The Scrum way of working is being elevated with the advent of AI. So, we will be seeing a new generation of AI-powered Scrum Teams.
If you want to upgrade your Scrum way of working with the power of AI, this guide is a powerful starting point. It shows you how to setup an AI-powered Scrum Team.
Use this link to download the full document:
https://www.agilevisor.com/#section_brevo-pop
A New Era of Collaboration Begins
The rise of AI marks a turning point in how we work, not by replacing human roles, but by dramatically expanding what those roles can achieve.
For Scrum Teams, this is more than just automation. It is the opportunity to surround yourself with a scalable team of intelligent digital AI colleagues. Colleagues that can handle the repetitive, accelerate the complex, and provide insights on demand—freeing Product Owners, Developers, and Scrum Masters to focus on higher-order thinking, strategy, creativity, and product impact. And for that to work, we need leaders who not only understand AI but collaborate with it to lead teams and projects smarter, faster, and more effectively.
This guide offers practical direction for Scrum Teams and their leaders to confidently step into the next era of collaboration. Join this exciting movement where you will no longer perceive AI to be a threat, but a new beloved team member.
AI-Powered Product Owner
Main Responsibilities: More focus on the market, customers, and stakeholders. Most of their time will be spent on product discovery, strategy, and complex problem-solving to move from backlog managers to true product leaders.
This table shows how Product Owners can leverage AI capabilities:
1- AI facilitators of meetings
Use Cases
- Using them as a meeting assistant in your meetings with stakeholders and customers
- Collecting and managing feedback in the Sprint Review
- Creating a list of stakeholders’ ideas in the Sprint Review for the Product Backlog
- Transcribing meetings and taking notes with AI
- Generating a summary of the meetings
- Searching the content of the meetings
- Interacting with your meeting recording for instant answers and insight
- Crafting follow-up emails
AI Tools
2- AI-generated sketch and prototype
Use Cases
- Showing ideas visually to stakeholders
- Creating prototypes for better understanding in Product Backlog Refinement
- Creating a Product Box
- Creating a visual elevator pitch
- Getting feedback from stakeholders based on a visual design
- Tweaking better innovation and making synergy in product design
- Creating prototypes to extract Acceptance Criteria and test scenarios
- Visual storytelling
AI Tools
3- AI-generated video
Use Cases
- Creating a compelling Product Goal / Product Vision video
- Creating a compelling elevator pitch for stakeholders and investors
- Creating studio-quality videos with your own AI avatars and voiceovers
- Creating a video with your own avatar to announce a new release
- Explaining how your product works
- Making a welcome video for meetings & events
- Making a video for the Sprint Planning summary
- Sprint Review kickoff video
- Making onboarding video for new users
AI Tools
4- AI-generated presentation
Use Cases
- Creating stunning report of market research and product discovery
- Sharing the EBM metrics trends
- Building burndown, burnup charts for the Product Backlog or any specific release
- Creating roadmaps and strategic plans
- Informing your stakeholders about the result of the Sprint Planning
- Communicating the progress of the product development
- Creating a compelling elevator pitch for stakeholders and investors
AI Tools
5- AI-generated audio
Use Cases
- Converting a potential customer profile into a podcast
- Communicating the Product Goal / Product Vision through a podcast format
- Storytelling of your product through voice
- Creating a voice message to inform your stakeholders about the result of the Sprint Planning
- Creating a podcast for the summary of the Sprint Review
- Creating a voice message with multiple languages for diverse and globally distributed stakeholders
- Converting Sprint outcomes into short audio updates for stakeholders
AI Tools
6- Shared
Use Cases
- Creating user personas
- Doing market research and product discovery through the deep search capability of LLMs
- Writing user stories and requirement documents
- Writing acceptance criteria
- Generating new ideas and thoughts for the product
- Asking for the guide for things that Product Owners don’t know
- Developing Product Goal / Product Vision
- Adding more details to PBIs in the Product Backlog Refinement
- Creating the Product roadmap and strategic plan
- Creating release plans
- Converting pictures of hand-written post-its into digital text
- Converting the voice of sales calls to text
- Generating improvement items based on the metrics
- Preparing agendas or discussion points for a meeting
- Summarizing text, generating scripts, generating email text, converting text into bullets, …
AI Tools
7- Others
Use Cases
Miro AI:
- Brainstorming ideas and refinement
- Generating user stories and ordering them
- Writing acceptance criteria for user stories
- Creating Product brief documents
Productboard:
- Collecting feedback from multiple channels
- AI groups related feedback and recommends features to prioritize
- Keeping your roadmap connected to real user needs
Zeda.io:
- AI assists in backlog refinement and feature prioritization
- Automates insights from user feedback, support tickets, and surveys
- Helps generate PRDs (Product Requirement Documents) with AI
AI Tools
AI-Powered Scrum Master
Main Responsibilities: More focus on the human side and all things that AI cannot do. Becoming a thought leader, knowing what AI-powered tools are available, suggesting, setting up, and combining them in the Scrum Team’s process.
This table shows how Scrum Masters can leverage AI capabilities:
1- AI facilitators of meetings
Use Cases
- Transcribing meetings and taking notes with AI
- Generating a summary of the meetings
- Generating action items for meetings
- Searching the content of the meetings
- Analysing the meeting sentiment
- Interacting with your meeting recording for instant answers and insight
- Crafting follow-up emails
- Scheduling meetings
AI Tools
2- AI-generated video
Use Cases
- Creating studio-quality videos with your own AI avatars and voiceovers
- Making an onboarding video for new team members
- Teaching a topic through an AI-generated video
- Making a welcome video for meetings & events
- Making a video for the Sprint summary
- Sprint Retrospective kickoff video
- Presenting impediments and their impact
AI Tools
3- AI-generated presentation
Use Cases
- Creating stunning Sprint reports
- Sharing the performance metrics trends
- Presenting the impediments resolution status
- Teaching Scrum and Agile principles
- Building burndown, burnup, and cumulative flow charts
- Visualizing value stream mapping
AI Tools
4- AI-generated audio
Use Cases
- Creating a podcast for the summary of the Sprint Review
- Creating a voice message with multiple languages for diverse and globally distributed teams
- Creating and sending a weekly audio tip about Agile and Scrum to your team to improve their knowledge
- Converting Sprint outcomes into short audio updates for stakeholders
- Reminding the meeting follow-ups through audio snippets summarizing what was decided and who’s doing what
- Retrospective Icebreakers: Creating fun or reflective voice clips to start Retrospectives with energy
AI Tools
5- Shared
Use Cases
- Generating new ideas and thoughts to better serve the Scrum Team, like generating Retrospective formats
- Asking for the guide for things that Scrum Masters don’t know
- Writing/updating the Definition of Done (DoD)
- Creating Sprint Goal / Product Goal / Product Vision
- Analysing performance metrics
- Asking for the guide to remove impediments
- Preparing agendas or discussion points for a meeting
- Supporting Developers with the estimation
- Role-playing difficult conversations to help prepare for conflict resolution
- Getting recommended learning resources (books, videos, courses) on Agile, Scrum, or leadership
- Summarizing text, generating scripts, generating email text, converting text into bullets, …
AI Tools
6- Others
Use Cases
- Brainstorming, Refinement, Retrospective with Miro AI
- Performance Metrics Management with Plandek
- Team Sentiment & Wellness Management with TeamMood
- Estimation with Taskade
AI Tools
AI-Powered Developers
Main Responsibilities: Define and configure AI tools, plus review and orchestrate the work that AI agents do.
This table shows how Developers can leverage AI capabilities in each step of their development process:
1- UI/UX Design
Use Cases
- Turning ideas or text prompts into wireframes
- Converting low-fidelity designs into polished, styled UIs
- Generating UX writing for buttons, tooltips, error messages, etc.
AI Tools
2- Front-End Development
Use Cases
- Converting UI design files (like Figma design) to front-end code
- Generating UI code from text prompts
- Generating code for React, Next.js, Flutter, Vue, Angular, HTML/CSS, JS, TypeScript, Tailwind, etc.
AI Tools
3- Back-End Development
Use Cases
- Generating back-end code from text prompts
- Code generation, API logic, database integration, and writing backend functions in real-time.
- Generating code for Node.js, Python (Django/Flask), Java, Go, etc.
AI Tools
4- Testing
Use Cases
- AI-generated Acceptance Criteria and test cases
- End-to-end UI testing with self-healing AI.
- Writing test cases with natural language (text prompt)
AI Tools
5- Deployment & DevOps
Use Cases
- Build, test, release, and automated rollbacks
AI Tools
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