Atlassian and OpenAI Partnership Expansion

Atlassian and OpenAI have expanded their partnership to integrate frontier models from the GPT-6 family across Atlassian’s platform to enable AI agents that assist teams in planning, building, and delivering work. This collaboration combines OpenAI’s reasoning capabilities with Atlassian’s Teamwork Graph, an enterprise context layer that connects people, projects, documents, and decisions.

Integration of GPT-6 and the Teamwork Graph

OpenAI frontier models, including GPT-6 Astra and the GPT-5.6 series, will power agents across Atlassian’s platform and Rovo. Rovo utilizes the Teamwork Graph to provide AI with a deep understanding of company operations, allowing it to synthesize information across disparate sources.

For example, a product manager can use Rovo to assess launch readiness by connecting Jira tickets, Confluence documents, and discussions to identify engineering blockers and missed milestones. OpenAI models then convert this data into a clear assessment and recommended next steps.

Developer Workflow Enhancements

Atlassian has broadened its adoption of Codex and ChatGPT Enterprise, with over 3,000 Atlassian developers using Codex in terminals, IDEs, and code review workflows. Through plugins powered by the Teamwork Graph, Codex users can access technical documentation and relevant work items to streamline writing, testing, and shipping software.

Customers can further integrate their workflows via the following tools:

  • Atlassian and Teamwork Graph CLI plugins: These allow ChatGPT and Codex to access project information and documentation, subject to permissions.
  • Atlassian plugin extension: This brings Jira work items, Confluence content, and people directly into ChatGPT and Codex prompts.
  • Pinned Atlassian Home: This surfaces assigned work, recent Looms, projects, and Bitbucket pull requests for faster context access.

Future AI Agent Orchestration

Atlassian and OpenAI are exploring deeper integrations with Jira to enable teams to assign work directly to AI agents, track their progress, and review results. When paired with DX’s platform for measuring developer productivity and engineering performance, these capabilities aim to help engineering leaders quantify the impact of AI on cycle time, development speed, and overall developer experience while maintaining human oversight.

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