Few developers chose their profession to write endless Jira comments, spend hours on manual triage, or dig through complex JQL searches. But in 2025, the game has changed. Atlassian’s new AI capabilities are seriously removing friction from daily workflows, giving developers more time for what truly matters: building smart solutions.
AI in Jira opens new opportunities to enhance the developer’s work, cutting hours spent on manual queries, making onboarding smoother, and improving communication and knowledge sharing within the team. For leaders and decision-makers, the benefits go even further.
Automation directly impacts product time-to-market, team well-being, and organizational scalability. Less administration means faster deliveries. Reduced friction boosts motivation and lowers the risk of burnout. And AI-generated insights provide leaders with a clearer picture of bottlenecks and progress, without needing to dive into the details themselves.
Just as test automation once transformed how we build quality, AI-driven workflow automation is now reshaping how we manage and lead development work. The earlier companies adopt it, the more natural it becomes to let AI handle the repetitive – so both developers and leadership can focus on what truly drives projects and business value.
Automation you can feel immediately
What makes AI in Jira particularly powerful is that the functionality isn’t “just another plugin”, it’s built into the platform itself. AI can suggest who should take a ticket based on team history, condense long discussion threads into short summaries, and break down larger stories into smaller, manageable tasks. It can also recommend priorities based on what the team actually tends to start with, instead of just following backlog order. The result: less time lost to administrative noise and more time spent on value-creating development.
Natural language instead of JQL
For many new team members, mastering advanced JQL searches has been a hurdle. With Atlassian’s generative AI, you can now simply write in plain language: “Show all bugs in the sprint that are blocking release.” Jira translates it directly into a correct query. This makes onboarding easier and frees up time even for experienced developers who’d rather code than memorize syntax.
A hub for hybrid teams
As more teams work in distributed setups, knowledge sharing becomes an increasing challenge. Here, AI acts as a hub. By summarizing discussions and creating context, it ensures no one loses the big picture, even in projects spanning different time zones or working hours.
Five tips to get started
Enable Atlassian Intelligence
The first step is often overlooked: make sure AI features are actually turned on in your Jira instance. Many teams already pay for a license that includes AI but haven’t taken the time to explore it. “Flipping the switch” is critical to start experimenting and finding where the value lies.
Practice with the built-in tools
Build a culture where testing AI becomes part of the everyday workflow. For example, have the team use AI-generated summaries of long threads before standups, or try natural language search during backlog refinement. Small steps help AI quickly become a habit, lowering the barrier to adoption.
Adapt to your team’s needs
Default settings are fine to get started, but real impact comes when AI reflects your team’s workflows. Do you have a specific bug-handling process or a structured onboarding routine for new developers? Create rules and automations that support these scenarios. That way, AI strengthens your ways of working instead of adding friction.
Stay aware of limitations
AI is powerful, but not flawless. Treat it as an assistant that sometimes needs supervision. If a summary looks odd: double-check. If an assignee recommendation doesn’t feel right: adjust it. Keep an eye on Atlassian’s roadmap too, since the functionality is evolving rapidly and new tools can quickly change your daily work.
Use AI in retros and planning
Let the system summarize sprint highlights, blockers, and recurring patterns. This frees up time in retrospectives to focus on solutions and improvements instead of spending half the meeting recalling what happened. The same applies to planning: let AI break down stories into tasks so you can focus on priorities and strategy.
Conclusion
AI in Jira is not a gimmick, it’s a tool that’s already transforming how development is organized and delivered. For developers, it means less time on repetitive tasks and more focus on creative problem-solving. For decision-makers, it means faster time-to-market, sharper insights, and more motivated teams.
The earlier organizations start exploring these features, the more natural it becomes to let AI handle the repetitive, and free up energy for what truly drives innovation and business growth.
Want to know more about how we at HiQ can help your business with Jira or other Atlassian solutions? Get in touch!
