Answer, act, and resolve with AI for service management
Before you start, this guide covers:
What AI for service management is and what Rovo brings to employee service teams
The top use cases for AI across IT, HR, and business support
The Rovo features and agents behind each use case
Frequently asked questions and additional resources
Service Collection products referenced: Jira Service Management, Rovo
Reading time: 5 minutes
What is AI for service management?
AI for service management is the application of artificial intelligence and machine learning to automate service delivery, resolve requests, and optimize support workflows. It enables teams to provide instant self-service and automate routine tasks like ticket triage and knowledge maintenance.
Atlassian delivers these capabilities through Rovo in Jira Service Management. Rovo moves beyond generic AI to provide contextual agentic support that understands your people, your tools, and your history.
Powered by the Teamwork Graph, Rovo pulls in your unique organizational context to resolve requests accurately and automatically.
What are the benefits of AI-native service management?
By embedding AI directly into daily service workflows, Rovo enables teams to expand support capacity, accelerate resolution times, and reduce manual overhead across every department:
Scale support capacity: Resolve more requests without adding headcount by providing instant answers and automating routine fulfillment tasks.
Provide omnichannel help: Deliver contextual support directly in Slack, Microsoft Teams, and the help center so employees get help where they already work.
Automate request triage: Get every request to the right team faster by automating categorization, prioritization, and assignment, reducing manual queue management.
Accelerate agent resolution: Help agents focus on complex work by summarizing request history, surfacing relevant knowledge, and suggesting next steps for faster resolution.
Optimize service delivery: Continuously improve performance by using request trends and knowledge gaps to identify where automation has the biggest impact.
How do teams use Rovo to accelerate service workflows?
Here are some of the most common ways service teams put Rovo to work across IT, HR, and business support use cases in Jira Service Management.
Deliver seamless self-service support and deflect L1 tickets
Repetitive questions take up a large share of a service team's day, and employees often wait for answers they could get in seconds. With Rovo, teams can build custom agents in Studio tailored to their tools, workflows, and knowledge.
These agents connect to your knowledge base and the Teamwork Graph to answer questions and handle routine requests conversationally wherever your employees get work done – whether that’s in Slack, Microsoft Teams, or the help center – escalating to a human only when required.
This gives employees always-on, contextual support and can deflect a meaningful share of routine requests before they reach an agent.
Keep your knowledge base current with AI
Knowledge bases go stale fast. Agents rarely have time to write articles, so deflection suffers, and the same questions keep coming back. Rovo identifies gaps in your knowledge base, suggests topics based on recent ticket trends, and drafts articles from resolved tickets.
Your team reviews and publishes, so the knowledge stays accurate with a human in the loop.
Better knowledge feeds every other use case: it grounds your custom agents, sharpens agent replies, and lifts deflection over time. The same questions stop coming back.
Triage and route every request automatically
Sorting, prioritizing, and assigning requests by hand takes time and can lead to inconsistent handling. The Request Router agent reads request details and sentiment to recommend the right request type, urgency, and priority, then routes each request to the correct queue or assignee.
It draws on the Teamwork Graph and historical ticket data, so routing gets more accurate over time. This helps requests reach the right person sooner and reduces the manual effort of managing the queue.
Resolve requests end-to-end with autonomous AI agents
Answering a question is only part of the job. Many requests also require action across teams and systems, often resulting in work waiting in a queue. Request Resolver resolves service requests end-to-end. It understands the request, finds the right operational knowledge, generates a resolution plan with citations, then carries it out across your connected tools – from provisioning access to executing onboarding tasks.
Teams decide how much autonomy to give it. In supervised mode, an agent reviews and approves each plan before it runs. In autonomous mode, Request Resolver handles qualifying requests as they come in. After self-service, this is one of the most significant ways Rovo helps service teams: work that once sat in the queue can now be resolved automatically, freeing agents from repetitive fulfillment and shortening resolution time.
Help agents resolve escalations faster
When a request does reach a human, agents burn time reading long threads and researching answers before they can respond. The Service Request Helper agent summarizes ticket activity, suggests next steps, drafts replies, recommends SMEs, surfaces relevant past tickets, and more. Agents stay in control while Rovo does the legwork, which speeds up resolution and keeps responses consistent across the team.
Customer spotlight: Sprout Social
Atlassian is having a massive impact on the way we work - not only helping us to get more efficient as we scale, but also to create a more competitive company.
Mason Proud, Director of IT, Sprout Social
The results: 80% of new-hire questions are answered by a Rovo agent, freeing IT staff and speeding up onboarding.
Frequently asked questions
What is Rovo for service management teams?
Rovo for service management is an AI-powered solution that integrates intelligent agents and unified knowledge into Jira Service Management. It helps IT, HR, and business teams automate routine work, provide 24/7 employee self-service, and accelerate request resolution across Slack, Microsoft Teams, and the help center.
How does Rovo help deflect employee requests?
Rovo uses a virtual service agent to connect your knowledge base to the Teamwork Graph, answering questions and handling routine requests in a conversational way. By automatically resolving common inquiries and escalating only complex issues to human agents, Rovo significantly increases deflection rates and reduces manual ticket volume.
Can Rovo resolve service requests autonomously?
Yes. The Request Resolver agent can resolve service requests end-to-end by finding operational knowledge, generating a resolution plan, and executing actions across connected tools. Teams can choose supervised mode for agent approval or autonomous mode to let Rovo handle qualifying requests without manual intervention.
Where can employees access AI for service workflows?
Employees can access Rovo’s AI-powered support directly within the channels they use daily, including Slack, Microsoft Teams, and the Jira Service Management help center. This omnichannel approach ensures employees receive instant, contextual help without needing to search for specific service portals or email addresses.