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March 02.2025

2 Minutes Read

Transforming Service Management with AI: The Impact on Atlassian's Jira Service Management

Confetti bursting from a party popper, symbolizing celebration.

The Rise of AI in Service Management

As we move deeper into 2025, we're witnessing a remarkable transformation in service management, underpinned by the advancements in artificial intelligence (AI). Organizations have embraced AI not as a trend but as a core component of their operational strategy. According to recent reports, an astonishing 88% of organizations have already integrated AI into their service management processes, and 89% are boosting their investments in AI applications this year.

Exploring Agentic AI in Jira Service Management

Among the pioneers in this domain is Atlassian with its Jira Service Management platform. With its latest upgrades in AI capabilities, Jira not only enhances IT operations but also simplifies employee support and enriches HR service delivery. This is where agentic AI comes into play. This technology provides autonomous AI systems capable of managing tasks with minimal human oversight, promising to reduce the burden of service operations significantly.

Real-World Applications and Benefits

One of the most exciting features is the new AI-generated summaries, which provide intuitive overviews of employee requests and suggested next steps. This capability streamlines the workflow, saving valuable time for IT teams. Furthermore, organizations can expect an impressive 30% increase in ticket handling efficiency and faster approval returns on change requests, transforming how operational tasks are executed.

The Future of Work: People-Centric ITSM

Interestingly, while AI plays a significant role, Atlassian emphasizes that enhancing the human experience in IT service management is equally important. By focusing on a people-centric approach, companies are recognizing that the quality of service directly impacts employee satisfaction and productivity. The feedback loops through AI-generated insights ensure that the needs of the workforce remain at the forefront.

Conclusion: An Invitation for Innovation

As we navigate this new landscape defined by AI, companies like Atlassian are not just setting the pace but are inviting businesses worldwide to join the movement. The ongoing evolution of service management through AI is not just technology-driven; it’s about creating a more efficient, responsive, and human-centric approach to delivering services efficiently. It's time for organizations to tap into these advancements and transform their service delivery model.

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02.01.2026

6 Async Practices to Uncover Insights and Boost Team Productivity

Update Unlocking Team Insights: The Power of Async Practices In today's fast-paced work environment, knowledge workers are inundated with information yet often find themselves unable to access relevant insights when they are needed the most. A report from Atlassian reveals that Fortune 500 companies waste an astounding 2.4 billion hours annually just searching for information. This indicates a severe lack of visibility into prior research, project histories, and valuable insights that could streamline workflows and enhance decision-making. Async Practices to Enhance Collaboration Adopting deliberate asynchronous practices can be a game-changer for teams looking to unearth buried insights. Here are several strategies that can catalyze better collaboration: Write Before You Meet: Encourage team members to articulate their ideas in writing prior to meetings. This practice avoids biases that arise in real-time discussions, promoting clearer thought and more thoughtful contributions from all participants. Design for Time-Delayed Contribution: Implement structured response windows to ensure everyone can contribute, leveling the playing field for insights regardless of time zones or individual response speeds. Intentionally Invite Disagreement: Foster an environment where team members feel comfortable voicing differing opinions. Creating spaces for constructive dissent can unearth critical insights that might otherwise remain obscured. Separate Idea Generation from Evaluation: Distinguish between brainstorming new ideas and assessing them. This allows creativity to flourish without immediate judgment, leading to a wider array of potential solutions. Surface Summaries: Consistently recap discussions and decisions. Summaries act as a valuable resource for future teams, preventing redundant efforts and reinforcing the existing knowledge base. Create Dedicated Async Thinking Spaces: Establish channels or documents where team members can share thoughts or questions as they arise, ensuring that valuable ideas are captured before they vanish. Leveraging AI to Maximize Async Benefits Artificial Intelligence (AI) can be an empowering ally in executing these async practices more effectively. Tools like AI-based notetakers can automate the summarization process after discussions and ensure all are aligned on key decisions. Moreover, AI can help analyze patterns in team contributions to surface insights that might have gone unnoticed. For instance, AI can organize inputs by themes and flag unique perspectives that differ significantly from the majority. Conclusion: Moving Towards Better Decision Making As teams embrace these async practices, they not only enhance the visibility of crucial insights but also streamline their processes. By integrating AI tools effectively, organizations can turn the challenge of information overload into an opportunity for growth and innovation. The bottom line is simple: thoughtful async collaboration can transform how teams function, allowing them to do more with less, and ultimately leading to more informed, quicker decisions.

01.31.2026

Discover How Atlassian's Rovo Think Deeper Revolutionizes AI for Agile Teams

Update Enhancing Workflows with Rovo: The New Standard for AI IntegrationIn today's fast-paced work environment, the quality and speed of problem-solving can make all the difference. Atlassian has introduced an innovative tool called Think Deeper, integrated within its Rovo AI platform. Designed for scenarios where quick responses fall short and extensive reports are unnecessary, Think Deeper strikes a balance that allows teams to enhance their operational efficiency without getting bogged down in information overload.Rovo's Think Deeper functionality redefines how teams engage with AI. Instead of providing a simple answer or a lengthy document, it employs a systematic approach: breaking down queries into manageable parts, analyzing intermediate results, and ensuring that all relevant aspects of a request are addressed. This enhances understanding and decision-making, particularly in complex projects.Empowering Teams with the Teamwork GraphOne of the standout features of Rovo is its Teamwork Graph, which contextualizes information across various Atlassian products like Jira and Confluence. By understanding the interconnections between teams, projects, and data, Rovo eliminates confusion and knowledge silos, empowering users to make informed decisions.For instance, if an HR department needs to consolidate feedback and policies regarding hybrid work, they can input various data points into Rovo. The AI processes this information, generating a clear, up-to-date hybrid work policy that reflects current employee sentiments. This capability demonstrates Rovo's value in real-world applications, as teams see tangible results from its reasoning.AI-Driven Decision-Making for Agile TeamsWith the agile methodologies that many organizations adopt, the need for rapid yet accurate decision-making is paramount. Think Deeper was built to handle multifaceted tasks, avoiding superficial responses and instead anchoring recommendations within specific organizational contexts. This functionality ensures that every decision is based on thorough analysis, hence improving overall productivity.In an engineering context, for example, Rovo's AI can review recent project updates against documentation, ensuring that all materials are current and relevant. This reduces the frequent mismatches between documentation and actual project status, allowing engineers to focus more on development rather than administrative tasks.The Future of Work with Atlassian's RovoAs teams increasingly trust AI solutions for complex problem-solving, it's crucial that the technology evolves to meet their needs. Rovo's innovative approach, particularly through features like Think Deeper, enhances human-AI collaboration. This powerful synergy positions Atlassian at the forefront of AI integration in businesses, supporting teams in navigating the complexities of modern workflows more effectively.In summary, Rovo's Think Deeper functionality is a game-changer for organizations seeking to improve efficiency while maintaining high-quality outcomes. Those who embrace this transition will find themselves well-equipped to tackle the challenges of tomorrow.

01.30.2026

How Atlassian Revolutionized Software Development with AI: 45% Faster PR Cycles

Update The Revolution of Code Reviews at Atlassian Atlassian faced a pressing challenge: its median pull request (PR) review time had ballooned to over three days, leaving developers in limbo as they awaited review comments, often for a significant 18 hours. This delay not only hampered productivity but also stunted innovation, especially given the accelerated pace of coding in today's tech landscape. The bottleneck became evident—despite the increase in code generation, the number of engineers available for reviews remained fixed. To tackle this, Atlassian’s Developer AI team introduced Rovo Dev, a cutting-edge AI agent designed to streamline this crucial process. How Rovo Dev Transformed the Review Process Rovo Dev's implementation was nothing short of revolutionary. By leveraging advanced large language models (LLMs), Rovo Dev provides immediate feedback on code quality, efficiently enforcing engineering standards and ensuring PRs align with the relevant acceptance criteria tracked in Jira. With Rovo Dev automating the first round of reviews, Atlassian saw an impressive 45% reduction in PR cycle time—translating to more than a full day off the review process. The Advantages of Instant Feedback One of the most significant hurdles was the waiting time for the first code review comment, which contributed to an average of 26% of the total PR cycle time. With Rovo Dev, this wait was eliminated. The AI quickly identifies common issues such as typos, logic errors, and anti-patterns, allowing engineers to make corrections in real-time without the lengthy back-and-forth typical of manual reviews. Enforcing Standards to Improve Quality Beyond just speeding up reviews, Rovo Dev helps maintain consistent coding practices by embedding company-specific engineering standards into the review process. This integration not only enhances code quality but also aligns coding practices with organizational expectations—eliminating confusion and improving overall team cohesion. As the AI automatically checks PRs against established standards found in Confluence, developers can focus more on the value they are adding rather than getting bogged down by procedural errors. A Future Powered by AI and Continuous Improvement The positive impacts of Rovo Dev extend beyond just time saved. It has notably accelerated the onboarding process for new engineers, with those utilizing Rovo Dev merging their first PR five days faster than their peers. As Atlassian looks forward, the company plans to enhance Rovo Dev further by expanding its feature set to cover even more stages in the software development lifecycle. Rovo Dev signifies a remarkable shift towards AI-driven processes that promise not only efficiency but sustained quality in code development. Conclusion As software development actions shift towards more automated approaches, tools like Rovo Dev are paving the way for streamlined workflows without compromising on quality. The Atlassian team’s proactive embrace of AI illustrates a roadmap for others in the industry. By adopting such innovations, organizations can mitigate bottlenecks, elevate engineering standards, and foster an environment where developers’re actively engaged in creative problem-solving rather than administrative tasks.

Transforming Service Management with AI: The Impact on Atlassian's Jira Service Management

The Rise of AI in Service Management

Exploring Agentic AI in Jira Service Management

Real-World Applications and Benefits

The Future of Work: People-Centric ITSM

Conclusion: An Invitation for Innovation

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