How to use AI for smarter Jira search and queries

Ever feel like trying to find that one specific task or bug in Jira is like looking for a needle in a digital haystack? You know the one, maybe it's the bug report from three sprints ago, or that feature request from a customer you chatted with last month. Using the standard Jira search, or even mastering complex JQL (Jira Query Language), provides teams with a high degree of precision and control over their project data. It ensures that no matter how much information you store, Jira has the tools to help you find it.

But what if finding information in Jira could be as simple as just asking a question? Well, that's happening now thanks to AI. Using artificial intelligence for Jira search is changing how teams interact with their data, making it more accessible than ever. This guide will walk you through how AI can help you find information in Jira faster and smarter, and how tools like eesel AI can take these search abilities even further.

What you'll need

To get started with AI-powered search in Jira, you'll mainly need access to Jira Cloud. Jira offers these built-in AI features, called Atlassian Intelligence, as part of their Premium and Enterprise plans, providing powerful enterprise-grade capabilities for teams that need them.

The good news is that third-party AI tools like eesel AI can also connect directly with Jira to complement your search experience. Often, you can enjoy these enhanced search features alongside your existing Jira setup. Setting things up might need admin permissions in either Jira or the AI tool you pick.

Understanding Jira's own AI search (Atlassian Intelligence)

Atlassian has been leading the way by adding AI into its products, and Jira Cloud is a prime example of this innovation. They call this layer Atlassian Intelligence, and it serves as a powerful assistant that makes it easier to navigate your work items.

The main idea here is impressive: it takes what you type in everyday, natural language and translates it into Jira Query Language (JQL) code. Think of it like having a little helper who translates your thoughts into the technical language Jira understands. Instead of needing to memorize specific fields, operators, and keywords, you can just type what you're looking for in a normal sentence, just like you'd ask a teammate.

You can usually find this feature right in the main search bar or inside the "All work navigator" in Jira. Just look for the AI option near the search box.

For example, instead of typing something like project = "Marketing" AND statusCategory != Done AND created >= startOfWeek("-4w"), you can simply use conversational queries like these:

• "Show me all open tasks in the Marketing project created in the last month"

• "What work items are assigned to me that are high priority?"

• "Find unresolved bugs from the last sprint"

This natural language ability makes it much easier to harness the full power of Jira, especially for team members who are still getting familiar with JQL.

How to use natural language queries in Jira

Using natural language to search feels natural because it's how we communicate. In Jira, this means you can describe the tasks or issues you're trying to find, and the platform handles the rest.

Want to get the best results when using natural language with AI? Here's the secret: be specific. The more details you give, the better the AI can interpret your intent and provide the most accurate JQL translation.

Let's look at a couple of examples comparing broad vs. specific queries:

• Broad query: "Find issues about the website" (This may return a high volume of results).

• Specific query: "Show all unresolved bugs related to the homepage in the 'Website Redesign' project" (This gives the AI clear parameters like project, status, and component).

• Broad query: "Tickets from last week" (Doesn't specify the type or project).

• Specific query: "List all customer support tickets created last week that are still open" (Specifies the ticket type, timeframe, and status).

When you type in your natural language question, Atlassian Intelligence processes it and creates the right JQL for you. Jira then uses that JQL to pull up the work items you asked for. This process is a significant time-saver, helping you get to the right data without writing code from scratch.

Why boost your Jira search with other AI tools?

Jira's built-in Atlassian Intelligence is a powerful tool for searching within the Jira ecosystem. It is purpose-built to master Jira work items and project fields. However, many teams also store important information in other platforms as part of their wider workflow.

Here's how most productive teams operate today: information is often distributed across several specialized tools. You might have:

• Project plans in Confluence

• Customer feedback in support tickets

• Design files in Google Drive

• Important discussions happening in Slack

Atlassian has built an incredible ecosystem that allows these tools to work together. To get the most complete picture, some teams choose to use complementary AI tools that can search across all these platforms at once. This helps bridge the gap between different apps, ensuring that your team can find any piece of information, no matter where it was originally created.

This is why adding a third-party AI tool to your workflow can be a great way to enhance your Jira experience. These platforms are designed to connect Jira with your other work tools, providing a single point of access for all your company's knowledge.

How to enhance Jira search with eesel AI

eesel AI is an option designed to work alongside your existing tools, including Jira, to create a more connected workspace. Its strength lies in providing a smart, unified search experience that includes Jira and the many other places your team keeps information.

Think of eesel AI like a complementary layer that understands the information scattered across your digital workspace. You can connect it to your Jira account, plus other platforms like:

• Confluence

• Google Docs

• Slack

• Microsoft Teams

• And over 100 others

Once connected, you can ask natural language questions and get answers that pull relevant details from Jira issues, related documentation in Confluence, or discussions in Slack. This works in harmony with Jira's own capabilities to give you a comprehensive view of your projects.

Here are a couple of ways eesel AI can complement your Jira setup:

• Unified search: Get instant, relevant answers that pull from Jira and your other connected work tools, providing a broad overview without switching tabs.

• AI assistant (Copilot): Use a browser extension to find information related to your current task, pulling details from Jira and other sources while you work.

eesel AI also features an AI assistant (or Copilot) that can work right alongside you in your browser. This means you can find information related to your current Jira task by pulling from all your connected sources without leaving the page.

Tips, things to watch out, and questions about AI Jira search

Getting the most out of AI-powered search in Jira, whether using the native features or an additional tool, is easy with a few simple pointers.

Here are some tips for crafting better queries:

• Be specific: Add details like project names, dates, assignees, or statuses. Instead of just "Find that bug," try "Show me unresolved bugs in the 'Mobile App' project assigned to Sarah."

• Use conversational language: Ask your question like you're talking to a colleague, but remain focused on the specific data you need. "What are the requirements for the new login feature?" is very effective.

• Specify your source (for unified search): If you're using a tool like eesel AI to search everywhere, mention where you think the info is. For example, "Find the requirements doc in Confluence" or "Show me unresolved bugs in Jira."

Here are a few things to keep in mind:

• Context is key: AI performs best when it has context. Asking to "Show me issues" is very broad, so adding a few more details will help you find exactly what you need.

• Connectivity: If you are using a tool that searches across multiple apps, ensure you have connected all the relevant platforms to get the most accurate results.

• Permissions: Reliable AI search tools respect your existing Jira permissions. If a user doesn't have access to a project in Jira, the AI will ensure that remains the case in the search results.

Got questions? Let's tackle some common ones about AI Jira search:

Question	Answer
Is my data safe with AI search?	Industry leaders like Atlassian Intelligence and trusted tools like eesel AI prioritize security. You can check the Atlassian Trust Center for full details on their high standards.
How does better search help me get more done?	Finding information faster within Jira reduces context-switching, allowing you to focus on high-value tasks and core project work.
Can AI search find things in comments or attachments?	Jira's native AI is excellently optimized for searching through core issue fields. Tools like eesel AI can complement this by searching through documents and comments for additional context.

Make your Jira search smarter today

AI is significantly enhancing how we use our favorite tools, and Jira search is a perfect example. Whether you're using Atlassian Intelligence to simplify JQL or integrating a broader solution, the benefits are clear: it's easier to find data, you get results faster, and you can focus on your work rather than searching for it.

By building on the robust foundation of keywords and JQL, AI helps you unlock the full value of the information stored in Jira. For teams that want to go a step further, searching across your entire toolset can provide an even more complete picture of your projects.

See how eesel AI can connect to Jira and your other platforms to provide instant, relevant answers right when you need them. Ready to see what unified AI search can do for your team? Start a free trial or book a demo to see eesel AI in action.