What’s the best AI tool for product management? Atlassian's AI Rovo vs. Product Copilot
If you are a Product Manager or Product Owner looking for an AI tool that helps inside Jira and Confluence, you’ll find a few options. In practice, one question comes up again and again: why use Product Copilot if Atlassian Rovo is already there?
Product Copilot and Atlassian’s AI Rovo are often compared, but they solve different problems. This article helps you understand the difference, so you don’t expect the wrong thing from the right tool.
Best AI tool for product management: the short answer is…
… it depends on what you need.
Atlassian's AI Rovo is about AI-supported automation and execution inside the Atlassian ecosystem.
Product Copilot focuses on supporting your overall daily product work.
That difference may sound small. In practice, it is not.
When we started building Product Copilot, we didn’t begin with tools or technology. We started by talking to Product Managers, Product Owners and developers and trying to understand their biggest challenges. Messy backlogs and unclear tickets were not the core problem. They were symptoms.
What people actually struggled with were complex products, knowledge spread across many tools, and the effort it takes to communicate requirements clearly. Long refinement meetings and clarification rounds after a sprint had already started came up again and again.
AI turned out to be a good fit for these problems because it can help structure information, ask the right questions and think along. Jira and Confluence are where product management work already happens, so that’s where Product Copilot lives – to support product work directly, not to optimize the Atlassian tools themselves.
That is why Rovo and Product Copilot feel so different in practice.
What Atlassian’s AI Rovo is built for
Rovo is Atlassian’s AI layer across Jira, Confluence and other Atlassian tools. Its main goal is to connect the Atlassian ecosystem more tightly and support existing workflows with AI. It is directly integrated into Atlassian products.
With Rovo, you can search across Jira issues and Confluence pages using natural language, summarize content on demand, and trigger predefined actions through chat.
In many ways, Rovo extends what Jira and Confluence have always focused on: processes, rules and configurations. The difference is that you no longer have to click through everything manually or write complex JQL queries for simple questions. AI helps you navigate and execute these workflows faster, without manual clicks or complex queries.
You prompt, Rovo executes what you asked. If you think in terms of “when X happens, do Y”, or you want AI to help you work more efficiently inside structured Atlassian workflows, Rovo can help you greatly.
What Product Copilot is built for
Product Copilot takes a very different approach. It is not designed to make Jira and Confluence easier to navigate or to automate workflows. It is an AI tool built to support Product Managers and Product Owners in their most important product management tasks.
Product Copilot behaves more like a smart colleague than a command-based tool. It helps with real product work, uses Jira and Confluence as primary context sources, and lets you save results directly where you work. The goal is not to improve how you navigate your issue tracker, it’s to help you build a great software product and get the work around it done.
The key difference lies in how the interaction works. Prompt-driven tools like Rovo wait for instructions and execute exactly what you ask. Product Copilot thinks along. It does not just create a ticket when you say “create”. It asks follow-up questions, challenges unclear requirements and points out gaps or inconsistencies proactively without needing perfectly phrased prompts.
You might disagree, but we believe your job is not building workflows in an issue tracker. Your job is shaping a product, aligning decisions and working under uncertainty. That is why we built Product Copilot, to support you with exactly that kind of work.
An overview of the facts: Atlassian’s Rovo vs. Product Copilot
| Criterion | Atlassian Rovo | Product Copilot |
|---|---|---|
| Supported Environments | Atlassian Cloud | Atlassian Cloud and Data Center |
| Delivery model | Built directly into Atlassian Cloud products | Browser extension for maximum flexibility |
| Primary purpose | AI layer for Atlassian tools | AI assistant for daily product management work |
| Main focus | Automation, execution and workflows | Support like an experienced teammate, turning raw input into high-quality product work |
| Interaction style | Command-based | Proactive, collaborative |
| Use of product context | Only when explicitly requested | Uses context smartly and proactively |
| Handling unclear input | Executes the request as given | Flags unclear requirements and missing information |
| Features |
|
|
| AI output style | Conservative | Flexible, customizable |
| Best suited for | Structured workflows and repeatable actions | Complex product work |
| Deployment | Fully managed by Atlassian | Flexible, optionally with own Azure OpenAI models |
| Pricing model | Tied to Atlassian plans, same pricing model for all Atlassian users, usage limits | Flexible, per active user or per team, unlimited use |
| What it is not | A product-thinking assistant | A workflow automation engine |
What these differences mean in practice: capabilities, setup and pricing compared
You’re still reading, which probably means you want more than the high-level picture. The differences below are not just our opinion. These are the differences that matter in practice. They are based on what users who tested both tools side-by-side told us when we asked why they chose Product Copilot instead of Rovo.
Interaction: execution of commands and workflows vs. thinking along
Rovo waits for input. You tell it what to do, and it executes. It works well for predefined tasks, clear commands, repeatable actions and structured workflows. What it does not do is question your input, challenge assumptions or think ahead. It executes instructions.
Product Copilot is designed to focus on the content of your work and actively think with you. It uses Jira and Confluence context proactively, asks follow-up questions, points out unclear requirements, challenges vague tickets and brings up related context you did not explicitly ask for. For example: You are creating a user story – but there already is a similar one. Product Copilot will let you know.
That is not a small UX difference. It is a completely different philosophy.
Context usage: on-demand access vs. proactive use
Context decides whether AI helps you or just produces nice-sounding nonsense. Both tools can access Jira tickets and Confluence pages, but how they use that context is where the difference becomes obvious very quickly. With Rovo, Jira and Confluence context is available, but is only used when you explicitly ask for it. You prompt, Rovo fetches, Rovo responds.
Product Copilot uses Jira and Confluence (but also Figma, your codebase or additional provided documents) as active knowledge sources. This leads to more relevant answers and fewer hallucinations with less prompting.
Users who tested both tools side by side often told us the same thing: with Product Copilot, they spent less time fixing AI output and more time actually thinking about their product.
Tool intent: Atlassian platform optimization vs. product work optimization
Rovo’s strength is how well it connects the Atlassian stack. It pulls knowledge from Assets and Jira Service Management and links it easily with Jira and Confluence. That makes it powerful inside Atlassian. But Rovo is not a software product management AI. It’s an Atlassian AI.
Product Copilot focuses on one thing only: software product work. It’s built for Software Teams, whether you are a Product Owner, Product Manager, Developer, Software Tester or Scrum Master. It comes with preconfigured prompts that mirror real product work based on the best practices of experienced product teams.
Writing tickets. Refining backlogs. Creating documentation. Rovo can do all of that – if you prompt it correctly. You prompt it, and a Jira ticket appears. But it doesn’t check whether the problem is clear, whether the scope is too big, or whether the acceptance criteria are testable. Making sure it's a good user story is still up to you.
With Product Copilot, your effort goes into your product, not into prompt engineering. We’ve built Product Copilot with product expertise and have done the prompt work upfront, so you get solid results for everyday product tasks.
AI performance: predictable templates vs. practical results
Rovo is built to stay within predefined boundaries. That makes it predictable for simple tasks like summaries or straightforward requests, but also more static and constrained. This is a deliberate choice by Atlassian to keep outputs conservative and tightly controlled.
In practice, it often feels like a classic chatbot attached to Jira: useful for executing clear instructions, but limited when the work becomes messy or ambiguous.
Product Copilot is designed for more complex product work where context, trade-offs and incomplete information are the norm. We deliberately use more capable models and allow them more flexibility in how they reason and respond, because product work rarely fits into strict templates.
With Rovo, outputs often look good at first glance because they follow familiar templates and standard phrasing. Users report that these results tend to stay generic, leave important questions unanswered and require manual rework before they are actually useful.
A user story that reads “As a user, I want to …” may look correct, but no developer wants to work with generic text. They need the important facts, constraints and decisions. Otherwise, they will ask, clarification meetings follow, and the time saved writing the ticket is lost elsewhere. Product Copilot focuses on output that supports real implementation, not just output that looks right in a template.
Supported environments: Atlassian Cloud vs. Jira and Confluence Data Center
By now, we all know it: Atlassian is on a cloud-first march. That works well for some teams, but for many large enterprises with years of valuable knowledge in their Data Center instances, moving to the cloud is not something you just do. These migrations take time. Often years, not months.
Telling product teams to wait with AI support until a future cloud migration was done sounds harmless on paper, but it has real consequences. Teams keep doing more work manually, decisions take longer, and people get frustrated because they know better tools exist but are not allowed or available to them yet. Product work does not pause for three or five years, and neither does the competition.
Rovo is built exclusively for the Atlassian Cloud ecosystem and is not available for Data Center environments. Product Copilot works with all Jira and Confluence Data Center setups as well. It meets teams where they are, not where they might be in a few years.
AI model hosting: Atlassian-managed vs. flexible hosting options (incl. Azure OpenAI hosting)
For many teams, the question is not whether using AI is helpful, but whether it meets their security requirements.
Product Copilot offers flexible deployment and hosting options, including the ability to use your own Microsoft Azure OpenAI models. If you need data residency in Europe, Product Copilot can support that. This is relevant for organizations with strict compliance requirements, regulated environments, or clear policies about where data is processed.
Pricing model: instance-wide vs. only for those who use it
Atlassian apps have long followed an “everyone or no one” model. You wanted to use a tool with a few people, but you pay for the entire Atlassian instance. Rovo changes the packaging, not the principle. It is currently included in Jira Standard, Premium, and Enterprise (not available for Free), which means access and cost are still tied to your Jira plan and total user count.
Rovo usage is limited by a shared monthly credit pool. These credits make it easy to try out AI capabilities, but run out quickly even if only a few people use the tool regularly. Additional credits are billed separately.
It’s also worth noting that Atlassian is changing Rovo pricing, availability, and limits frequently. The model is not stable yet and has already shifted several times in the last months.
The pricing for Product Copilot works differently. Product Copilot runs as a browser extension, independent of your Atlassian plan, and is licensed per active user or per team. Only the people who actually use the tool need a license. There are no credit pools and no artificial usage limits. This makes it possible to work with the tool on a regular basis instead of rationing usage. You can start with the people who actually need it, build real routines, and expand when it makes sense.
Conclusion: The differences in a nutshell
Rovo and Product Copilot do not cancel each other out. They are built for different jobs.
Rovo is a good choice if you want AI-powered workflows, structured automation and command-based interactions that are tightly integrated into Atlassian tools. It fits teams that think in processes, rules and execution.
Product Copilot is the better choice if you want a smart teammate that is built for product work. It thinks along proactively, understands your product context and supports the kind of decisions Product Managers and Product Owners make every day, far beyond the context of Jira and Confluence, even if those are the tools you use most.
So how do you decide?
AI tools are hard to judge based on feature lists alone. Atlassian will tell you Rovo is the best solution. We are a bit biased too. But you know your workflow and your product best and you can only decide which AI supports you best if you try them. While you write tickets, refine a backlog, prepare a sprint or think through a product decision.
If you are serious about finding the best AI tool for your product team, try them in real work. Side by side. Use them for a month. The tool that actually helps you is the one you should use.
If you want to see how Product Copilot works in your environment, try it for free. No migration, no big rollout. No Atlassian admin needed. Don’t overthink it, just start something.