Optimize support with AI for customer service management
Before you start, this guide covers:
What AI for customer service management is and what Rovo brings to customer service teams
The top use cases for AI across the customer support lifecycle
The Rovo features and agents behind each use case
Additional FAQs and learning resources
Service Collection products referenced: Customer Service Management, Rovo
Reading time: 5 minutes
What is AI for customer service management?
AI for customer service management uses AI to automate external support interactions, deflect cases, and improve agent efficiency, enabling organizations to provide 24/7 conversational support, resolve common inquiries autonomously, and surface trends that improve the overall customer experience.
Atlassian delivers these capabilities through Rovo within the Customer Service Management app. Unlike generic chatbots, Rovo uses the Teamwork Graph to pull in real-time customer context and product knowledge, allowing it to resolve complex technical issues with the context and personalization that generic chatbots can't match.
What are the benefits of AI for customer service?
Most support requests still land on a person, which is expensive for the business and slow for customers stuck waiting for business hours. Rovo shifts that balance: it handles the routine autonomously with AI agents, and gives human agents the context to move faster on the rest.
Support customers 24/7: Resolve the majority of requests automatically across chat, email, and the help center, at any hour.
Deflect cases before they are filed: Surface the right answer at the point of need so customers never reach "contact us."
Speed up every agent: Draft grounded replies and summarize case history so resolutions are faster and more consistent.
Protect retention: Catch frustrated, at-risk customers early and route them to the right people first.
Turn support into product direction: Cluster case themes so leaders know what is actually breaking and can close the loop with the product team.
Top use cases for Rovo in customer service
These are the highest-impact ways customer service teams put Rovo to work across the support lifecycle. Each one pairs a real job to be done with the Rovo capabilities that deliver it.
Resolve and deflect frontline requests with an AI customer support agent
Much of the front-line support consists of common, repeatable questions. When each one needs a person, customers wait longer, and costs add up. The Customer Service Agent, powered by Rovo, provides conversational, self-service support across your channels.
It connects to your knowledge base, customer context, and the Teamwork Graph to answer questions and resolve requests on its own, and it hands off to a person when a request needs one.
Because it works across the channels customers already use and is available at any hour, the agent can deflect a large share of front-line requests before they reach a queue - freeing your team to focus on the work that actually requires human judgment.
Fill knowledge gaps and grow your knowledge base
An AI agent is only as good as the knowledge behind it, and most knowledge bases have gaps. The Optimize feature in Customer Service Management reviews escalated tickets, including the full conversation between the customer and the agent, and drafts a knowledge base article to address the gap.
That way, the Customer Service Agent can handle similar requests on its own next time.
A person reviews each suggested article, edits it if needed, and publishes it, so your team stays in control of what goes into the knowledge base. Each suggestion shows how many past support interactions a new article would have addressed, which helps you prioritize.
The result is a continuous improvement loop: every gap the agent hits becomes new knowledge that makes it more capable over time.
Empower teams with a customer support copilot
When a ticket reaches a person, agents often spend time searching documentation, account history, and past tickets before they can respond. With Rovo Chat, agents can ask questions in plain language and get answers grounded in your knowledge base, past tickets, and connected tools, without switching between systems.
They can find how similar tickets were resolved, pull up a customer's account history and entitlements, and draft a reply to a complex ticket, all in one place.
This keeps agents in control while Rovo Chat does the research in the background, helping them resolve tickets faster and more consistently and enabling new agents to ramp up more quickly.
Customer spotlight: Leadership Circle
The AI capabilities in the Customer Service Management app are among the most impactful applications of AI I've seen in a business tool. It's transforming how we support customers across 21 languages, making complex product knowledge instantly accessible to everyone.
Matt Ingersole, Chief Information Officer (CIO), Leadership Circle
The results: 71% of resolutions via AI and 65% fewer manual tickets.
Frequently asked questions
How does Rovo help customer service teams?
Rovo acts as a customer support copilot, resolving routine requests 24/7, detecting at-risk customer sentiment, and synthesizing voice-of-customer (VoC) data to improve product direction."
How well does the Customer Service AI Agent perform?
In Atlassian's own production use, the Customer Service AI Agent drove 71% engagement and a 45% resolution rate, contributing to significant customer support savings.
Does Rovo replace human agents?
No. Rovo resolves routine requests autonomously and escalates to a human when confidence is low, while giving agents drafted replies, summarized history, and sentiment signals so they can focus on complex, high-value cases.