How AI and Agile Can Supercharge Scrum Techniques: Your Ultimate Time-Saver
In the world of business, time is everything. Agile way of working, particularly Scrum, is designed to help teams stay focused, work collaboratively, and deliver high-quality results in quick, iterative bursts called “Sprints”. But as the pressure to deliver faster while maintaining quality increases, there’s a new game-changer emerging—Artificial Intelligence (AI). By weaving AI into Scrum practices, teams can save huge amounts of time, allowing them to focus on what really matters: building high-quality solutions that meet customer needs.
93% of surveyed organizations by State of Agile Report, reported that Agile practices (including Sprint Goals) help teams focus better on value delivery. One of the most immediate ways AI can be effective for the Scrum Team is enhancing productivity and collaboration. Typically, Sprint Planning’s most crucial point is Sprint Goal which AI fosters better alignment towards Sprint Goal seamlessly, ensuring team stays on the same page without getting drained with bottlenecks. Additionally, AI reduces the cognitive load of repetitive tasks, such as updating progress, monitoring dependencies, or generating reports, by automating these processes. This allows team members to focus on high value activities, ensuring the sprint progresses efficiently and effectively toward its objectives and strategic KPI’s.
AI also brings real-time efficiency to tracking progress and decision-making. Scrum relies heavily on metrics like burndown charts, velocity, and backlog health to gauge progress and identify potential bottlenecks. While these metrics are essential, tracking them manually is often tedious and time-consuming. AI-powered tools can continuously monitor these metrics and automatically update them in real-time, giving Scrum Masters, Product Owners and team members immediate insights into how the sprint is progressing. AI can even alert the team to deviations early on, allowing them to make adjustments before small issues turn into bigger problems. With the Reporting feature we try to give real time data of your teams’ progress rather than bogged down in manual tracking and monitoring.
One of the most impactful areas where AI saves time is in the Sprint Retrospectives. After each sprint, Scrum teams gather for Retrospectives to reflect on what worked, what didn’t, and how to improve. This is a crucial part of the Scrum framework and teams spend 40 hours/month on retrospectives in total more than 150 hours which can be time-consuming and sometimes subjective. Teams often rely on memory or personal opinions to identify patterns, which can lead to missed insights. Teams that actively track action items from retrospectives in real time are more likely to make incremental improvements, resulting in a 20-25% improvement in sprint efficiency over time. As oNabu team who works with Scrum framework as well we inspired from our missing points and created AI Retro Agent to ensure Retrospectives are more objective, data feedbacked which helps teams identify root causes of problems more quickly and accurately without wasting time. This results in more effective retrospectives and speeds up the process of implementing improvements with AI generated Retro Reports with actionable insights.
In conclusion, integrating AI into Scrum isn’t just a nice to have it’s a game-changing time-saver that can completely transform the way teams operate. By automating essential tasks like Sprint Planning, tracking progress, and Retrospectives, AI frees up valuable time for teams to focus on collaboration, innovation, and delivering real value to customers. At oNabu we embraced AI since technology continues to evolve, its role in Scrum will only grow, making it an indispensable tool for teams that want to work smarter, not harder, and achieve faster, more efficient results in today’s competitive development world.
