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AI in customer service: how it works and where it fits
Key takeaways
Customer support teams are under pressure as ticket volumes rise and customer expectations are higher than ever. With the rise of AI, organizations are moving to a new model of human-AI collaboration to deliver the best customer experiences.
AI in customer service helps teams resolve more requests faster by automating routine issues, surfacing relevant knowledge, and intelligently routing complex cases with all the right context to the right agent.
The key AI capabilities in a customer service management solution that can empower your teams include AI agents, AI performance analytics, intelligent knowledge surfacing, knowledge gap identification and article generation, and multilingual support.
What is AI in customer service?
Customer service teams are under more pressure than ever. Ticket volumes are growing, and customer expectations for fast and personalized support are rising. As a result, organizations initially turned to AI to reduce headcount and automate routine inquiries.
But here's what modern support teams understand: there’s a shift happening in customer service. It’s not AI replacing humans, but human + AI. A new model is needed that has the two working hand in hand.
AI in customer service refers to the use of artificial intelligence to help support teams handle customer requests faster, more accurately, and on a greater scale. But the most important word in that sentence isn't "faster" or "AI" — it's "help." The future of customer service isn't AI replacing human agents. It's humans and AI working together, each doing what they do best.
Handle routine, repetitive requests such as status updates, password resets, and more. AI handles this common, high-volume work, can route tickets to the right team with all the necessary context, surface relevant knowledge in the moment, and resolve issues that don't need a human at all. That frees your agents to focus on what they're uniquely good at — building relationships, navigating complex situations, and delivering the kind of empathetic, nuanced support that no AI can replicate to ensure customers stay loyal to your brand.
The result is a support team that's faster, more consistent, and more human.
In this article, we'll cover:
Key AI capabilities for customer service
The most effective AI in customer service isn't just about deflecting tickets. It's about empowering every person on your support team to do their best work. Here are the core AI capabilities to look for in a customer service solution that help agents work smarter, respond faster, and deliver more consistent, human-centered support at scale.
AI agents
AI agents handle the routine, high-volume customer requests that fill every support queue, such as common questions, account updates, and status inquiries. They are available 24/7 so customers can get help instantly and whenever they need it. When a request is more complex, the AI agent hands off to a human with full context so your support team can jump in quickly and your customers never have to repeat themselves.
Here’s what to look for when it comes to AI agent capabilities:
Capability | Description |
|---|---|
Connect knowledge | Your AI agent is only as good as what it knows. By connecting your knowledge base, it can generate accurate, grounded answers from the information your team already relies on. |
Handoff to a human agent | When a request needs a human, the AI agents can automatically create a ticket, pre-fill relevant form fields, and pass along the full conversation transcript and customer context so your agent picks up right where the AI left off and with everything they need to resolve the issue quickly. |
Set the identity | Customize your AI agent to reflect your brand. Set the tone of voice and personality, write a custom greeting, and configure how the agent introduces itself so every interaction feels like a natural extension of your support team. |
Provide guidance | Continuously improve the AI agent experience. This is crucial as it keeps humans in the loop to give feedback on the agents' conversations, inform future behavior, and deliver a better customer experience. |
Conduct actions | Beyond answering questions, let AI agents take action. With third-party integrations, the agent can trigger workflows and perform tasks across your connected tools to resolve issues end-to-end without requiring a human to step in. |
AI agent performance analytics
Understanding how AI is performing is what separates teams that continuously improve from those that plateau. You need clear visibility into AI agent deflection rates, resolution accuracy, knowledge gaps, escalation patterns, and customer satisfaction trends. This data helps both your AI and your human team keep improving.
Intelligent knowledge surfacing
Intelligent knowledge surfacing reduces one of the biggest drains of time for support agents - searching for the right answer. AI automatically surfaces relevant knowledge base articles, similar resolved tickets, and suggested responses directly in the agent's view as they work a case, so agents spend less time hunting and more time helping.
Knowledge gap identification and article generation
AI can automatically identify knowledge base gaps, highlight the topics customers are asking about that aren't covered, and can even draft suggested knowledge base articles for your team to review and publish. Over time, your knowledge base gets smarter, your AI agent gets more capable, and fewer issues require human intervention.
Multilingual support
Global support teams no longer need dedicated language-specific queues or staffing for different markets. Multilingual capabilities enable your AI and human agents to handle requests across dozens of languages, maintaining consistent service quality wherever your customers are located. Your team's expertise scales globally without the operational complexity of manual management.
How the Customer Service Management app and Rovo deliver AI-first customer service
Atlassian's Customer Service Management app is built from the ground up as an AI-first customer service solution. Built on the Atlassian platform, Rovo, Atlassian’s AI offering, isn’t bolted on but embedded into every step of the support workflow. Learn more about the app here.
Omnichannel support
Customers expect help wherever they are—web, email, chat, in-product widgets, or phone. Omnichannel support lets them choose the channel(s) they are most comfortable with, provides instant support with a readily available customer service AI agent, and when requests need to be escalated, human agents have all the context they need so they don’t have to ask customers to repeat themselves.
Customer service AI agent
The Customer Service Management app’s customer service AI agent works 24/7 across your external support channels, resolving routine requests autonomously by learning from your knowledge base and past interactions. When a request requires human expertise, it hands off to an agent with full context so nothing is lost in the handoff. Over time, the AI agent surfaces knowledge gaps and continuously improves resolution quality for your support agents.
Continuous improvement
Over time, the AI agent surfaces knowledge gaps and continuously improves resolution quality for your support agents. By looking over the AI agent’s past conversations, creating agent versions as you make changes, running tests, and running evaluations based on your agent’s previous behavior, you compound and build on previous enhancements to ensure the AI agent is providing the best possible customer experience.
The Teamwork Graph: AI with full cross-team context
What makes AI in the Customer Service Management app uniquely powerful is the Atlassian Teamwork Graph. Most customer service AI only has access to support data. Because AI agents are built on Rovo, Atlassian’s AI platform, which is powered by the Atlassian Teamwork Graph, it draws on the full context of your organization — linking customer requests to related bugs in Jira, incidents in Jira Service Management, product feedback in Jira Product Discovery, and documentation in Confluence. This means AI is informed by what's actually happening across your business and has the full picture.
Frequently asked questions about AI in customer service
What is AI in customer service?
AI in customer service refers to the use of artificial intelligence technologies, including AI agents, machine learning, and natural language processing, to help support teams handle customer requests faster, more accurately, and at a greater scale. AI can automate routine issue resolution, surface relevant knowledge for agents, intelligently route tickets, and provide analytics on support performance.
What is an AI customer service agent?
An AI customer service agent is a software system that autonomously handles customer requests by answering questions, taking action, and resolving issues without requiring human intervention for every interaction. AI agents work across channels and around the clock, learning from your knowledge base and past resolutions to continuously improve. When a request is too complex for the AI agent to resolve, it is escalated to a human agent with full context so the customer experience remains seamless.
What are the benefits of AI customer service software?
AI customer service software helps teams handle higher ticket volumes, reduce resolution times, improve first-contact resolution rates, and deliver more consistent customer experiences. It also gives support leaders better visibility into performance through AI-native analytics and helps identify knowledge gaps that can be addressed proactively.
What types of customer requests are best suited for AI?
AI is most effective for high-volume, repeatable requests such as order or ticket status checks, password resets, account changes, FAQs about products or policies, and simple troubleshooting steps. These requests follow predictable patterns, which makes them ideal for AI to handle end-to-end.
How is AI different from traditional customer service automation?
Traditional automation (such as rule-based chatbots or canned response templates) follows fixed scripts and breaks down when customers deviate from expected inputs. Modern AI customer service solutions use large language models and machine learning to understand intent, handle variation in how customers phrase requests, learn from past interactions, and continuously improve without requiring manual rule updates. As a result, it creates a strong human-AI collaboration loop in which AI frees your agents to focus on complex requests.
Can AI replace human customer service agents?
While AI can handle common, repetitive requests, your support teams are crucial for the complex, emotionally nuanced issues where a real person makes all the difference. They bring the creativity, expertise, and judgment only a human can to build trust, ensure customers feel taken care of, and keep them loyal to your brand. As a result, they are best as a collaborative pair, rather than one replacing the other, as each does what they do best to deliver the best customer experience.