Revolutionizing JIRA Management with Artificial Intelligence: Streamlining Workflow Efficiency and Enhancing Project Outcomes

Abstract

IT organizations are investing heavily on artificial intelligence (AI), though the value realization and areas of application of AI are still limited and not explored completely. Artificial intelligence applications are using large set of data to train the system to either generate new content or to predict the outcomes. Predictive analytics is used in agile management projects for budgeting, forecasting and capacity management. The article represents the use of cycle time and cumulative flow diagram metrics in ActionableAgile or JIRA to predict in agile development projects for forecasting of inflow of work and for the improvement of current work processes.

Keywords

• artificial intelligence
• predictive analytics
• actionable agile
• productivity improvement
• product support
• agile development
• machine learning
• cycle time