Top 6 use-cases using AI & ML in Jira

Atlassian Intelligence is a powerful feature within Jira Software that leverages artificial intelligence (AI) and machine learning (ML) technologies to enhance project management and decision-making processes. It can also be used to streamline workflows. Here is our top-pick list, the six most beneficial practical use-cases, based on our experience of using it:

• Smart Issue Suggestions
  When creating new tasks or tickets, Jira Software can suggest relevant issue types, assignees, and priorities based on historical data, similar issues, and team workload. This feature helps users save time and ensures that tasks are accurately categorized and assigned.

• Predictive Planning and Estimation
  With Atlassian Intelligence Jira Software can forecast project timelines, identify potential bottlenecks, and suggest resource allocations to optimize project planning and scheduling. By providing accurate estimates and forecasts, teams can better manage expectations and deliver projects more efficiently.

• Automated Workflow Optimization
  Using AI-driven insights, Jira Software can recommend workflow modifications, task dependencies, and process adjustments to streamline project execution and eliminate unnecessary steps. This automation enhances productivity, reduces manual overhead, and ensures that teams follow best practices for project management.

• Intelligent Issue Prioritization
  Atlassian Intelligence can help Jira Software to dynamically prioritize tasks and tickets to ensure that the most critical issues are addressed first. This helps teams focus their efforts on high-priority tasks, minimize project risks, and meet stakeholder expectations effectively.

• Advanced Analytics and Reporting
  Atlassian Intelligence can analyse project performance metrics, trends, and patterns and this will help Jira Software to generate interactive dashboards, custom reports, and visualizations that offer actionable insights into project health, team productivity, and resource utilization. These analytics empower stakeholders to make data-driven decisions, identify areas for improvement, and track progress towards project goals.

• Natural Language Understanding (NLU): Atlassian Intelligence incorporates natural language understanding (NLU) capabilities to enable seamless interaction with Jira Software using conversational interfaces. Users can engage with the software using natural language commands, voice inputs, or chatbots, making it easier to create, update, and manage tasks. This NLU integration enhances collaboration, improves user experience, and increases overall productivity within the Jira ecosystem.