environment where any employee – not just developers or power users – can build agents, automations and applications that connect into the Teamwork Graph.
Users can describe what they need in natural language and Studio assembles the appropriate agents, automations and views. Automations can be triggered by real-world events such as a new hire joining, a severity-one incident opening or a deal advancing, with agents coordinating work across Jira, Confluence, service portals and chat.
Studio also enables users to describe a custom application and have it scaffolded, previewed and turned into a Forge app ready for publishing. Governance features including roles, approvals, versioning and usage insights are built in.
Tapiwa Samkange, Director of Digital Transformation at Teach for All, described how the tool fits into existing workflows.
“I created a Digital Transformation Update Agent in Rovo that generates my weekly reports from Jira and our Google Sheets,” Samkange explained. “It gets me about 60 to 70 per cent of the way there, and then I refine it. The structure it provides has been a great partner in my work.”
Max mode for autonomous multi-step workflows
Atlassian is introducing Max, a new reasoning mode within Rovo Chat that is designed to handle complex tasks autonomously. Coming in early access, Max mode breaks requests into multi-step action plans, executes them across connected tools and surfaces outputs for team review.
In practice, this means Rovo can draft documents and slide decks, create or update Jira work items, notify teammates with next steps and find available calendar slots – while the user focuses on decisions and priorities rather than execution.
Atlassian states that Max mode is designed to ask for clarification where it matters, present plans for review before executing and show its working throughout. If something in a workflow breaks, the system attempts to resolve it independently before escalating back to the user.
Rovo across surfaces and tools
Rovo now operates across Atlassian applications, the browser, mobile, desktop, command-line interface and MCP connections. The platform is structured around several core functions.
Rovo Search draws on live context from connected tools across the Atlassian ecosystem and beyond, adapting to the user’s intent and the application they are working in. Rovo Chat plans and executes multi-step workflows, handling delegated work and looping users back in when human input is required.
Through the Rovo MCP Server and Teamwork Graph CLI, organisations can extend their graph context to agents running outside Atlassian’s own products. Each action taken by an external agent feeds back into the graph, building context that benefits the broader team over time.
Matthew Hargreaves, Head of Product Delivery and Automation at Lendi Group, described how this integration works in practice.
“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,” Hargreaves outlined. “That’s what takes us from AI hovering at the edges to AI embedded in the core of how the organisation operates.”
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Customer results
Several customers have reported measurable outcomes from Rovo deployments.
Ryan Boyd, VP of IT at SpotOn, pointed to concrete metrics from a sales support agent built in Slack.
“Rovo answered 95 per cent of questions in the channel, and our clean deflection rate increased from 40 to 53 per cent,” Boyd stated. “That gave us measurable impact, not just anecdotal value.”
Ben Richards, Systemic Coach at KFC UK and Ireland, noted that the platform has helped surface issues earlier in workflows.
“Rovo reduces noise, enables self-service and helps teams find blind spots earlier,” Richards commented. “It sees our entire Teamwork Graph, searches our collective knowledge, helping us surface broader connections, reduce mundane work and automate intelligently.”
Enterprise governance at scale
As AI agent usage grows across organisations, Atlassian is expanding its governance capabilities to give administrators more visibility and control.
New features include organisation-wide agent inventories that show administrators who built each agent, where it is running and how frequently it is used. Separate permissions now distinguish between AI usage access and agent-building rights, allowing organisations to open up AI broadly without creating uncontrolled agent sprawl.
Data governance controls let administrators set policies for what third-party data Rovo can ingest, how conversations are filtered and where AI features are enabled across Atlassian products. New dashboards and audit logs provide visibility into AI adoption, credit usage and activity.
Shivi Verma, Senior Manager of Engineering at DocuSign, described governance as a deciding factor in the company’s adoption.
“We’re picky about AI,” Verma noted. “What convinced us was Atlassian’s focus on secure, governed agents and their willingness to build alongside us. That’s why we trust Rovo in our System of Work.”
All Rovo controls are managed through the same administration surfaces used to configure other Atlassian settings, including data residency, hosted LLM selection, AI access permissions and agent policies.
The Teamwork Graph as competitive advantage
Atlassian is framing the Teamwork Graph – which now holds more than 150 billion connections – as the differentiating factor in its AI strategy. The company argues that what separates AI-native organisations will not be which frontier model they use, but the depth of context their people and agents can draw on.
Every Jira ticket filed, every Confluence page edited and every decision recorded adds to an organisation’s graph. Atlassian contends that this accumulated context cannot be easily replicated by competitors and becomes more valuable the longer a customer uses the platform.
Last Updated on May 10, 2026 by Nick Ross
