[Atlassian Intelligence], [Rovo], [Artificial Intelligence], [Integration]
Executives say only 24% of teams do mission-critical work. Employees handle many tools (269 on average) and information, reducing efficiency and productivity, leaving less time for engaging work. How can organizations cut through noise, connect tools, and focus on priorities? Atlassian’s Rovo Agents, combining AI and human collaboration, enhance efficiency by removing repetitive tasks, sharing knowledge, and improving outcomes.
Introduction – Why Rovo Agents?
Rovo Agents are AI-powered teammates developed by Atlassian to automate routine tasks, assist with workflows, and enhance productivity within tools like Jira and Confluence. Unlike traditional automation rules, Rovo Agents use AI to understand context, suggest solutions, and take action without manual intervention.
Automate Repetitive Tasks
Less manual work, more productivity.
Smart Decision Support
Helps teams make informed choices.
Seamless Integration
Works across Jira, Confluence, and third-party tools.
Enhanced Collaboration
AI that works alongside your team.
How Rovo Agents Work in Real-World Scenarios
Currently, Rovo offers 20 ready-to-use agents and various marketplace agents for immediate deployment, as well as supporting teams across engineering, IT, sales, and marketing. You can start with pre-built Agents and further customize them to fit your team’s needs. Easily create custom Agents with specialized skills using the Forge platform or a no-code interface.
Here we will present 4 common use cases for Rovo Agents, but rest assured, there are many more. We recommend checking out this free white paper for more detailed information and practical usage tips. In addition to a step-by-step guide on creating your own Rovo Agent, Atlassian offers best practices and recommendations.
4 Practical Use Cases for Rovo Agents:
1. Automating Ticket Management for IT Teams
Scenario: An IT helpdesk receives repetitive requests for password resets.
Rovo Agent Action: Automatically detects requests, sends predefined steps to the user, and escalates only complex cases.
2. Sprint & Standup Reporting in Agile Teams
Scenario: Agile teams manually track blockers and sprint summaries.
Rovo Agent Action: Gathers Jira issues, summarizes progress, and posts updates to Slack/Confluence.
3. Automating HR Tasks & Simplifying Onboarding
Scenario: New hires frequently ask about leave policies and tools setup.
Rovo Agent Action: Automates responses based on Confluence knowledge base and assigns tasks to IT & HR.
4. Extracting Insights from Customer Feedback
Scenario: A product team receives a lot of customer feedback from JSM tickets, emails, and surveys.
Rovo Agent Action: Categorizes feedback, summarizes insights & patterns, flags urgent issues, and generates reports.
Having examined just a few such examples, we can already highlight Rovo's key features, which open up a wealth of benefits and opportunities for your teams:
Customization
Every Rovo Agent is fully customizable and has its own character, goal, and unique abilities. You can easily tailor its personality to your team's culture, specific tasks, or workflows.
Knowledge Integration
Agents can access internal and external data sources, including Confluence spaces, Jira projects, and third-party applications like Google Drive and Microsoft SharePoint, to provide informed assistance.
Action Execution
Beyond providing information, Rovo Agents can create or edit Jira issues and Confluence pages, streamlining processes and reducing manual effort.
Setting Up a Rovo Agent - How to Create Your Own Rovo Agent
1. Enable Rovo Agents
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Go to your Atlassian Admin panel.
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Navigate to Rovo Agents in the settings.
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Enable access for the relevant Jira/Confluence projects.
2. Create a Custom Rovo Agent
Rovo’s no-code product ensures anyone can build agents. Here's how:
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Select "Create Agent" and choose a predefined template (e.g., IT support, Agile reporting).
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Define agent permissions and scope (e.g., read Jira tickets, edit Confluence pages).
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Deploy and test in a sandbox environment.
For advanced users and developers, we recommend trying Atlassian’s Forge platform to build custom AI behaviors. Here, you can define API integrations with third-party apps (Google Drive, Slack, etc.) and then deploy them via Atlassian Cloud for organization-wide automation.
| To get the most out of Rovo Agent, do a little background research to determine its role, purpose, and specific use case. |
3. Optimize Rovo Agents for Best Performance
✍️Fine-tune responses: Train agents using real user queries to improve accuracy.
🚀Integrate with third-party tools: Connect to Google Drive, Slack, and Microsoft Teams.
📊Measure success: Track response time reductions and task automation rates.
Troubleshooting & Common Pitfalls
By proactively addressing these issues, you can maximize the efficiency and reliability of Rovo Agents while maintaining security and accuracy.
Agent Not Responding?
Check permissions and integrations:
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Ensure the agent has the correct permissions to access Jira, Confluence, or third-party tools.
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Verify API integrations and authentication settings.
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Restart the agent or reconfigure its scope if necessary.
Inaccurate Suggestions?
Refine learning data and scope:
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Review the agent’s training data and feedback logs to identify inconsistencies.
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Adjust filtering criteria to focus on relevant information.
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Continuously refine prompts and responses for better accuracy.
Security Concerns?
Restrict access to sensitive data:
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Limit agent permissions to prevent unauthorized access to confidential information.
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Use role-based access controls (RBAC) to define who can modify the agent.
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Regularly audit agent activity logs to ensure compliance with security policies.
The Future of Rovo Agents – What’s Next?
Rovo Agents are rapidly evolving, with new features expanding their capabilities. Future updates will add more third-party integrations, enhancing connections with tools like Slack and Microsoft Teams. Advanced AI models will improve context understanding, making recommendations more accurate and reducing manual adjustments. As workflows adapt, teams can create dynamic automations without complex scripting.
AI-powered teammates like Rovo Agents will soon be standard in workflow automation, evolving from task execution to proactive problem-solving. They will manage routine tasks, identify inefficiencies, and enhance decision-making with real-time data and recommendations. As automation grows, AI teammates will be crucial for boosting productivity and efficiency. Now is the time to explore Rovo Agents and prepare for AI-driven work management.
