Executive summary
Adoption without governance is the fastest way to stall enterprise AI. A Rovo rollout moves quickly until Legal, Security, or Audit asks who approved an agent, what data it can reach, and where the record lives. Enterprise AI governance gives you those answers in advance, so teams can expand Rovo and connected AI tools without pausing for reviews.
What is enterprise AI governance?
Enterprise AI governance is the set of policies, roles, technical controls, and review routines an organization uses to decide which AI capabilities are allowed, what data they can access, and how their use is monitored. On Atlassian, it spans Rovo, the AI features inside Jira, Confluence, and Jira Service Management, and external AI tools that connect to Atlassian data. For the wider platform picture, see our complete guide to enterprise AI on Atlassian.
The governance surface: four areas to control
Data access and permissions
Rovo honors existing permissions, so users only get answers drawn from content they can already view. That protection is only as strong as your permission hygiene. A Confluence space left open years ago becomes searchable through AI the day Rovo goes live.
Audit logging
The Atlassian organization audit log records Rovo activity such as chats started and agents created, updated, or deleted. Every tool call through the Atlassian MCP server is logged with the tool, action, and user, giving you a trail for external AI clients.
Data residency
Rovo supports data residency, so in-scope Rovo data stays in the region you pin. Inference is a separate question. By default, Rovo sends requests to third-party LLM providers that operate under zero data retention agreements, and Cloud Enterprise organizations can request Atlassian-hosted models only.
Agent oversight
Agents act on behalf of the person using them, or under their own agent account with permissions admins manage. Oversight means knowing who builds agents, who can use them, and which tools each one can call.
AI access controls Atlassian admins can set today
These controls form the technical base of Rovo governance. Availability varies by plan.
| Control | Where it lives | What it governs |
| AI activation per app | Atlassian Administration | Which apps run AI-powered Rovo features (Rovo Search, Studio, and Bookmarks stay on) |
| Agent creation rights | Rovo Studio settings | Whether all users, up to 10 selected groups, or only org admins can create agents |
| Agent user access | Each agent's settings | Who can see and use a specific agent |
| Connectors and indexing lists | Atlassian Administration | Which third-party apps Rovo searches, plus allowlists or blocklists for Google Drive and SharePoint |
| Atlassian-hosted LLMs | By request, Cloud Enterprise | Whether inference stays inside the Atlassian Cloud boundary |
| MCP server settings | Atlassian Administration | Whether external AI tools can connect, and by which authentication method |
| Data residency | Atlassian Administration | Where in-scope Rovo data is stored |
A governance operating model: policy, roles, and review cadence
Controls only hold when someone owns them. A lightweight operating model keeps Atlassian AI governance running after launch.
Policy
Publish a short AI use policy covering approved tools, off-limits data classes, the approval path for new agents, and where a person reviews output before it ships. Map it to ISO/IEC 42001, the international standard for AI management systems, so auditors recognize the structure.
Roles
- Executive sponsor: sets risk appetite and resolves disputes
- Platform owner: administers Rovo, Studio, connector, and MCP settings
- Agent owners: accountable for each agent's purpose, sources, and tools
- Security and compliance reviewer: signs off on high-impact agents and new connectors
Review cadence
- Monthly: review audit log events for new agents, connector changes, and MCP activity
- Quarterly: recertify permissions on sensitive spaces, retire unused agents, and re-check connector scope
- Annually: refresh the policy against new regulation and Atlassian feature releases
Connect AI governance to the Atlassian governance you already run
Most of what enterprise AI governance needs already exists in a mature Atlassian estate. Permission schemes, space ownership, identity provider groups, and change control all carry over. Extend them before building anything new:
- Use the identity provider groups that define admin roles to grant Studio creation rights
- Route new agents through the same change process you use for automation rules
- Add agent accounts and connector scopes to your existing access reviews
Our Atlassian governance framework for large organizations covers the platform-level model, and Top 7 CIO Moves for Atlassian AI Readiness covers the cleanup to finish first.
Where a Field CTO partner fits
Sequencing these guardrails alongside a live rollout is the hard part, especially when AI touches regulated data. Praecipio is North America's largest pure-play Atlassian Platinum Solution Partner, a seven-time Atlassian Partner of the Year, and a Select Partner in the Claude Partner Network. Our Field CTO model pairs an executive advisor with a delivery team, so governance design and implementation stay connected.
Talk to our team about building a responsible AI enterprise program with our enterprise AI services.
Frequently asked questions
Does Rovo respect existing Atlassian permissions?
Yes. Rovo only returns or acts on content the user already has permission to view or edit, including content from connected third-party apps.
Can we turn off Rovo while governance is in progress?
Organization admins can deactivate AI-powered Rovo features app by app. Rovo Search, Studio, and Bookmarks are part of the Atlassian platform and stay on, so restrict agent creation in the meantime.
Is our data used to train AI models?
Atlassian states that its third-party LLM providers do not store your inputs and outputs or use them for training. Atlassian may use de-identified metadata to fine-tune models in its own infrastructure, subject to your data contribution settings.
Does Rovo support data residency?
Yes. In-scope Rovo data follows your data residency settings, so it stays in the region you select.
How do we govern external AI tools, such as Claude, that connect to Atlassian?
Through the Atlassian MCP server. Admins control which authentication methods users can connect with, and each tool call appears in the organization audit log.
