By Denis Boisvert, Solutions Architect, Engineering & Dave Rosenlund, Global Director of Software & Solutions at Trundl

AI tools are everywhere these days. Teams often ask us a variation of the same question:

“We have Rovo in our Atlassian Cloud – but we also use ChatGPT. When should we use each?”

Read the original on Atlassian Community

This isn’t a marketing comparison. It’s about practical, everyday work: what Rovo does well today, where it still has limits, and how to make your tool choices deliberate – not hype‑driven.

Here’s the short version: Use Rovo where structure and existing data are important; use general-purpose AI for discovery, exploration, and creativity.

🧠 Rovo’s Strengths – What It’s Really Good At

In our experience with customers, Rovo shines when:

Work fits clear patterns – like summarising Confluence pages, extracting action items, or classifying Jira issues. These are bounded problems, and Rovo handles them reliably.

Data already lives in Atlassian – because Rovo’s intelligence layer uses your Teamwork Graph to connect Jira, Confluence, and linked tools.

You want less context switching – rather than flipping between Slack, Google Drive, Jira, and Confluence, Rovo brings info and actions into the work context you’re already in.

Repetitive processes benefit from automation  – agents in Rovo can create issues, assign labels, and generate summaries for common workflows.

“Fantastic write‑up! It’s easy to get caught up in AI hype – this grounded perspective helps teams decide based on real value.”

– Atlassian Team commenter on the original article

🧪 Where Rovo Has Limits (and Still Needs Humans)

But Rovo isn’t magic, and it’s not a full “co‑pilot” yet.

Here’s what we’ve seen:

• It excels on structured, predictable tasks – but gets inconsistent when the question is open‑ended or ambiguous.
• When there are missing fields, unexpected inputs, or permission quirks, agents can fail silently – and don’t recover without human direction.
• It doesn’t learn your team’s preferences or deeply understand organizational context the way a human teammate might.

That’s why we say, Rovo is a work accelerator – not a replacement for thoughtful judgment.

🤖 ChatGPT (and Similar Tools) Still Matter

Here’s the practical split that we suggest:

Use Rovo agents when the work lives inside Jira or Confluence and benefits from reduced manual steps. Think: Summarise meeting notes into action items, group issues by pattern, extract key decisions from documentation. Use ChatGPT (or other general‑purpose LLM tools) when you’re exploring, drafting, ideating, or wrestling with ambiguity. This is where free-form text generation and creative reasoning still outperform structured agents.

In many cases, the most effective teams use both in tandem – explore externally with ChatGPT, then operationalise with Rovo inside your Atlassian environment.

🤝 Adoption Starts with Trust

One point we emphasise with customers is that no tool matters if your team doesn’t trust its outputs.

Before adopting Rovo deeply, make sure your security, compliance, and business leadership have aligned on how AI tools handle data – that’s foundational.

🧩 Balance > Hype

Rovo is real, useful, and evolving quickly – but it works best when you:

AI isn’t a silver bullet – it’s a toolbox. And the teams that succeed are the ones who match the tool to the problem.

Denis & Dave are two of Trundl’s six Atlassian Community Champions.