Jira AI recommendations in software projects

"AI-powered project management" gets thrown around a lot, but what does that look like when you’re facing a packed Jira board first thing on a Monday? It’s a fair question. I’ve seen threads on Reddit where people genuinely ask if Jira is an AI tool right out of the box, so you’re definitely not the only one feeling a bit lost in the hype.

Let’s cut through the noise. This guide breaks down what Jira’s AI can actually do. We’ll look at the features that come with Atlassian Intelligence, where third-party apps fill in the gaps, and how you can use these tools to make your projects less chaotic. We’ll get into the specifics of using AI for both planning and execution, and I’ll be straight with you about where the built-in tools fall short.

What are Jira AI recommendations, really?

First off, "Jira AI" isn’t one specific thing you can just turn on. It’s more of an umbrella term for two kinds of AI you’ll run into:

1. The built-in stuff: This is Atlassian’s own AI, called Rovo (you might know it by its old name, Atlassian Intelligence). It’s part of Jira Cloud and connects with their other products like Confluence.

2. The add-ons: The Atlassian Marketplace is full of apps from other companies that add special AI features to Jira, covering things the native tools can’t do.

So, using Jira AI recommendations in software projects really just means using either of these to get a little help. We’re talking about automating boring tasks, getting a hand with writing tickets, and receiving smart suggestions based on your data. It could be as simple as breaking down a huge project into smaller tasks, summarizing a comment thread that’s a mile long, or finding old bugs that look suspiciously like the one you’re working on now.

Atlassian’s native AI is genuinely useful, but there’s a catch. It really wants you to live and breathe inside the Atlassian ecosystem. The moment your team’s work spills over into other tools, you start to see the limitations.

Setting up your project with Jira AI

The start of any software project is a flurry of activity. You’re trying to turn big ideas into a list of actual tasks, and it’s all too easy for important details to get lost in the shuffle. This is one of the first areas where AI can lend a hand.

Generating tasks and breaking down work

Atlassian has been focusing on what it calls "Jumpstart planning," and one of the handiest native features is the AI work breakdown. You can feed it a huge epic, like "Launch New User Dashboard," and ask it to suggest smaller user stories or sub-tasks. It’s a pretty good way to build out a backlog without having to brainstorm every little thing from scratch.

You can also create a whole Jira ticket just by typing out a sentence. The AI figures out what you mean, fills in the fields, and gets it logged, which definitely saves some time.

Connecting conversations to tasks

Here’s where things get tricky. Jira’s built-in AI is helpful, but it works on the assumption that you’re already logged into Jira when a great idea or a critical bug report comes up. But we all know that’s not how it works. The most important stuff usually starts in a Slack channel, a Microsoft Teams chat, or a customer support ticket.

This is where you bump up against the walls of the Atlassian ecosystem. You end up manually copying and pasting those conversations into Jira, which is tedious and almost always loses some of the original context.

A much smoother way to handle this is to use a tool that automatically brings the work into Jira. For instance, eesel AI plugs into the places where work actually begins, like your chat apps and help desks such as Zendesk or Jira Service Management. When a user flags a bug in a support conversation or a PM outlines a new feature in Slack, eesel AI can create a perfectly formatted Jira issue in an instant. It can figure out the issue type, set the priority, and attach the entire conversation for context, all without anyone having to do it manually.

An image showing how eesel AI creates a Jira ticket directly from a Slack conversation, preserving context.

It’s not just about saving a few minutes here and there; it’s about making sure nothing important gets forgotten on its way to the backlog.

Using Jira AI to speed up project execution and support

Okay, so your project is planned out, and the team is busy building. Now a new set of problems pops up. How do you keep everyone on the same page? And how do you solve problems quickly without getting stuck on the same old repetitive tasks?

AI summaries and search

One of the most useful features in Jira’s native AI is its ability to summarize long comment threads. If a ticket has bounced between five different engineers, the new person assigned can just click a button to get the highlights. It’s a great way to catch up without having to read a short novel’s worth of back-and-forth.

Atlassian also added natural language search to JQL (Jira Query Language). So instead of wrestling with complicated syntax, you can just type something like "show me all open bugs for me due this week," and Jira will do the heavy lifting.

But again, the usefulness has its limits. The AI only knows what’s inside Jira. It has no clue that the original project brief is in a Google Doc, the designs are in a Confluence page, and the support team has already solved this exact same problem twenty times over in Zendesk.

Bringing knowledge together for smarter support

To build great software, your team needs the full picture, not just the bits and pieces that live in Jira. This is where having a tool designed to unify all your company knowledge makes a huge difference.

Instead of being confined to Jira, eesel AI connects to all your company’s information hubs. We’re talking Confluence, Google Docs, Notion, and even the history of your resolved support tickets. It creates a single brain that actually understands the context behind your work.

Let me give you a practical example. Say an IT support agent gets a ticket in Jira Service Management about a bug that keeps popping up.

• With native Jira AI: The agent can get a summary of the comments within that one ticket. That’s about it.

• With eesel AI: The agent’s AI Copilot immediately drafts a complete answer. It does this by looking at how your team solved similar tickets before, finding the official troubleshooting steps in Confluence, and pulling the latest update from a Google Doc. The agent gets a perfect, detailed response without ever having to leave the JSM screen.

A screenshot of the eesel AI Copilot drafting a detailed answer within Zendesk by drawing from multiple knowledge sources.

This approach helps slash resolution times and keeps answers consistent because the AI is learning from everything your team knows, no matter where that information is stored.

Automating triage and workflows

Atlassian has some AI-powered features in Jira Service Management that help with basic ticket sorting. It can suggest what kind of request is coming in and help get it into the right category.

But for teams that need more control, a tool like eesel AI’s AI Triage gives you a lot more power. You can create custom workflows that automatically route, tag, and prioritize tickets based on just about anything: the words used, the customer’s tone, or any other rule you can dream up.

A view of the eesel AI Triage dashboard, showing how users can build custom automation rules and workflows.

But here’s the best part: eesel AI lets you simulate your automation rules on thousands of your old tickets before you turn them on. This lets you see exactly how the AI is going to perform and gives you a real forecast of its accuracy. You can roll out new workflows feeling confident they’re going to work the way you expect. Most built-in tools just don’t give you that kind of safety net.

Feature	Atlassian Intelligence (in JSM)	eesel AI
Knowledge Sources	Mostly Atlassian tools (Jira, Confluence)	100+ integrations (Help desks, Google Docs, Slack, Notion, etc.)
Setup	Built-in, but needs Premium/Enterprise plans	Self-serve, you can be live in minutes without talking to sales
Pre-Launch Testing	Limited previews	Run simulations on historical tickets for accurate forecasts
Automation Control	Standard rules	Fully customizable workflows with custom actions and prompts
Pricing Model	Bundled into expensive plans	Transparent pricing, no per-resolution fees

How much does Jira AI cost?

So, what’s the price tag on all of this? With Atlassian, it really depends on your subscription level.

The native Rovo and Atlassian Intelligence features are included in the Jira Cloud Premium and Enterprise plans. They aren’t available if you’re on the Free or Standard tiers. This means that to get things like AI summaries and automated work breakdowns, you have to be on a pricier plan, which can start around $13.53 per user each month.

Third-party AI apps are a different story. You buy them from the Atlassian Marketplace, and they each have their own pricing, which is usually per user.

This is another place where a platform like eesel AI takes a different route. eesel AI’s pricing is based on how many AI interactions your team actually uses per month, not how many people are on your team. This model is often more predictable and budget-friendly, especially for bigger teams. You don’t get a surprise bill just because you hired a few more people or had a month with a lot of customer questions.

It’s about intelligent outcomes, not just tasks

Jira AI recommendations are clearly more than just marketing fluff. If your team operates almost entirely within the Atlassian world, the native tools offer a decent starting point for breaking down tasks and getting quick summaries of ticket histories.

But let’s be realistic, most modern software teams don’t work in a bubble. Your workflows probably jump between Slack, Google Workspace, multiple help desks, and a dozen other tools. If that sounds familiar, you need an AI that can connect all those dots. A specialized platform is the only way to get a complete view of your company’s knowledge and build automation that’s truly smart.

This is exactly what eesel AI is built for. It plugs into the tools you already use, learns from all your company’s information (not just what’s in Jira), and lets you test and deploy powerful AI workflows without the guesswork. You can get it set up in minutes, not months, and have full control over how your AI works.

Ready to get more out of Jira? eesel AI connects to all your company knowledge, automates support in Jira Service Management, and helps your team solve issues faster. Start a free trial or book a demo to see how it works.