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Generative AI for Scrum Teams

Who it’s for: Scrum Masters, Product Owners, and Agile teams who want to use Generative AI safely to accelerate planning, facilitation, and delivery.

Outcomes

  • Create sprint-ready user stories faster with AI-assisted refinement (without losing clarity).
  • Run more effective Scrum events using repeatable prompt templates and facilitation checklists.
  • Add lightweight guardrails to reduce risk (data leakage, hallucinations, and inconsistent outputs).

Your Learning Path

Follow these steps to master Generative AI for Scrum Teams

  1. 1

    Understanding AI Fundamentals for Scrum

    Learn the core AI concepts every Scrum team member needs to know before diving into practical applications.

    Do this exercise
  2. 2

    AI-Assisted User Story Creation

    Discover how to use AI to draft, refine, and validate user stories that are sprint-ready and stakeholder-approved.

    Do this exercise
  3. 3

    Prompt Templates for Sprint Planning

    Get repeatable prompt templates to streamline sprint planning, capacity forecasting, and backlog refinement.

    Do this exercise
  4. 4

    Facilitating Scrum Events with AI

    Learn how to use AI to prepare agendas, generate retrospective insights, and capture action items efficiently.

  5. 5

    Building AI Guardrails for Your Team

    Implement lightweight policies to prevent data leakage, hallucinations, and ensure consistent, trustworthy AI outputs.

    Do this exercise
  6. 6

    AI for Product Backlog Management

    Use AI to prioritize backlog items, identify dependencies, and align work with strategic product goals.

  7. 7

    Measuring AI Impact on Team Velocity

    Track how AI adoption affects your team's velocity, quality, and overall delivery predictability.

    Do this exercise

Steps - Free

24 Feb 2026

Step 1: Understanding AI Fundamentals for Scrum

Before using AI in backlog refinement, Sprint Planning, or testing, every Scrum team member should understand a few core concepts.

Without shared understanding, misuse is inevitable.

Author: Rod Claar
0 Comments

24 Feb 2026

Step 2: AI for Product Owners: Turn Customer Feedback Into Sprint Experiments

Customer & Stakeholder Discovery Prompts

This content explains how Product Owners can use AI to convert raw customer and stakeholder feedback into actionable sprint work.

Instead of treating interviews and notes as static documentation, the approach reframes them as structured inputs for rapid synthesis.

The model follows four steps:

  1. Input – Gather interviews, support tickets, surveys, and call notes.

  2. Clustering – Use AI to group feedback into meaningful themes.

  3. Risk Framing – Identify usability, adoption, and value risks.

  4. Experiment Design – Translate insights into 2–3 testable sprint experiments.

A practical exercise reinforces the method:

  • Paste 10–20 lines of real feedback into AI.

  • Ask it to cluster themes, surface risks, and propose three experiments for the next sprint.

The core principle: AI accelerates synthesis, enabling continuous learning and faster validation within the Scrum cadence.

Author: Rod Claar
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Steps - Members

 
 
✓ Featured Content

Generative AI Videos

A curated playlist of specific YouTube content.

Search Results

17 Feb 2026

AI-Enhanced Scrum: Transforming Agile Development with AI - April 22-24

Author: Rod Claar CST  /  Categories: Certified Scrum Developer  / 

Event date: 4/23/2026 - 4/25/2026 Export event

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  • Price: $749.00 - $949.00
$749.00 - $949.00

AI-Enhanced Scrum: Transforming Agile Development with AI

Artificial Intelligence is rapidly changing how modern software teams design, plan, and deliver products. AI-Enhanced Scrum shows how to integrate practical AI tools directly into your Agile workflow so teams can generate specifications faster, automate development tasks, and improve collaboration.

In this immersive three-day workshop, you will learn how to combine the proven structure of Scrum with emerging AI capabilities. The course demonstrates how AI can assist with backlog refinement, technical specification generation, development workflows, and overall team productivity.

By the end of the class, participants will understand how to apply AI tools in real Scrum environments and create development workflows that significantly accelerate delivery while maintaining Agile principles. :

Key Learning Objectives

  • ✅ Understand how AI is transforming modern Agile software development
  • ✅ Integrate AI tools directly into Scrum workflows
  • ✅ Generate technical specifications and development artifacts with AI assistance
  • ✅ Improve backlog refinement, planning, and estimation with AI support
  • ✅ Automate repetitive development tasks to increase team productivity
  • ✅ Apply practical techniques to accelerate delivery while maintaining Agile principles
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20 May 2026

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2 Apr 2026

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5 Mar 2026

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10 Nov 2025

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