Artificial Intelligence in Jira Service Management

Whether your goal is to enhance automated support, streamline onboarding, or provide knowledge at your customers' fingertips, Jira Service Management’s AI-powered support workflows are designed to ensure employees receive the assistance they need while simultaneously increasing the productivity of front-line agents.

In this section, we'll walk through how you can use AI in Jira Service Management to:

• Deliver great self-service support experiences
• Accelerate agent & admin productivity

Virtual service agent intent flows

Virtual service agent intents represent a specific problem, question, or request that your virtual service agent can help resolve for your customers. Each intent includes a set of training phrases to help the virtual service agent recognize a help-seeker’s request, and a conversational flow that helps guide the help-seeker through their work item based on their responses to the virtual service agent. Intents are great for questions that:

• Require guided work/troubleshooting
• Require information collection and triaging
• Require an automated action via web request

Examples: Software access requests, reporting an incident, new hardware, procurement requests, onboarding workflows

Intents can be easily configured with out-of-the-box templates and a low code/no code editor. The virtual service agent also uses generative AI to suggest relevant intents based on your team’s historical ticket data and actually populate some of the basic settings like a description and training phrases.

Intents allow you to automate support tasks and take action immediately. For example, you could use it to check the operating system of a help-seeker and then actually update the version in real time, or do things like automate password resets and granting software access. This can be done by running an Atlassian Automation rule in your intent flow, sending a web request, or triggering actions through third party tools like Workato and Workday.

AI answers in the virtual service agent

AI answers uses AI to search across your linked knowledge base spaces and answer your customer questions. This feature is great for getting started quickly with the virtual service agent, as there is minimal setup involved, and is particularly powerful in deflecting help requests that:

• Can be resolved by providing information or instructions

• Are covered in (or can be easily added to) your existing knowledge base articles

• Don’t usually need to be escalated to a human agent

Set up AI answers

To set up AI answers, you’ll first need to configure your virtual service agent intake channels. You can learn more about how to do this in our virtual service agent product guide.

Connect your self-service knowledge base

Once your intake channels are ready to go, you’ll need to ensure that you have a knowledge base linked to your project, either through Confluence or Jira Service Management’s native knowledge base. Maintaining an up-to-date and comprehensive knowledge base is essential for enhancing your AI experience. You can build out your knowledge base directly from Jira Service Management, or integrate existing FAQs and docs you already have in Confluence. (Hint: read below for some AI capabilities that can help you build out and maintain your knowledge base)

Activate AI answers

Once your knowledge base is ready to go, it’s time to activate AI answers in the virtual service agent settings:

From your service project, select Project settings, then in the left-hand panel find Channels & self-service and select Virtual service agent from the drop-down. Select AI answers, and then turn the toggle on next to AI answers, and select Activate. AI answers will start working immediately in all of your connected channels.

AI for knowledge management

AI editing for knowledge base articles

AI empowers agents to create knowledge base articles directly from a Jira Service Management issue. Easily brainstorm content for a new article, ensure your spelling and grammar are correct, and make your article sound professional and empathetic for your customers in just a few simple steps.

How to create a knowledge base article using generative AI

From the Jira Service Management work item view:

1. From your project sidebar navigation, select Knowledge base.
2. Select Create article.
3. Select the knowledge base space you want to create your article in and select Next.
4. Bring up AI via the toolbar or by typing /ai in the editor.
5. Write your desired prompt.
6. AI provides a draft that you can use as a starting point.

AI Drafts

Grow your knowledge base and deflect more tickets with AI drafts topics. Suggested topics enable you to proactively identify gaps in your knowledge base based on recent customer requests, and creates draft articles for you to review and publish. By creating more relevant knowledge articles, you can ensure a delightful self-service experience for help seekers and improve support team productivity through increased ticket deflection.

How to view suggested AI drafts:

1. From your service project, go to Knowledge base.

2. Select suggested topics.

3. In the topics column, you can find the submitted request topics that currently lack corresponding articles in your knowledge base. The related requests column indicates the number of requests associated with each specific topic.

4. Next to each topic, select Create article under the Actions column to write an article.

Ticket triage and prioritization

Jira Service Management offers several AI powered capabilities to help you organize your queue and prioritize the tickets that matter:

1. AI triage

Quickly clean up queues by taking bulk action to intelligently assign work items to the correct request type. By using AI to streamline the triage process, support teams can significantly reduce the time spent on manual sorting, enabling them to resolve high-priority issues more efficiently.

AI triage analyzes tickets in your queue and makes recommendations for appropriate request types and associated fields. This feature can be particularly useful when you receive requests by email and end up with a lot of work items with the “Emailed request” request type.

To use AI to triage work items:

1. Select work items in your queue.
2. Select Triage.
3. Review the suggestions and update request types if necessary.
4. Select the work items you want to update.
5. Select Apply.

If the suggestions don't match what you need, you can always manually select a request type from the list and continue the bulk update with your own selected request types.

2. Customer sentiment analysis

Get to know your customers better with AI sentiment analysis, which analyzes and interprets the emotional tone of customer comments to help you understand how customers are feeling. Using ticket context like the title, description, and comments, AI assesses the customer sentiment – whether it's positive, neutral, or negative – and displays it directly on the work item view, updating in real-time as new comments come in. By spotting frustrations early, you can provide top-notch service, keeping customer happiness as a top priority.

3. Rovo Agent: Service Triage Assistant

If you want to really supercharge your triaging process, try the Service Triage Assistant, one of our out-of-the-box Rovo Agents. It helps you triage incoming requests by analyzing their content, sentiment, and other details to determine the request type, urgency, and priority. The agent is designed to be used within an automation rule so it can instantly rewrite ticket titles and descriptions, update the priority, or assign request types as work items appear in your queue. It can also determine whether a request should be escalated based on SLAs, customer interactions, urgency, etc.

There are a two different ways you can engage with Service Triage Assistant.

Once you’ve sorted your queue and know which tickets to tackle first, use AI to pull critical context into your workflows, helping you respond promptly and take the right steps to get to resolution.

Get up to speed with AI summaries

Rather than reading through numerous comments on a Jira Service Management work item, AI can quickly summarize ticket activity so you can get up to speed, easily loop in new stakeholders or transition tickets to a new agent, and take action.

To use AI summaries:

1. From your Jira Service Management project, navigate to your desired work item.
2. Scroll down to the Activity section.

3. Select Comments, and then Summarize.

   1. The AI-generated summary will only be visible to you, and will disappear when you navigate away from the ticket. You can summarize an issue’s details as many times as you like.

Use AI to craft the perfect help-seeker response

AI can help agents quickly draft and edit their response to help-seekers, ensuring clear and thoughtful communication. There are a couple different ways to do this:

1. Draft Replies

This feature uses AI to draft a recommend response to your customers. It allows agents to respond to tickets smartly and efficiently with the appropriate troubleshooting tips or follow-up questions based on comments added by agents while resolving similar requests.

2. AI editing

Use the AI slash command or the drop down AI menu in the editor to fine tune your customer response, including shortening it, adjusting the tone, and more.

AI suggestions

The suggestions panel, located on the right side of any work item view, uses AI to efficiently summarize requests and recommend assignees, pertinent requester details, escalation paths, troubleshooting steps, and more. It also enables you to directly take action from the panel, like updating the priority level.

Similar Requests

Make finding similar requests a breeze by using AI similar requests to find and identify recent requests with similar titles to the one you’re currently viewing in a service project. This feature uses Natural Language Processing (NLP) to provide a list of recent requests with similar titles to the one you’re currently viewing. This AI-automated process of finding related requests reduces the manual effort required to search for similar issues.

How to use AI Similar Requests:

1. First make sure you, Enable similar requests panel, start from your service project, select Project settings, then Features.
2. Under the Issue view, turn on the Similar requests panel toggle.
3. Next, to view similar service requests, problems, changes, and post-incident reviews. Go to the issue you want to find related requests for.
4. Select Similar requests or Similar incidents.
5. Select Open or Resolved to filter similar requests by status. 

3. Rovo agent: Service Request Helper

Another out-of-the-box Rovo Agent, Service Request Helper, provides your team with the insights needed to streamline request management and accelerate resolution times. Designed to use both Atlassian apps and connected third-party apps as knowledge sources, Service Request Helper can gather relevant information and offer guidance on how to resolve requests with speed and precision. Human agents can use Service Request Helper to identify SMEs, compose responses using insights from previous requests, summarize ticket activity, and even recommend next steps.

Like other Rovo Agents, Service Request Helper can be accessed through the Rovo Chat window in the top right corner of your navigation, near your profile icon or avatar. Navigate to any request in your queue, then open Rovo Chat, select Agents, and search for Service Request Helper.

From there you can chat with the Agent, asking it things like:

• What steps should I take next?
• Help me draft a reply to send to the customer.
• Find people who worked on similar requests before.

AI automations

Use AI to generate automation rules by simply describing the rule you want to create in natural language. This feature can be found in the automation rule builder in your project’s settings. Make sure whatever you input includes a trigger and an action.

Request type and field suggestions

Request type suggestions can help take the guesswork out of creating your service desk by intelligently suggesting request types based on how you describe the kind of work your team manages. AI can suggest request types across a range of use cases, from IT and HR to dog grooming and catering, and then add them to your service desk with just a few clicks.

How to use request type suggestions:

1. Navigate to Project settings > Request types.
2. Select Suggest.
3. Describe the type of work your team manages.
4. Select a request type from the list of AI suggestions and then select Create.
5. Confirm the request type’s name, description, icon, and issue type.
6. Select Next and add the request type to a portal group.
7. Select Create.

Once a request type has been created using AI, it can suggest relevant existing and custom fields you can add.