A practical guide to Jira Product Discovery AI features

Product discovery is a messy process. You’re trying to sort through a mountain of ideas, customer feedback, and random insights to figure out what your team should actually build next. Atlassian is trying to clean this up with Jira Product Discovery (JPD), and recently, they’ve thrown some AI into the mix.

So, what do the Jira Product Discovery AI features actually do? How much will they set you back, and are they really the right tool for your team?

Let’s break down what the AI inside JPD, powered by Atlassian Intelligence, is all about. We’ll get into the specific features, the pricing and plan limits you need to be aware of, and where it might not be enough for teams needing more powerful, connected automation.

What are Jira Product Discovery AI features?

First up, a quick refresher. Jira Product Discovery (JPD) is Atlassian’s space for product teams to capture, prioritize, and map out ideas before they ever become a ticket in a development sprint. Think of it as the "fuzzy front end" of product development, where you bring some order to the chaos of brainstorming.

The Jira Product Discovery AI features aren’t a separate tool but are built right into the text editors you already use in JPD, like in an idea’s description field or a comment thread. These capabilities come from a broader platform called Atlassian Intelligence.

Right now, the AI features in JPD are all about generating and polishing text. You can use them to:

• Brainstorm a few ideas: If you’re staring at a blank page, you can ask the AI to generate some starting points or topics for discussion.

• Rewrite and clean up content: This is the main event. You can highlight text and ask the AI to summarize it, change the tone to sound more professional, or just fix your spelling and grammar mistakes.

• Get a quick summary: Quickly digest long idea descriptions or comment threads to understand the main points without reading every single word.

In short, Atlassian Intelligence acts like a writing assistant inside JPD. It’s handy for making your notes and ideas clearer, but it doesn’t do the heavy lifting of the discovery process. It won’t, for instance, analyze raw customer feedback from your help desk or spot trends across a dozen different sources.

Atlassian Intelligence: The AI powering the Jira Product Discovery AI features

Atlassian Intelligence is the engine running in the background of many Atlassian products, not just JPD but also Jira and Confluence. It uses technology from OpenAI combined with Atlassian’s own models, which are trained on something they call the "Teamwork Graph."

The Teamwork Graph is a map of how your projects, issues, and people are connected within your organization. The idea is to give the AI context that’s specific to your team. So, when you ask it to summarize something in JPD, it theoretically understands the related Jira tickets or Confluence pages.

But here’s the catch: its worldview is limited to the Atlassian universe. Most companies don’t keep all their knowledge locked up in Atlassian tools. Critical customer feedback is sitting in Zendesk, important strategy docs are in Google Docs, and countless decisions are made in Slack. Atlassian Intelligence can’t see any of that, which means its "context" is pretty incomplete.

An AI for product discovery that’s actually effective needs to connect to all your knowledge, no matter where it is. This is the whole idea behind platforms like eesel AI, which integrate with your entire tool stack to create one unified source of truth. By linking to your help desks, wikis, and chat tools, it can give you insights based on the complete picture, not just a small part of it.

This workflow shows the difference between a siloed AI like Atlassian's, which only works internally, and a connected AI like eesel AI, which can automate actions across customer-facing tools.

Jira Product Discovery AI features pricing

This is where things can get a little painful for a lot of teams. The Jira Product Discovery AI features aren’t included in every plan. To get access, your team needs to be on the Premium plan.

Jira Product Discovery uses a freemium model. The Free plan is fine for very small teams (up to 3 creators), and the Standard plan unlocks the core features. But to use Atlassian Intelligence, you have to leap up to the Premium plan, and it’s a pretty big price jump.

Here’s a quick look at the plans and where AI shows up:

Feature	Free	Standard	Premium
Price (per creator/month)	$0	$10	$25
Creators	Up to 3	Unlimited	Unlimited
Core Features (Views, Insights)	✓	✓	✓
Roadmaps		✓	✓
Admin insights			✓
IP Allowlisting			✓
99.9% SLA			✓
Atlassian Intelligence (AI)			✓

As you can see, AI is strictly a premium feature. For a product team of five, that means paying an extra $75 per month over the Standard plan just to get some text summarization and editing tools. For bigger companies, that per-seat pricing for AI can add up fast.

This model is quite different from platforms like eesel AI, which offer more straightforward pricing based on usage (how many AI interactions you have) instead of charging every single user for AI access. With eesel AI, your whole team gets access to AI agents, copilots, and internal chat under a single, transparent plan.

Limitations of the Jira Product Discovery AI features

While having a writing assistant built-in is a nice touch, the AI in JPD has some major limitations that product teams should know about before upgrading.

It’s only for generating text

The main job of Atlassian Intelligence in JPD is to help you write better. It can summarize, rephrase, and brainstorm. But it doesn’t automate any of the actual work of product discovery. For example, it can’t:

• Automatically scan incoming feedback from a help desk and group it by theme.

• Flag that 50 different customers have requested the same feature this month.

• Triage new ideas and route them to the right product manager based on the content.

It helps you write down your discoveries, but it doesn’t help you find them in the first place.

It’s stuck inside the Atlassian ecosystem

We touched on this before, but it’s a big deal. Atlassian Intelligence only knows what’s in Atlassian’s tools. Your real product discovery process, however, pulls from data all over the place. Think about it: customer support tickets, sales call notes, user research interviews, and competitor analysis docs are all packed with insights.

Because JPD’s AI can’t reach that external information, you’re still stuck doing the manual, time-sucking work of gathering, reading, and making sense of feedback from all those different apps before you can even drop it into JPD to be summarized.

It can’t take action

A truly useful AI should be able to do things for you. The AI in JPD is passive; it waits for you to give it a command inside a text box. It can’t act on its own.

In contrast, a platform like eesel AI includes a customizable workflow engine. You can build AI agents that not only understand requests but also take action. For instance, an eesel AI agent can:

• Triage tickets: Automatically categorize and route support tickets that contain product feedback.

• Tag issues: Apply the right tags to ideas based on sentiment or certain keywords.

• Fetch external data: Look up customer info in your CRM or order data from Shopify to add valuable context to an idea.

• Learn from your history: Analyze thousands of past support conversations to understand your common problems and customer language, giving you a goldmine of insights that JPD’s AI is completely blind to.

On top of that, eesel AI lets you test your automations in a simulation mode, so you can see exactly how an AI agent will behave with your historical data before you let it loose. This kind of risk-free setup just isn’t an option with JPD.

A better way to use AI: Going beyond the Jira Product Discovery AI features

If your team already uses JPD and likes it for roadmapping and managing ideas, you don’t have to abandon it to get better AI. Instead of settling for Atlassian’s limited, walled-off intelligence, you can add a dedicated AI layer that connects to all of your tools.

This is exactly what eesel AI is built for. It acts as the central AI brain for your company, integrating smoothly with JPD and all the other apps you rely on.

Here’s a simple breakdown of how it works:

1. Connect all your knowledge: Hook up eesel AI to all your sources of information. This includes your Jira instance (so it can see your JPD ideas), but also Confluence, Google Docs, Zendesk, Slack, and more.

2. Ask questions about anything: With eesel AI’s Internal Chat, you can ask plain-language questions like, "What are the top 3 feature requests from our enterprise customers this month?" eesel AI will pull together an answer using data from support tickets, JPD ideas, and sales notes.

3. Automate your feedback loop: You can set up an automation that spots trends in your support tickets. When a new theme starts popping up, eesel AI can automatically create a new, detailed idea in your Jira Product Discovery project, complete with links back to the original tickets.

This workflow shows how a powerful AI can connect to multiple data sources like Zendesk, Slack, and Google Docs to provide a complete picture for product discovery, unlike the limited Jira Product Discovery AI features.

With this approach, you get the best of both worlds. You keep the familiar roadmapping and prioritization tools in JPD, but you supercharge it with a cross-platform AI that does the hard work of finding insights and automating your workflows.

Wrapping up our review of the Jira Product Discovery AI features

The Jira Product Discovery AI features are a decent first attempt at AI-assisted product management. The text editing and summarization tools can certainly help you write more efficiently.

However, these features are stuck behind an expensive Premium plan, are confined to the Atlassian ecosystem, and don’t offer any real automation. They help you document your work, but they don’t actually do the work for you.

For teams that want to seriously use AI to speed up their product discovery, a more capable, dedicated platform is the way to go. Instead of waiting for Atlassian Intelligence to catch up, you can connect your tools to eesel AI today and get a true AI brain for your entire discovery workflow. It brings your scattered knowledge together, automates the tedious stuff, and finds the deep insights you need to build what actually matters.