Atlassian is delivering a practical, customer-first AI playbook built from inside the company and publicly shared to help enterprises achieve measurable gains, a strategy highlighted at Team 9/26.

The Teamwork Graph is now accessible to external systems via a command-line interface, enabling developers and AI clients to pull work context directly from local tooling and CI pipelines, not solely through Atlassian products.

A bottom-up approach surfaced about 14 high-ROI use cases across sales, HR, finance, and legal, showing AI adoption spreading from within rather than being mandated from above.

New Team 9/26 offerings center on leveraging Teamwork Graph, including Rovo Studio for no-code agent building, generally available Jira agents, DX AI Experience for AI governance, Rovo Max for multi-step task execution, Remix with Rovo for text-to-visuals in Confluence, and the Product Collection for connected product-management workflows.

A key risk is data quality: exposing Jira and Confluence data to external AI agents could reveal organizational weaknesses if knowledge is stale or fragmented, making data cleanliness critical.

Avani Prabhakar, Atlassian’s chief people and AI enablement officer, leads the internal program with three principles: lead AI with an innovation narrative, openly acknowledge unknowns, and maintain fast experimentation loops.

Adoption of Rovo is high across enterprise cloud customers and Fortune 500 firms, with agentic automations growing sevenfold in six months, signaling the internal playbook’s resonance and expansion.

In a competitive landscape with Microsoft, ServiceNow, and Salesforce, Atlassian differentiates through deep Jira/Confluence context and exposing it via MCP and CLI interfaces for external AI agents, aiming for ubiquity rather than exclusivity.

Team 9/26 framed Context as Infrastructure with the Teamwork Graph—now a map of people, projects, documents, code, goals, and decisions containing over 150 billion connections and 12 billion daily updates that lets AI agents reason across Jira, Confluence, Jira Service Management, and more.

Over nearly two years, Atlassian built and deployed its own enterprise AI transformation, treating AI adoption as a company-wide effort and creating a practical playbook from real-world operations rather than external consultants.