If you’re a product manager, your brain probably feels like a browser with way too many tabs open. You've got feature requests coming from the sales team, bug reports piling up from support, a few brilliant shower thoughts, and a constant stream of customer feedback. The hard part isn't just collecting all these ideas, it's making sense of the chaos and turning that jumbled pile into a roadmap that actually works.
Atlassian’s latest attempt to help with this is Jira Product Discovery, a tool meant to be a home for all those big ideas. And now, they’re adding their new AI toolkit, Atlassian Intelligence, into the mix. The big promise is that it will speed up brainstorming, using AI to generate and organize ideas so you can get to the good stuff faster.
So, how does it actually hold up in the real world? Let's walk through what these new AI features do, how the workflow is supposed to go, where the cracks start to show, and of course, how much it's all going to cost you.
What is Atlassian Intelligence Brainstorming in Product Discovery?
First, let's break down the two main pieces of this puzzle.
Jira Product Discovery is Atlassian's answer for product teams drowning in ideas. You can think of it as a central hub where all your feature requests, user feedback, and half-baked concepts can live before they’re ready to become official development work. It’s all about adding some much-needed structure to the messy, early stages of product management.
Then there's Atlassian Intelligence. This isn't a separate app you buy. It’s the brand name for all the AI features Atlassian is sprinkling across its products, from Jira to Confluence. It acts like an assistant that’s always there, ready to automate tasks, summarize long documents, or give you a smart suggestion.
So, when we talk about Atlassian Intelligence Brainstorming in Product Discovery, we're mostly talking about a set of AI tools inside Confluence Whiteboards that connect directly to Jira Product Discovery. The main goal is to help your team come up with, sort through, and summarize ideas more efficiently, turning a chaotic brainstorming session into a clear list of things to work on.
Core features
Atlassian has rolled out a few key AI features that are designed to make brainstorming feel less like a chore. Here's a look at what you can actually do with it.
Generate ideas from a simple prompt
We’ve all been there: staring at a blank whiteboard, waiting for inspiration to strike. Atlassian Intelligence tries to fix this. You can start a session in a Confluence Whiteboard with a single thought, like, "How can we make our mobile app’s onboarding less painful?"
The AI then populates the board with a bunch of related ideas on virtual sticky notes. You might see suggestions like "Add a quick video tutorial," "Turn the setup into a game," or "Let people sign in with their social accounts." The neat part is that it can pull some context from your existing Confluence pages or Jira tickets, so the ideas it spits out feel at least somewhat connected to what your team is already working on.
Automatically group ideas into themes
After everyone has thrown their ideas onto the board, you’re usually stuck with the job of sorting through the mess. This is where the AI's "clustering" feature comes in handy.
With a single click, the AI reads all the sticky notes and groups similar ones into themes. For instance, ideas like "add tooltips" and "create a tutorial" might get bundled under a "User Education" theme. Meanwhile, "add a progress bar" and "celebrate milestones" could be grouped as "Better Engagement." It saves a lot of time and lets your team start talking about the bigger picture instead of getting bogged down in tiny details.
Summarize your session and create next steps
Once the session wraps up, you need to figure out what you actually decided. The AI can generate a quick summary of the whole discussion, pulling out the main themes and most popular ideas.
What's really useful is that you can immediately do something with that summary. You can turn it into a new Confluence page to have a clean record of the meeting, or you can use it to create a bunch of Jira issues at once. This smooths out the transition from a free-form brainstorm to your structured development backlog, so good ideas don't just fade away.
The workflow and its limitations
On paper, the whole process looks fantastic. But when you start thinking about the day-to-day reality of product management, you notice a couple of big issues.
The ideal workflow (in Atlassian’s world)
The path Atlassian lays out is clean. A product team gets together in a Confluence Whiteboard, uses AI to generate and organize ideas, and then pushes the best ones into Jira Product Discovery. For teams that do everything inside the Atlassian suite, it’s a pretty slick setup that keeps everyone on the same page.
But let’s be honest, most companies don’t work that way.
Limitation 1: All your best knowledge is somewhere else
Atlassian Intelligence is smart, but it can only see what's inside its own ecosystem. It learns from your Confluence pages and Jira tickets, and that’s about it. This creates a huge blind spot.
Think about where your most valuable product insights actually come from. They're hidden in Zendesk tickets from frustrated customers, in notes from sales calls on Google Docs, and in urgent debates happening on Slack. If your AI can't access any of that, your brainstorming is happening in a vacuum, totally disconnected from what your customers are actually saying. You could spend a whole afternoon dreaming up a new feature, only to find out later that the support team is drowning in tickets about a simple bug your AI knew nothing about.
A genuinely helpful AI needs to see the whole picture. That’s the problem platforms like eesel AI are built to solve. It connects all your company's knowledge, from your helpdesk to your chat tools, to give your AI a complete foundation. That way, your brainstorming is based on what’s actually happening, not just what’s written down in Confluence.
Limitation 2: Brainstorming without data to back it up
Coming up with ideas is easy. Figuring out which ones to build is the hard part. Atlassian Intelligence can group ideas into themes, but it has no way of telling you which theme your customers care about most.
For example, the AI might create a cluster of ideas about "improving the login process," but it can't tell you that this exact issue was mentioned in 500 support tickets last month, making it a massive source of frustration. This leaves you right back where you started: digging through other tools to find data that proves your roadmap is the right one, which kind of defeats the point of having an efficient AI workflow.
This is a huge gap. An AI should be able to do more than just generate ideas. With a tool like the eesel AI Agent, for instance, you could see how an AI would have handled past support tickets. This gives you real, measurable insight into which product fixes would actually reduce your support load and make customers happier.
Pricing
It's important to know that Atlassian Intelligence isn't just a free update for everyone. The really useful brainstorming features are only available on their more expensive plans.
First off, you need a Jira Product Discovery subscription. There's a free plan, but it's pretty basic. To get the AI tools, you have to upgrade to the Premium plan.
Here's a quick look at the pricing, based on Atlassian's official site:
| Plan | Price (per creator/month) | Key Features for Brainstorming | Atlassian Intelligence |
|---|---|---|---|
| Free | $0 (up to 3 creators) | Basic idea capture and list views | No |
| Standard | $10 | Published views, custom project roles | No |
| Premium | $25 | Roadmaps across projects, idea hierarchies | Yes |
As you can see, you have to jump to the $25 per creator, per month Premium plan to get the AI features. For a small product team of five, that's an extra $1,500 a year just for AI tools that are still stuck inside the Atlassian bubble.
Is Atlassian Intelligence Brainstorming in Product Discovery the future?
What’s the final verdict? Atlassian Intelligence offers a very polished brainstorming experience for teams that are all-in on the Atlassian ecosystem. Being able to go from a messy whiteboard to organized Jira tickets in a few clicks is genuinely nice.
But its biggest strength is also its fatal flaw. It’s a closed system by design, which means it’s completely blind to the messy, honest, and incredibly valuable feedback living in all your other tools. It's a step forward for making internal meetings a bit smoother, but real AI-powered product discovery needs to connect every piece of company knowledge, not just the bits that live in one place.
Going beyond Atlassian Intelligence Brainstorming in Product Discovery
This is where you can fill in the gaps Atlassian leaves behind. eesel AI connects to Jira and Confluence, but it also plugs into all the other places where your customer and team knowledge lives.
Instead of brainstorming in an echo chamber, you can use a tool like eesel’s AI Internal Chat to ask questions and generate ideas from a knowledge base that includes everything, from the latest customer complaints in Zendesk to the project specs in your Google Docs. You get the whole story, so you can build a roadmap that actually solves real problems.
You can get it running in just a few minutes and see what’s possible when your AI can finally access all your knowledge. Try eesel AI for free today.
Frequently asked questions
Atlassian Intelligence Brainstorming in Product Discovery refers to a set of AI-powered tools within Confluence Whiteboards, designed to help product teams generate, organize, and summarize ideas more efficiently. These tools connect directly to Jira Product Discovery, allowing for a smoother transition from brainstorming to structured development work.
The core features include the ability to generate new ideas from a simple prompt, automatically group similar ideas into themes, and summarize entire brainstorming sessions. These summaries can then be easily converted into new Confluence pages or Jira issues for next steps.
Yes, it is deeply integrated within the Atlassian ecosystem. Specifically, it leverages AI capabilities within Confluence Whiteboards and is designed to push finalized ideas and summaries directly into Jira Product Discovery for further management and action.
A significant limitation is its reliance on data exclusively within the Atlassian ecosystem (Jira, Confluence). It cannot access valuable insights from external tools like Zendesk, Slack, or Google Docs, which can lead to brainstorming in a vacuum disconnected from a company's full knowledge base.
To access the full AI brainstorming features, you need to subscribe to the Jira Product Discovery Premium plan, which costs $25 per creator per month. These AI functionalities are not available on the Free or Standard Jira Product Discovery plans.
While it can group similar ideas, Atlassian Intelligence Brainstorming in Product Discovery cannot prioritize them based on external customer feedback or data from other systems like support tickets or sales calls. This means teams still need to manually cross-reference data from outside the Atlassian ecosystem to validate and prioritize ideas.
It offers a polished experience for teams fully committed to the Atlassian ecosystem. However, for teams that rely heavily on a diverse set of tools for customer feedback and internal knowledge, its closed system nature might be a limitation, as it won't factor in insights from those external platforms.
